Mother's Day Gift Guide, Rorra in WSJ, Morgan Housel, Mehul Nariyawala, Sonya Huang, Stanford Review, Will Quist, Aidan Dewar, George Maloney
9 May 2025 · 201 min
John Coogan hosts a live show covering Mother's Day gifts, market news, and interviews with investors and founders. Morgan Housel discusses investing behavior, Sequoia's Sonya Huang breaks down AI product trends, and Michael Zelenko of Fastino argues small task-specific models will outpace large language models by 3 to 1 in three years.
Hey, let's go.
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Today is Friday, May 9, 2025. We are live from the temple of technology, the fortress of finance, the capital of capital. Let's go. It is Mother's Day. In just two days, the super bowl of pronatalism, baby.
It's a day we've all been waiting for. We've all been waiting for, especially your mother.
It's going to be amazing. Switch your mom to ramp.com.
Time is money.
Time is money. Save both. Switch your mom to ramp.com. get her on ramp. Seriously, what is your. I mean, what does your family run on if not ramp?
Yeah, I mean, it's a good time to ask what is your pay? You know, how are your parents thinking about enterprise security?
Yes.
Should. Should they be on Vanta?
Should they.
Do they need to be thinking about SOC 2 compliance?
Yeah. Does mom pay sales tax? Get her on numeral.
That's right.
Put that on autopilot. Take that off of her plate so she can.
Yeah. I mean, it's the greatest gift. It is to let your mom no longer have to be spending more than five minutes this, you know, a month.
Anyway, we're gonna be doing a deep dive on Mother's Day, giving you a gift guide, breaking down just some of the most obvious choices for what to get the mothers in your life and. But first, we want to take you through the market, give you a little update on what's going on, what's moving the market. Obviously, the big news is the US UK Breakthrough tariff truce. Trump announced this yesterday. It's the first post tariff pact. US keeps 10% blanket duty. UK cuts average duty on US goods to 1.8%. Autos. The 27.5% levy on British cars falls to 10%. Huge for the Aston Martin owners in the community, huge for the Bentley owners in the community, huge for the Rolls Royce fans. I'm sure there's a lot of you listening from probably in your Cullinans Black badge.
Yes. Or fortunately, Aston will be safe here. So it's a 10% tariff for up to. To 10,000 vehicles. Sorry, 100,000 vehicles. Aston Martin, for context, only expects to sell around 1,000 in 2029. So they have a lot of that quota to sort of grow into, which is great.
Something happened by Celsius. It hit me in the face and I think I'm gonna lose the eye.
John's gonna lose his eye. Hey, you don't need eyes for podcasting.
I think there's a certain amount of Caffeine level that it will blind you. Yeah. Anyway, obviously exciting. A little bit odd that this one's the first one because you were telling me that we actually have a trade surplus.
That's right, we do.
So you know, one step forward, two, two steps back potentially. But it seemed like the market, like it, it seemed like the market traded market bitcoins at all times. High all time highs or near all time highs over 100K. And the, the we are going to have Pippa Lamb from Sweet Capital come on on Monday. She is from some foreign land. I think she said it was like London.
The United. Is it United?
Yeah, I think about these places like that but I think Carthage or like Constantinople, like these like long lost forgotten lands and she actually lives in one. And so yeah, I'm excited to ask her like do they have movies there?
Yeah.
Do they, do they have telephones yet? What type of technology is going there?
Exactly.
Yeah. But she's going to come on and break it all down for us on Monday. That but in the meantime we're going to move on China. China surprised on exports. Headline exports of 8.1% year over year growth versus 2%. Estimates US shipments were down 21%.
Okay, but where's the data coming from? It's a big question because last thing so, so there was a report, I think it was maybe Monday. The days blend together but at some point China used to report on hundreds of different economic metrics from across the country. Things like land sales, local gdp, things like that. A while back they just fully stopped reporting on most of those metrics.
They stopped sending investor updates when you're mature.
Reminded me of anytime you have a angel investment or something like that, stop sending investor updates. Usually doesn't usually not a good sign. So China has stopped.
Sometimes they're just advancing to like, you know, just board meetings only they don't need to update that investors. They don't need to update the global economy. No, they're responsible.
Or the other one is a founder that's building in public. You know, just euphoric every single week.
Yep, yep, yep. And then all of a sudden they stop posting.
They don't post for three months. You're like, you know, that's how you know.
Aqua Hire inbound. Maybe. Maybe we should acquiire China. Yeah, merge them in.
Definitely something bring them on the team definitely should be in the conversation.
In the conversation. Nvidia is launching a new age 20. They're pushing forward. The memory bandwidth is trim below US export caps. The export caps keep Moving down. Nvidia keeps adapting the hardware. Pinterest popped big on a huge Q1 beat. They had earnings, Q1 revenue 850, 855 million MAUs at 570 million. AI ad tools push Q2 guide to 960 million to 900 million. Yeah, Pinterest is. There was an article in the, in the, in the information about how they've kind of changed the management structure. We didn't get a chance to cover it, but it is interesting. Gen z accounts for 40% of user base. Fastest growth is in Brazil and Indonesia. You know, these, these, these platforms are just valuable. I've actually been using Pinterest every once in a while to try and find like really esthetic reference photos for brand guides and style. It's pretty cool. It's also been overrun by AI slop in a really negative way. So I almost want to have a filter on there to say, okay, I'm looking for, you know, a newsman in a suit, but don't show me anything that was created after 2022 or the 80s. Yeah, yeah, yeah. Nothing that was uploaded, but some good stuff, some bad stuff and they're certainly pumping a lot of ads in there and the ads are pretty related to what you're searching for because it's such a visual medium. So congrats to Pinterest for the big Q1 beat. Coinbase also bought a company for $3 billion. Barely broke through. I mean this is a huge number size gong for sure. Would love to talk to Brian Armstrong about that. He's coming on the show soon. We will have him break it down. Would love to get the founder of Deribit on as well.
700 million in cash and 11 million shares of Just Coin. Yeah, they're crypto Coin shares.
No, their stock anyways, Just Coin Deribit.
Is one of the world's top btc.
I think it is the world's top options house.
Yeah, yeah. And so very strategic pickup for Coinbase. Makes a lot of sense.
Adds Europe and Asia as client base and regulated futures to Coinbase's spot. Heavy mix derivatives drive over 50% of global crypto volume. Very important for them to get in.
So excited about that saying they have 90% of. They're clearing 90% of crypto option open interest, which is around $20 billion in volume. So very impressive.
On the flip side, company was started.
In 202016 based splitting time between Amsterdam and Panama.
Oh really?
Kind of a fun, fun place to bounce between.
Interesting. I'm sure that's for like Regulatory reasons, right?
Yeah.
On the flip side of crypto, Celsius founder Alex Mashinsky was sentenced 12 years for fraud tied to the 2022 Celsius collapse.
2020 bees at the peak 20 billion.
A billion they he made a $48 million personal gain via token manipulation. The still deciding what the restitution figure will be, what he'll have to pay for that. Prosecutor sought 20 years. Defense pleaded for less than four years, citing cooperation. But I don't know how much he was cooperating because he was selling merch that was like all about like bankruptcy and stuff. It was really, really crazy. A lot of great Coffeezilla reporting out there. If you want to go take the stroll down memory lane and hear about the Celsius debacle. But this is a rough time. I think they were doing okay while the market was up, but once the market pulled back.
The yield that they were offering was considerably high. Yeah. Given that interest rates, the risk free yield was about zero at the time.
Yep. And the last story is that there's a $3 billion lawsuit against Google in Italy. We won't do our Italian accents today, but I'm sure we'll be tracking it. It's part of the ongoing pressure on big tech, especially abroad.
Google getting into suiting?
No, actually search. But this goes back to 2010 to 2017. Google was showing a search bias against a particular group in Italy. And so they're claiming that Google shopping, you know, hurt them to the tune of billions of dollars and they want restitution. And so the financial impact is pretty limited given that Alphabet's 2024 revenue was 320 billion. But the legal overhang is certainly a headache for Google. But anyway, good luck to them.
Interesting dynamic being internal counsel at a firm like Google where there's just like, probably. Can you. I don't even. I don't even. Maybe these. I doubt you could probably figure. I'm sure you could figure out the number. But I wonder how many inbound lawsuits, complaints Google is getting on a daily basis. Right? It has to be.
Yeah. Hey, want to settle this with me? I mean, there was that whole story about that guy who was just sending fake invoices to big tech companies, just being like, yeah, if it's under ten grand, they'll probably just pay it. Just doing that constantly. Wouldn't work.
Wouldn't work.
Wouldn't work with ramp.com. yep, that's right. Anyway, let's pull up the show, the run of show, to kind of give you guys an idea of what the rundown is Today we're taking you through the Mother's Day gift guide. Rora was featured in the Wall Street Journal. We're going to break it down, we're going to do some timeline, tell you some other stories. Then we have two anons from Stanford talking about the Stanford Review. The Bombshell Report from the Stanford Review. We got Morgan Housel, Sonia Wong, Will Quist, Aidan Duer, a bunch of other folks coming on founders announcing rounds, announcing new products, bunch of VCs yapping. Should be a good show for you. And if you're following the market update and you want to trade it, get on public.com investing for those who take it seriously. Multi asset investing. Industry leading yields. They're trusted by millions, folks. Go to public.com Aston Martin sponsor.
Aston Martin sponsor.
Should we do six facts about David Steiner, the new U.S. postmaster General.
So I mean, and this is. Is one of the most coveted roles.
Obviously if I were going in the admin postmaster for sure. I mean I think of myself as a master of posting, so it would.
Make sense it could. You know, the extended. The full title is Poster Master General.
Poster Master General.
Most senior poster in the country.
Maybe they should have a Post Economic Master General.
Post Economic General.
Yeah. Post Economic General. He's just like, yeah, actually I can't really revitalize the DoD because I'm actually in Santo Pay and F1's coming up. So I'll get to it. But I'm not really checking email right now. I haven't checked this inbox. So good luck getting in touch with me. We're just like, that's exactly who we want. Anyway, he spearheaded a comeback for Waste management. He's a FedEx director who led turnaround of Waste Management after insider trading scandal. Some of the company's top executives in the 1990s falsified financial results. That's not good. Uh, really, really playing into the. The meme that, that the trash companies are run by the mafia. Right?
Yeah.
Uh, he joined the company as deputy counsel in 2000. In less than four years, climbed the ranks to become CEO. He streamlined operations. He calls himself the walking embodiment of better lucky than good. I like that.
Great.
Uh, that's because he went to work for Waste Management. He turned down a job offer from Enron.
Speaking of better lucky than good, uh, I was listening to Senra's episode on Jim Simmons. Sorry, Simons, Simons. And Jim Simons was obsessed with being lucky. He's like, I wake up every day, I just think how lucky Can I get today?
That's amazing. So he's stepping down as director of FedEx because FedEx of course competes with the US Postal Service, which he will be running. Honestly, surprising. Could have been running both.
I would have liked to see FedEx.
This whole divestiture thing we got to get rid of.
Yeah, I would have liked to see FedEx kind of merge with the USPS.
I would like to see if someone goes in the admin, don't make them divest. Make them go 10x levered, whatever. They're long. Yeah, just really stake it off. Risk on.
You're going to get a pension after this.
But if you make any mistakes, your bags are cooked. A 10% down draw from any of your bags, you're wiped. You're wiped. So don't mess up. It was really high stakes. Yeah. So he has a big job ahead of him. The Postal Service has been hemorrhaging money for years because of declining mail volumes, limits on what it can charge customers, and a costly mandate to deliver around 168 million addresses six days a week. Steiner must also address persistent delays of mail and package deliveries in some parts of the country. He was hand selected by Trump and he says he wants the Postal Service to remain an independent agency. I don't like that. I think we should take this thing private. Yeah, spack it.
Spack it.
Yep. Let's see. Let's let it rip.
Let chamath cook.
Anyway, I'm sure you all are aware of Mother's Day coming up. I'm sure you've already done a lot of your prep, bought all the gifts, but if you haven't, we have a gift guide for you today to take you through some of the. Just some of the basic options that you should be thinking about if you're in the audience. We know that you're wealthy, most likely post economic, so you got to make sure that the mothers, you know, you're pre.
Post economic, pre, you know, impending.
Yeah. You know, you could probably take a non recourse loan against your shares if, even if you're a series B founder and then drop that on something like the pink star. It's a 60 carat vivid pink diamond.
Ring coming in at only $70 million.
But it's, I mean, at that price, with that, you can't say no. Exactly. I mean, we talked about the graph hallucination Rainbow diamond watch, 110 carats for the wrist. And everyone's just going to know like, wow, that mom has a great son. Yeah, for sure.
He or she really loves their mom.
I mean, if you want to take a little bit further, you could go diamond tiara.
Yep.
A crown.
These have tiaras kind of fell off.
They did.
But that just creates an opportunity for them.
Bring it back.
So back. And I think that 2026 is feeling like it will be the year.
Yeah.
Of the tiara.
Yeah.
You know, your mom is going out on a little morning stroll. She's going to want to throw on that tiara.
Tiara. Exactly. And just putt around, let people know. Yeah. A lot of people say, oh, flowers. Flowers are only for Valentine's Day. But I think if you rethink what flowers can be, you can get to a really interesting place where. Yeah, exactly. So Juliet roses, orchid rarities. You can push a bouquet up into the six figures. If you really think that I thought.
You were going to say, basically drop an entirely new rose garden into her.
Backyard or hire a team of bio bioengineers to engineer an entirely new breed of roses never before seen. That's a reasonable thing.
Not unreasonable even to be getting ahead of it. Thinking about next year, going to Monsanto, saying, hey, look, I want to develop, you know, an entirely new.
Yes.
You know, group of flowers. Completely bioengineered.
Yep. You can also take some of those flowers, dip them in 24 karat gold, boom. You have an eternal bouquet. They'll never wilt.
That's right.
That's going to run you like 40k. But worth every penny.
Totally.
What else should we recommend? I mean, obviously renting an entire tropical island for a family week. Totally doable. Around the world, private jet, grand tour. Very good option. I take it to space. We saw this with, with Jeff Bezos.
Totally. But expect, I mean, you've been saying this for weeks. You think that you won't be able to get on a blue origin flight for the next three years after Mother's Day because everybody is gonna be sending their mother and their mother in law to space.
Yeah. They made this whole thing with the blue origin. Oh, it's all the women flight. What about all the moms? They should have just done. Really focused on just moms in space. That's definitely the future.
That's viral. Another favorite. We talked about this. Just a good old wire transfer. Just a big wire transfer. You remember as a kid.
Totally. Birthday money.
Yeah. Yeah.
Oh, I got a hundred bucks. You got 50 bucks. I can buy a video game.
The logic at the time was this kid knows how to spend it better than I do.
Exactly.
Flip it on your mom, put it on your mom.
Yeah. And six figure wire transfer.
Six figure wire transfer. Boom. Boom.
Yep. It's great if you're, if she's into purses, you know, we talk about Birkins. If you're going to go Birkin, don't go basic Birkin, go Hermes Himalaya Birkin with rare crocodile diamonds. Yes. It's going to cost you 200, maybe 500k.
Yeah.
But it's going to stand out in a sea of monotonous Birkins. Right.
For the average platform VC, that's 20% of your annual comp. Yeah. Not even counting carry. Right. So it's just, it's, it's the least that you could do.
Yeah. So in fact, if you see, if you meet some GP and their mom doesn't have Himalayan Hermes Birkin with crocodile and diamonds on it, you would think like that. Oh, their funds not doing well. Yeah, exactly, exactly. They're not raising, they're not ready. They definitely can't lead my next round.
Yeah.
So I got to start talking to other folks. I got to have run a, run a bigger bidding process for sure. Start networking. But I mean, if you want to go, if you're more serious, you should go with the Muawad Thousand One nights diamond purse.
Yes.
Guinness Book World records of handbags. I mean, going to be hard. Such a big deal at Birkins, but whole order of magnitude higher. 3.8 million dollar bag.
Yeah.
But you know, it's really the only way to stand out.
One of one.
One of one. Yeah, exactly.
The armored Rolls Royce.
This is a great choice. This is a great choice.
Runs going to grab coffee if they're.
Still dropping off the grandkids.
Dropping off the grandkids 100%. Yeah. Just getting, you know, ideally, knowing my mom, 700 horsepower is kind of like the right range for a daily.
Totally.
My mom drives a Prius, actually. But I, I think, I think.
Have you considered swapping a V12 in there? Engine swap for Prius?
Yeah, maybe. Maybe just putting whatever car she has.
Just soup it up.
Engine swapping a Cayenne turbo GT into the, into the Prius.
Yeah.
And so, you know, because she wants to be low key.
Yeah, exactly. She, she's comfortable. She knows what the buttons are.
Yeah.
But that doesn't mean that she can't.
Have a little more, A little more power. Yeah, I like that.
I mean, Zuck did this for Priscilla, right?
Yeah.
He made the, he made the custom turbo GP minivan.
Yes.
Which is sick. But you could have gone further. You could have done you could have gone, you know, Lamborghini Urus minivan.
Yeah.
You could have gone Cullinan Black Badge minivan. Mansory.
Yeah, There you go.
I think we're getting more. I think it's really like the creativity of just, you know, mixing these different cultures together with key.
I think under underutilized options, something you can do last minute, take your mom's phone, bring it to a jeweler, have them bedazzle. Have them bedazzle the back. And what I actually like about this is because the iPhone is uneven on the back. Right. It has a camera. You can just put the diamonds around this side so it will actually sit flat. Right.
Oh, that's smart. Yeah. So it's actually like an upgrade. Practical.
Yeah, it's practical. It's more practical, but it's also fun. She's taken a picture of the grandkids and so definitely something there.
I mean, we see a lot of these tech billionaires, they're super yachts, but you never hear about the mothers of tech billionaires getting their own super yachts.
Totally.
And so I would recommend calling a feed ship, start customizing something now, I mean, two days, you're not gonna be able to do much, but maybe next year, maybe the year after you start.
You want to be thinking three, four.
Years, thinking decades for Mother's Day at minimum. Yeah, absolutely. Absolutely. You could also do private IMAX theater at home for the cinephiles.
Totally.
They're into film.
Totally.
Just dig a massive hole into the house. Yeah.
Under.
Great.
Check out the, you know, reach out to the Boring.
Yeah.
I mean the last one that's pretty easy is just paying for a full domestic staff for.
You know, I like this.
Yeah.
Why is. Because you can write a card and say you're going to do it, but you get a little bit of time to actually find the staff. Right. To find the individual people that are going to make up that staff.
Yeah.
And so it's one of those great last minute option that will be unforgettable.
Yeah.
I really feel like if the household is running smoothly, the staff is firing on all cylinders. Ideally, you have kind of an Alfred type of butler who really oversees the staff. And I would love to see that type of, you know, house manager, estate manager. Using linear. Totally. Totally. To actually. Because linear is a purpose built tool for planning and building products. You want to be building custom software to run your smart home. Don't. Don't. The ideal Alfred.
The ideal Alfred was a PM in big tech.
Exactly.
Take that sort of ethos into the home and really just run it like it's a product with millions of users.
When is the registration on the Mansory Cullinan due to let's make sure that the license plates are coming. Track it in linear.
Boom.
Exactly. So this is a system for modern software development, streamline issues, projects and product roadmaps. I mean it's the perfect Mother's Day gift really.
It really is. Shout out to Matthew. I had a good call with him this morning. Runs a lot of the marketing over at Linear.
Anyway, let's quickly take you through the run of show. Let's pull that up to show you what's happening today. We're going through the Mother's Day gift guide, but we also have some massive news. Rohr was featured in the Wall Street Journal. We're going to break it down. We'll do some timeline. Then we got the Stanford Anon coming on and then a bunch of other.
Guests anons over at Stanford. Yeah, they wrote a pretty inflammatory piece which I'm excited to have them break down for us.
But let's take you through the Wall Street Journal. Rora was featured.
Yeah.
So for those that are new, I started a company called Rora with my co founders Brian and Charlie, long time ago at this point. Spent a lot of time in R and D and launched last year and it's been just off to the races, which has been great. And anyways, Rora was in the Wall Street Journal yesterday and I got a little bit of the backstory here. Somebody reached out apparently with a just like a random Gmail and was like hey, I'm doing some product testing. I get Aurora or whatever. Brian ended up sending and the article turned out really well. So we can read through it to the water filters you actually want in your kitchen. A new wave of models making grand claims regarding their pur. But our test revealed four clear winners when it came to flavor, functionality and sheer counter appeal. For many people, the thought of water filters triggers the tiresome realization that theirs needs to be replaced. Or worse, that the taste of their filtered water isn't what they actively crave, the way they once crave that chilled bottle of Fiji or Evian and probably still do despite the new news images of masses of plastic choking the oceans. I still have hopefully much way less now. But I still, you know, as of last year had a bunch of friends that were just drinking tap water, which is actually completely insane in our year 2025. So anyways going on and let's be honest, that plastic pitcher has never again looked Quite so crystalline as it did straight out of the box. Has it streaking water out of plastic. Just don't do it. So good news, it doesn't have to be that way. According to market research firm Fortune Business Insights, the global demand for water purifiers is exploding. And recently water filter makers have, pardon the pun, flooded the market with models ranging from sleek and even glamorous to sporty, high tech and industrial chic. Rora. I'm looking at you. The question then is how to choose a system that fits your drinking needs and aesthetics without sacrificing efficacy. Over the last several months I tested everything from single bottle to multi gallon filters. Blah, blah, blah, blah, blah, blah blah blah. Let's just talk about RORA for the family.
Is RORA numeral yet? Gotta pay sales tax, right?
Working on it.
Gotta get on sales tax. Put that sales tax on autopilot integrated.
There we go. There we go.
Run it, John. Sales tax and autopilot spend less than five minutes per month on sales tax compliance. Anyway, congratulations to the whole RORA team and you can go pick one up. What? Rora.com rora.com let's do a quick Poly market review. There's a few markets that I'm tracking. There's a few markets that you're tracking. I'm interested in this Tesla Elon Musk CEO replacement thing right now. There was, there was this leaked Wall Street Journal article saying Tesla was thinking about replacing elon Musk as CEO. Polymarket has a 13% chance. I think this is the perfect thing to be tracking on Polymarket. And now then they also have. Who will replace elon Musk as CEO. Of course 86% says no CEO announced in 2025. But JB Straubel is sitting there at 2%. I don't know if you know him, he runs Redwood Materials. One of the earliest employees at Tesla has been there for a long time. Redwood Materials does battery recycling. It's a huge company, but you can imagine them kind of putting together. So I don't know, Wildcard. There's a couple other folks to recycle that are, that are interesting. Gwen Shotwell is actually sitting here at 1%. Dara Khosrashari @ Uber Dark Horse. Dark Horse, Mary Barra. There's a bunch of other interesting people, but that is a market that I'll be tracking over the, through the end of the year as the, you know, the peanut gallery yaps about Elon, where he's going. The last thing that's interesting. Largest company at the end of May, Microsoft overtaking Apple.
Mogged.
Mogged. Yeah. Apple had.
Microsoft has a lot of momentum right now and Apple has the opposite. A lot of different forces coming into play. Obviously the trade wars kind of botching AI the big thing. Yeah. I'm just very interested. It's interesting that Google is not even in the conversation on this market anymore. Obviously impacted over the last week from some of the comments that Apple made in the.
Yeah. Trial Nvidia is still sitting at 4%, kind of that wild card because it, it moves much, it's much more volatile stock because you know they can just blow out 1/4 if someone orders 10 million H1 hundreds or something. But obviously a rough go with the, with the international sanctions and the chip bands and whatnot. What else are you tracking?
Which company has the best AI model. End of May sitting on 74%.
It's so crazy how you were talking about like they've trained such incredible models. They dominate the evals and invented the transformer. Absolutely insane team. And yet really struggled to actually break through and have this crazy counter positioning where the more they do with AI search, the more it takes away from their search. Is the classic innovators dilemma. Right?
Yeah, yeah.
Everyone said AI should be sustaining advantage and I think it could be in the sense that like they'll ven this into GCP and cloud platform and they will be a beneficiary of AI. But they do have some serious, serious product challenges.
Yeah, I was thinking they have. There's that Wario meme which is like I've won but at what cost? And that's really.
Isn't that from Avengers originally?
Yeah, but it was like popularized by this like image. It'd be too hard to pull it up.
But anyway, xai is actually second place, which is interesting because you'd think OpenAI based on the performance of the consumer app would be more in the conversation. But OpenAI is only sitting at 5%.
Yeah, this is based on model, this is based on benchmarks.
Yeah, of course, of course. Benchmarks don't matter to ChatGPT anymore. Just user retention, I think.
Yeah.
And stuff. And ads and things.
Maybe, who knows, put an ad in it.
Anyway, speaking of ads, we should talk about, talk to you about Vanta Automate Compliance. Manage risk, improve trust continuously. Vanta's trust management platform takes the manual work out of your security and compliance process and replaces it with continuous automation, whether you're pursuing your first framework or managing a complex program.
Anyway, did you know that Vanta was one of the Fastest growing vendors on ramp last month.
I did not know that.
That's great.
Congratulations, Cruising.
Congrats to Vanta.
Well, we got to move back to Mother's Day because we forgot to take you through some of the really obvious houses that are on the market. If you're looking for a house for your mother this Mother Day. Mother's day, there's an $8.5 million California home with a backyard railroad.
And so train heads are going to be scrambling.
A lot of moms have kids. The kids love trains. Buy a house with a railroad in the back.
Trains.
When David and Sherry purchased their La Canada Flintridge home, not too far from me, not far in 2008, they found the rusted remnants of train tracks where a previous owner had built a backyard railroad. It turns out that La Flidge, home to a number of Disney employees, was once a hub for garden railways. While the family weren't train enthusiasts, they were intrigued with the help of a one time Disney imagineer. They spent about a year recreating the railroad, completing it in 2011. Today, the roughly 530 foot circuit has a tunnel and a train station with a working crossing light. The train itself is faux steam battery powered locomotive and caboose with two riding cars. This is incredible.
This is the ultimate backyard toy for the grandkids.
It's such a flex. Everyone has. Oh, infinity pool.
Oh.
Oh, Jim. Yeah. Do you have a railroad in your backyard? No. The quote's so good. David, the owner is like, there's something universal about trains. They bring out the youth and everyone. However, their railroad needed a new conductor. They put in. They put the 1.55 acre property on the market for 8.5 million. They're, they're semi retired and moving permanently to their second home in Park City. He's a financial executive, grew up in Chicago. They married in 1982 and later settled in Flint Ridge, a semi rural community about 13 miles from downtown Los Angeles, where we are right now.
Home of LA's auto community. If you ever want to be scared driving, just drive up. Yeah, that's, that's like, I mean, effectively home. You have to drive through La Canada to get to Angeles Crest Highway.
Yeah.
And if you ever want to feel like you're gonna get run over, go on. Ach. And try going the speed limit. People will fly by you at four times that.
It's awesome. Apparently, Disney also had a railroad in his backyard. Walt. Walt Disney in H in homeby Hills in LA. The original railroad was built in the 1960s. According to the sun, who said his train loving father was friends with Johnston and Kimball. When the new family bought the house, the tracks had been dismantled and largely built over. At first, the railroad wasn't a priority. When David had played with toy trains growing up, he said he wouldn't describe himself as a train guy. But a friend offered to introduce David to the late Bill Tyson, a one time imagineer and garden railroad enthusiast who could help restore it. Then they visited the South Coast Railroad Museum near Santa Barbara where they rode a garden railroad for $1. At the end of it, we said, okay, we have to do this. It's just too much fun. It was the most expensive dollar I ever spent. That's hilarious. It's great.
We have another property.
Another property. This is another good option for Mother's Day. If you're in the market to buy your mother a house, she's trying to.
Move south to the tropics. Yeah, why not Fort Lauderdale?
Better weather. Fort Lauderdale. There's a new massive waterfront home.
15,000 square feet, $39 million.
And it includes eight separate bar areas. So for the entertainer.
So a heavy.
I mean, people are saying alcohol is coming back, you know. Yeah, there's so much alpha with alcohol being out of style. Maybe go long alcohol.
Yeah.
And enjoy the eight bars. But you could also serve mocktails and beverages.
That's right, kids, you could do energy drinks.
Energy drinks, yeah. For more than 20 years, Steve Savour has been hosting lavish parties at his waterfront mansion in Fort Lauderdale, Florida. Last year he hosted a Barbie themed gala, decking out the house in hot pink and dressing up as Ken. I always say, if the house burned to the ground and I didn't have any insurance, I got my money's worth out of it. The 64 year old retired bachelor. That's hilarious. He's now listing the property known as Villa de Palma for $39 million. He says he travels frequently, especially during the summer months, and wants a home that doesn't require as much attention. So the house is.
Saver, who was trained as a lawyer, made his fortune in merchant banking and is a former CEO of the Pittsburgh based communications company Comnet Erickson. Retiring at age 39, he assembled Villa de Palma over two decades, starting with the purchase of the main house for about 1.8 million in 2002. Property records show Florida is known for massive fluctuations in their housing market. In the years since, he has spent millions adding more land to expand his footprint to roughly an acre. One of those properties included a 5 bedroom house which he raised around 2000 this guy just turned making this party house into his full time job.
Raised. Raised means demolished by the way. And so he says. To celebrate the demolition, he hosted an Animal House style toga party. He spent two weeks decorating the house to look like a fraternity house. Then the night before the demolition, he and his pals tore up the house with sledgehammers.
Can you imagine that?
At the end of the night we were throwing kegs through windows. He said, what a bro. This is so insane. After tearing down the small house, Savor has expanded the main house, completing the project around 2010. The eight bedroom Mediterranean Mediterranean style estate has about 15,000 square feet of living space and two large large outdoor pools. It's well equipped for entertaining with a wine cellar and eight separate bar areas, including one inspired by Hotel Du Cap Eden Rock in the south of France. Have you been?
No.
And Savor calls another bar on the rooftop Tequila Tower. This guy is such a party animal. A giant table in the space can hold plenty of people to dance on after tequila has been depleted. Savage. There are two relaxation rooms properties within walking distance of the beach in downtown Fort Lauderdale's main shopping strip. I would come down for long three day weekends and ended up staying two weeks. When I retired, I made my playground my home. What a legend. Anyway, great option.
I'm interested to see where this one lands.
Yeah. Anyway, we have two minutes till our first guest is joining. Let's do some timeline. What else is this post news? Actually let's do an AD8 sleep. What's new? Pod 4 Ultra Pod 4 has all the signature features you love about the pod. Plus new groundbreaking upgrades. 5 year warranty, 30 night. 30 night risk free trial free returns, free shipping. You gotta love it.
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I did, terribly. I got 85.
96.
96. It's rough.
93 minutes of deep sleep.
One last potential gift for mothers on mother's day. A billboard. Go to adquery.com they make out of home advertising easy and measurable. Say goodbye to the headaches of out of home advertising and buy a massive out of home campaign.
Huge opportunity to just buy.
Just thanking your mother for all the chats.
Five billboards closest to your mother's home.
So she's wherever she lives, driving around.
And make it so that she can't leave her house. Well, without seeing how much you love her.
Exactly.
So we got a post here from. We'll cover this and then we'll go into the guest from Bucko Capital. Bloke. He Posted back on March 3rd, new Mag 7 Rheinmetall, which is German's arm, German arms manufacturer Solana V.C. s coin, Palantir Salesforce for.
Okay, he's not exactly the.
He's not pulling punches. Hims dtc. I can't say anything bloke. All new appliances and vehicles purchased before the tariffs, gold. And so he then quotes it and by saying Rheinmetall is up 54%. Salon is up 15%. Palantir up 42%. Hims up 26%. Dave up 60%. Used vehicles up 10%. Gold 14%. And the Max 7 is down 3%.
I wonder if this is actually just over the last two months. Maybe. Yeah, I guess this is. Do the tariffs hit March 3rd? Something like that. Anyway, congrats to him for calling it. Clean up the language if you want to be on the show more. Anyway, they said to cheat on everything, so I decided to cheat their company. I generated 84,000 believable resumes to spam their job applicants and send AI agents to waste their time. I'm shorting the VCs defending them. You see this fight that's gone.
Can we.
Michael, are we able to pull this up on the screen?
So Rise is trolling Roy, former guest on the show.
So, yeah, Roy has a company called Cluli. He is helping people cheat on everything. Right now, I think they're focused on sales calls. He's attracted a lot of controversy and Rise is messing with him a little bit by just using AI to spam Roy with an almost inconceivable number of applicants.
Somehow I don't think it's going to affect Roy. I think he's going to be just fine.
Roy's built different. He's hiring a videographer in San Francisco with for between 500k, 300 to 500k. Absolutely massive numbers for a vlogger. So if you want to vlog and make half a mil a year, it's crazy. Head over to Cluley.
Head over to Clulee. Good luck to him. Anyway, we should have our first guest joining right now or set of guests. Actually, I think we'll have two voices on the show. They're both anonymous. They've been involved in the latest report from the Stanford Review about spying on campus. You're not going to see their face, you're not going to hear their names, but you're going to hear us ask some questions about the report and try to get to the bottom of what's going on on campus and dig a little bit deeper into the viral Stanford Review article that went up most recently just a few days ago. Anyway, welcome to the show. Can we hear you? Can you hear us? Can we hear you?
Yes. Thanks for having us.
Thanks for having us. Great to be here.
Great to have you.
Thanks for joining. Can you start by. I don't know how you want to characterize your involvement in the story. I know you want to remain anonymous, but can you just give us the high level on how the report came together and what the key findings were?
Yeah, let's do it. So the Stanford Review spent over one year investigating Chinese academic espionage at Stanford. What we did is we talked to Stanford students, we talked to Stanford faculty, we talked to Stanford China experts, and we talked to Congress people about this. And at the end of our investigation, we compiled a bunch of anonymous reports for people working in AI labs, student researchers and faculty. And the overwhelming conclusion was that there is essentially widespread intelligence gathering at the behest of the CCP at Stanford.
What does that actually look like? I mean, no offense to the Stanford folks, but like, it's undergrad. It's not exactly like a proprietary AI lab or like nuclear weapons program. Like, what are they trying to steal?
Got you. So I'm going to pass you over to my colleague.
Sure.
And she's going to talk a little bit about what her experience with espionage looked like.
Sure, yeah. So a lot of what espionage looks like, you know, on an undergrad level is Chinese students and researchers trying to basically collect any and all information about Stanford that they possibly can. So, you know, Stanford is an open research institution, so a lot of the things that are being reported back to the CCP aren't exactly secrets. And, you know, obviously, you know, it's not as bad as stealing defense secrets.
Yeah.
But the issue is that it's happening at such a massive scale because they, the CCP essentially has all of their students reporting back to the CCP with any and all information that they have.
Right. So once one Chinese international student characterized it like this, many Chinese students have handlers. The CCP wants to know everything that's going on at Stanford. This is a very normal thing. They just relay the information they have. Now, with regards to sensitive research, we're not just talking about the undergraduate level, we're talking about the graduate level. And these are some of the best AI labs and best robotics labs in the United States of America and the world at large. What they want is not just published papers because you can imagine you can't replicate papers just via postpone. They want the methodology Sent back. They send back communications channels, they send back people that are involved with the research and other Chinese internationals that are working on it so that they can replicate this research at China.
How would you rate the university's reaction to the piece? There's obviously been a bunch of conversation and chatter online, but I imagine you guys have been having conversations as well.
Yeah, so we actually just published today, Larry Diamond, Matthew Turpin wanted to publish sort of a response article, so that was also published in the Stanford Review. And they, they came out in support of our article, which, you know, was good. And then Stanford also came out with a statement saying, you know, they take this very seriously and it is important to them. You know, we are sort of under the impression that there's not much that's going to be done about it because on some level everyone knows that this is happening and nothing is really being done about it. On a university level, they really want to kind of stay out of things.
Right. I mean, Matt Pottinger, the, one of the, one of the guys that commented is the former US Deputy National Security Advisor. Matthew Turpin worked as the China senior Advisor to the National Security Council. These guys have seen this happening for years on years. The issue is that Stanford is an open knowledge research institution. That means there's no secrets and that means it's very hard to prosecute people for sending back sensitive research information to China. So really what they get people on is just their visa. You know, they're working for the pla, but they haven't told the authorities about it. So what needs to happen is we need to have people that are sending back this information, registered foreign agents, and set up new laws and new legal guidelines that prevent people from being able to send public information at research institutions back to foreign governments.
Right? Yeah. And the other thing too is, you know, we also need to recognize that the students are actually victims in this situation. I mean, the CCP is exploiting them. They are essentially crowdsourcing, you know, espionage at massive scale at universities all around the country. And they are. There's this thing called transnational repression. And basically, you know, if they don't want to report back to the CCP, if they have any reluctancies or if they don't comply, their families can be threatened, their livelihoods, their scholarships. So, you know, it's really a sad situation for them as well.
Yeah, I mean, totally.
Matthew Turpin, who worked with the nsa, even said at Stanford there's been Chinese international students who had their parents brought to the police station because they refused to turn over Stanford's research information. So if you don't comply, you will face penalties from the Chinese Communist Party and your parents and your family back at home in China may be put in harm's way. And we've seen that happen.
Makes sense.
Yeah, it's incredibly challenging. You know, you could be here, your parents could be here, and yet if you have even one family member at home and a grandparent, a great grandparent, you know, there's some amount of risk.
What I don't know if you saw this post by Kim Mai Cutler, who I think is at Initialized. Right. Partner at Initialized. She said this, this report has pretty much all anonymous sourcing unfortunately. And so it does not seem like a good platform upon to, upon which to argue that many, most or all Chinese nationals or first gen Chinese students are spies. How do you interpret that kind of criticism of the piece?
Right, let's go through this point by point. So first of all, when you look at how the CCP operates, they have 2017 National Security Law. Under Article 7, all Chinese citizens must comply with national intelligence and provide information and keep secrets when they're asked. So straight out of the gates, all citizens must comply at the face of penalty, working with security services. So anybody who's asked at Stanford to do something for the CCP must do it or they will face legal penalties in China. The second point, we have talked to Chinese international students. They have families at home for the same reason that there's transnational repression. They cannot go on the record and say these things with their name out there because their families will be taken away, their families will be brought to police stations. It's already happened with research with regards to China experts. We've had Matthew Turpin on the nsa, we've had Matt Pottinger in the nsa, and then we've had Larry diamond all come out in support of our article. They've said this is a decades long relentless interference in Stanford to misappropriate our sensitive research technologies. All the experts have agreed with us. But at Stanford we've seen a culture of silence and fear talking about this issue because it's characterized as racism. So 166 Stanford professors wrote an article to the Department of Justice saying that we need to shut down the Chinese and China Initiative, which was an initiative that sought out Chinese spies because it's racist. But what that fails to recognize is if you don't shut this down, you have Chinese students who are the real victims here. So it's China who is profiling their citizens and victimizing them. It's not the usa. This is not racial profiling because we're just looking towards Chinese nationals who, who are being repressed by their own government.
That makes sense. Putting aside the kind of, like the geopolitical issue of China specifically, how are you thinking about not suffering from a lack of brain drain? I feel like the majority of tech companies, like the tech industry, might collapse if we didn't have a fluid transition from. There's Indian CEOs all over Silicon Valley. There are plenty of allied countries that send talented individuals. You know, even going back through history, we've had Operation Paperclip. We've. We have, we have historically successfully integrated members from even rival nations. And that feels like something that would be a risk of losing if we go too far here. Is that, is that a real risk? Or how do you think about confronting that?
Yeah, I mean, I think, you know, a lot of people have sort of interpreted our article, you know, and have said, like, ban all Chinese nationals from attending elite universities or, you know, coming to school in the US and we are, we do not want that. I mean, you know, I've. I grew up going to a Chinese immersion school. I think it's a beautiful culture. The people are amazing, and they are huge assets to Silicon Valley and Stanford. We just want to see some change in the way that these students are able to live and study abroad. Because right now they. It's as if they have no rights because they can't. They have such a hard time coming forward. So we need to, you know, figure out a policy system that can give these students a greater awareness of the freedoms that they have. And we need to be able to defend them.
Right. A couple of solutions to keep Chinese students in the United States and improve security. I mean, we should remove WeChat from the United States. That's the main method of communication with the Communist Party. It's an unsecure platform that's monitored. Secondly, we should consider AI visas for bringing Chinese people's families out of China and to the United States because that removes a huge risk of transnational oppression. So not just getting the best Chinese researchers, but also getting their families in coming to the United States. And that's what we saw. The Soviet Union, I mean, with the Soviet Union, whole people's families came with them. And then the third thing that you have to think about is China requires a lot of these people to come back. The USA should be doing the same thing. If you want to come study and work on the most sensitive research technologies that are key to winning the AI race. You should be forced to stay in the United States for 10 years or more, because what we really don't want to happen is for these people to replicate these ecosystems in China.
Yeah, Jordy, what, you know, who. Who have you guys seen the most support from on campus? And you can keep it high level to protect the identities if people don't necessarily want to be public yet, but I imagine there's quite a few people on campus that have, you know, massive concerns around, you know, the national security issues that you guys are presenting and are, you know, hugely in favor of reform.
Yeah, I think we definitely, you know, the vast majority of the response has been off campus. I feel like there's been a surprisingly little amount of response on campus, but I think the best reactions have definitely been from the Hoover Institution. They have been looking into this kind of thing for a long time and are working on, you know, policies to. To deal with these things. But, you know, a lot of people that we interviewed still wanted to remain anonymous. So it's really tricky because if you want to work with China on some level, you can't be, you know, consistently speaking out against China. So I think that's sort of the difficult balance.
Is there an argument here for just kind of going completely open source with our research? I mean, famously, like, the Manhattan Project had a ton of spies on it. We still kind of won the Cold War. It feels like a sloppy and potentially crazy solution. But is there a world where the only thing that matters in a geopolitical technology race is just pace of play and the actual secrets don't matter that much?
Yeah, so you definitely want to play more offense than defense when you're talking about the technology race. We're not going to win this by stifling competition in America. We were going to win this through the way we've always won it by having an open, free market system that encourages competition. You don't want to ruin the risk of China using vast government intervention and vast government subsidies to essentially take the best research out of America and distribute it writ large at China by using vast state apparatus. We've seen this happen with electric vehicles. We've seen this happen with most American technologies. China misappropriates it. I mean, 33% of Chinese GDP is directed towards subsidies alone. The whole Chinese economy is geared towards leveling up and distributing advanced technologies. The issue with the United States, and it's a great thing, is that the government will not subsidize these technologies to the same extent and encourage their diffusion to the same extent. So the real issue is that China may get these technologies and then use these subsidies to create a mass market in China and gain an advantage. So to a certain extent there has to be sensible research policy that protects our core interests.
After seeing all this, do you think that American tech companies are generally too naive when it comes to espionage? I think the major players in national security, defense tech, things like that, have historically been very aware of the espionage risk. But do you believe that many sort of more American tech companies, specifically in the bay, should be paying a lot more attention to security?
100%. The foreign interference Task force was disbanded, the China Initiative was disbanded. Two key efforts to stop Chinese research and corporate espionage. We have very few lines of defenses right now. Companies need to be vigilant because we've seen this happen again and again. I would say that they know it's happening and they've known for a very long time. Even at Stanford, the people we talk to will all say, yeah, this is not new to me. Duh, we knew about this for so long. This is obvious. And they're surprised that we've even published this article. Some people, because it's so apparent. So what really needs to happen is we need the government to come through with sensible research policies that also encourage innovation. And Bay Area companies, particularly startups working in this area, need to be more vigilant about this.
That makes sense.
Great. Well, thank you guys for coming on and sharing. It's extremely insightful and bit, bit scary.
It's scary. I'm glad you're on the case. It seems like you're optimistic.
We need people like you guys to, you know, keep banging the drum and, and forever going to get changed. So yeah, come back on when you guys have more news.
Good luck with the follow up reporting.
Thank you so much.
We'll talk to you soon. Cheers, thanks so much. Bye. Next up we have Morgan Housel coming in a little bit.
Switching gears.
Well, I mean in geopolitic. Geopolitics are in his wheelhouse. He was falsely accused of claiming that the US would fall, remember?
Oh yeah.
So we gotta talk to him about that. Addresses allegations of being anti America.
So funny.
But we're excited to have Morgan on the show. He was great last time and I'm sure we'll have a fantastic.
I'm excited to ask him about his new book.
Oh yeah.
Art of Spending Money.
Art of Spending Money. Well, welcome to the show.
Morgan.
How you doing?
Hey guys, good to see you.
Great to have you on. Welcome back. It's been too long.
Yeah, I mean, I want to start with the, with the accusations that you claim that America was in decline. I saw a viral post. I didn't look at any of the replies, so I don't really know what, what was the story there?
It's, it's weird because everyone knows that things get exaggerated on the Internet, if not just made up on the Internet. When it happens to you, it's, it's pretty strange. So I went on the Diary of a CEO podcast. It aired I think a week or two ago and we talked about tariffs and I mentioned something about the, the fall in manufacturing jobs over the last 80 years, something to that extent. And I had so many different asterisks of like, oh well, part is technology, some of it is offshore etc, etc. And that got spun into Morgan Housel is predicting the collapse of America. And just one of those just like what, how does, how does that even happen? And so I called the guy out, he deleted the post. But it's, it's, it's amazing to see when it happens to you personally because then you start questioning every, like how many times have I read a headline that said so and so predicts the collapse of America? But, and, but they didn't or some, some, you know, some version of that. So I'm not predicting the collapse of America. I'm quite optimistic.
Such a challenge right now. There's so much long form content that's created and we're also in this era of like clipping. Right. The Internet likes long form content, but it really likes, you know, these short segments and sort of pulling out interesting moments. And we've had some issues with that already where you know, we, we had the seat, we had the CEO of Perplexity on and John asked him a hypothetical question about ads and TechCrunch ran with this article saying that, you know, Perplexity plan to, you know, just jam a bunch of ads in their browser or something like that. And anyways, context is, is very important. Were you at, were you at the Berkshire Annual Meeting?
Now this is the first, this is the first one in four years I didn't go to. Awesome. One to miss.
Right.
Yeah. Yeah. How was, how was, what made you decide not to go this year? Just, just family stuff. Busy.
I've got, I've got lots of other stuff going on. What's interesting is that I think I've been seven times and you. The last four times I went, I didn't even go inside to the meeting. It's turned out to just be a place where there's so many like minded people who go there. So several years ago, me and Brent, Be sure and Patrick o' Shaughnessy and Shane Parish all rented a house and hung out and it was an awesome weekend, even though we didn't even go to the meeting. So it's just been a place where there's so many collective people who have the same, same thoughts, same priorities to go and meet.
That's great. Well, I wanted to, I mean, I reached out to have you on earlier this week because obviously the news of, of Buffett, you know, stepping back at the end of the year to kind of get your reaction to it. It's one of those things, it's interesting dynamic where it feels like the most important sort of knowledge and wisdom in the world is sometimes becomes so widespread that people, sometimes people don't even pay enough attention to it. Even, even, even 0 to 1 is one of those things. It has like, it's one of the most popular business books in history, yet people kind of underestimate the value of it because it's just become the ideas and it have become shared so broadly. So I wanted to have you on specifically to talk about kind of the ideas that you've most gravitated to from Buffett yourself. Some of the ones I'm sure are very widely, you know, understood and talked about. And then I'm sure others that are a little bit more kind of under the radar. There's just so, there's so many good bits. So.
Yeah, I mean, the first is that to put his, his retirement into context, Buffett made his first investment before Pearl harbor and he started professionally managing money as a professional hedge fund manager when Harry Truman was president. So just to put like the, the context of how long he's been doing this is absurd. And then so there's two parts of that. One is like, yes, let the guy retire. He's 94. He's been going non stop since he was 11. Like, come on. And then the other side of that is that's why he's successful. Yes, his annual returns are good. They were very good back in the 50s, 60s and 70s. He hasn't really outperformed in any meaningful sense in a quarter century. Not a criticism because he has almost a trillion dollars in assets now. It's almost impossible, it's almost impossible to outperform when you're that big. But the point that is so easy to overlook is that, yes, he's been a Good investor. But he's been a good investor for 80 years, and that is literally 99 of why he's been successful. So I made this point in my book the Psychology of Money that if Buffett retired at age 60, you would have never heard of the guy. He never would have been a household name. He would have retired with like 100 million bucks. Awesome. He buys a yacht and a house in Miami and lives happily ever after, but no one would have ever heard of him. The whole reason he's successful is because he's been going for so long. And I forget who mentioned this, I forget where I read this, that Apple is Steve Jobs with a thousand lives. That's what Apple is like. Steve Jobs built the company and then. And then died. But Apple can live on because he built what it is. And I think that's what Berkshire's always been. And Buffett has talked about this, that he wanted to build a company that would way outlast him. And the irony is, like, he. He still last. He still ran the company for half a century or more. And so he lasted a long time. But it's going to keep going so far after he's gone, which is rare and unique. And I also think of all the lessons that people like us try to learn from him. The. The wrong lessons that you can learn from Buffett is like, is. Is how to pick stocks. I think that's probably the wrong lesson to learn because a lot of the. What he did in his heyday in the 60s and 70s just would not work today. It's a very different world, different markets, faster information. It's just not transferable. But the lesson of, like, he's successful because he stuck around for so long, even when he was so preposterously financially independent by, you know, hundreds of orders of magnitude, he kept going. And like, that's something that ordinary people can stick around. Like, stick around long enough that you're going to let compounding actually work in your favor. I think that's probably the most pertinent takeaway for people. There's also so many entrepreneurs, too, who, when they talk about, and I understand this, it's not a criticism because being a founder of a startup is so ridiculously hard and stressful. But for so many of them, the goal is, we're going to build this company, we're going to scale this company, and then we're going to sell it. And I get that. I don't look down upon that. But the huge, massive results are for people who are like, I'm going to do this and I'm going to do it as long as I as humanly possible that I can.
Yeah, I have a bunch of follow ups there. First up, Greg Abel. Is he underrated? It's interesting because he's coming in in his 60s. He looks like, you know, guy who could be retiring next year. But the culture of, of Buffett, you have to imagine that he's thinking, yeah, I got at least three more decades in here. I'm just getting started. So what's your take on Greg Abel? I don't know if you've actually dug into his career at all, but I'd love to know kind of how you think the culture that Buffett created kind of lives on.
Yeah, he's 60, so he can run the company for 30 years and then run for president after that. That's how this works. That's the standard path. I think most people outside of Berkshire don't know that much about Greg Abel. He hasn't, he's not like Buffett has very intentionally, I think, been on kind of a media tour for the last 25 years. Goes on CNBC all the time, of course, the annual meetings and the letters. Like, people know a lot about him. Greg Abel, people don't know that much about him other than that he's been at Berkshire for 25 years. And Buffett picked him as the obvious successor. What is known is that he's not a stock picker. And there's going to be people who, who get into a lot of trouble over the next five or ten years who are like looking for Greg Abel stock picks and they're, they're not going to find them anywhere. He's an operator. He's a damn good operator. And that's important because Berkshire 30 or 40 years ago, its market cap was like half stocks. Like, that's like its portfolio was just public stocks that own Coca Cola and Procter Gamble and stuff. Today it's like less than 20%. So the majority of Berkshire are wholly owned operating businesses. And that's Greg's bread and butter. It's just like operating those. I think it's, it's probably a very similar transition from Steve Jobs to Tim Cook. Steve Jobs was this like genius magician and Tim Cook was just a stone cold operator. And that's, I think that's what we're going through with Berkshire. You're going from like the, the wizard stock picker magician to the stone cold operator. And worked out great for Apple. It's just you have to keep your expectations in check, both because Berkshire size and because of what Greg Abel's strengths are. It's not going to be. And Berkshire hasn't been this in 20 or 30 years. The place that's going to have, like, massive outperformance year after year.
Yeah. I wonder about how much he needs to be a stock picker, because I totally understand the operator lens, but when you're looking at that $300 billion cash pile, it's like, what are you going to buy a big oil company or something like. Like you can do so much with that. So I'm sure that will be. Will be a challenge. I wanted to talk about the legacy of Warren Buffett a little bit more. There was a retrospective in the Wall Street Journal that I kind of took issue with, but I wanted to get your take. The author is talking about Buffett's remarkable recall. He estimates that Buffett read more than 100,000 financial statements. He famously reads books and seven newspapers and just reads constantly. And the right. And the author says his unparalleled exposure to financial information combined with his prodigious memory made Buffett into a human form of artificial intelligence. He could answer almost any query out of his own internal database. That has given him an unparalleled ability to identify the kernel of significance in any new bit of information and a durable advantage over other investors. Now, and this is the controversial part in my mind, says now that AI is universally available, a person with Buffett's massive command of data won't even have an advantage in the future. And I just don't know if that's true. But I want to know, do you think AI changes the landscape in a way that the Buffett strategy just doesn't work anymore?
I think part of the problem with Buffett in the last 20 or 30 years is that his folksy grandpa demeanor hid the fact that he is off the charts intelligent. And most of the time, when you think of like an Einstein kind of genius, like, they have a certain look and they talk a certain way. That. And Buffett was not. That's what made him so popular, is you felt you could relate to him. But anyone who spent a lot of time with him when he's not talking for the camera or writing in his folksy way will tell you he is. He is in a different universe of intelligence, particularly for money. And the reason he's successful is that since he's been 11 years old, he has spent 24 hours a day, seven days a week, thinking about stocks and nothing else. And so it's less about the data that he knows, even though people will tell you those stories that he can recall specific figures from a balance sheet, from an annual report he read 20 years ago. So there is like a. Just an insane memory recall, but it's the pattern matching recognition in there. And then this other element that is way more important, which is his reputation. That's something that AI can't do. And so a lot of Buffett's biggest investments, certainly the most important ones, came from the fact that he was. Had such a good reputation that he could walk into a boardroom and just say, hey, I'd like to buy 10% of your company. And they were like, yes, name us your terms. Like, we'd love to partner with Warren Buffett. And so that's less about intelligence or data and more about the reputation that he had. And I think if you. I think if Buffett were a jerk or a raider and had a reputation of stripping companies, he would not have been 5% as successful as he was. All the big deals came from people wanting to partner with him. Particularly think about 2008, the financial crisis. Every bank called him up and they were like, Warren, name your terms. Like, just, just tell your terms. And he did it. If Goldman Sachs and GE and bank of America, where he got these crazy deals that nobody else could have because of his reputation. And so I wasn't just that.
It wasn't just that he had the liquidity, you're saying, right?
It's just, yeah, there's. There's a lot of liquidity in the world. There's a lot of people who can write. Who can write a big check, not who can do it with that kind of, that kind of reputation. So I think there is a little bit of truth to that idea that the skill that he had of reading annual reports was so much more valuable in the 1970s than it is today, because everyone's reading the same reports. There's bots that can scan them just instantly. But there's like, that's not to say that anyone can be a Warren Buffett now. I think that's certainly a stretch.
What do you think of the. This narrative that the past decade of Berkshire is really just the story of Apple and their. And again, like kind of the stock pick there. It's such a huge scale. Do you think there's like a cultural shift towards technology?
Of course, when Apple was already the most.
It was the most valuable company in the world, and it still outperformed the market and drove fantastic returns. It seemed like A big shift at the time. At the same time, it panned out very well. Do you think that that represents, like, a significant change in the culture?
I think what's interesting is that for having a reputation for decades of, I don't do tech. I don't do tech. I'm a grandpa dinosaur. I don't do tech. Literally, in dollar terms, Warren Buffett is the most successful tech investor ever. He made. He made $100 billion profit on Apple. No one's even come close to that. And so is that like a change or an evolution? It is an evolution, but it's easy. It's easy to assume, and it's wrong to assume that Buffett's been the same investor for 80 years. I think part of why he's been so successful is that every five or 10 years, he completely updated his operating system to. To have a different style, a different influence, and to. To really adapt what was going on. And I think that there's only a handful of investors who are like that who have made money in different eras. There's a lot of investors who were very well suited for one era. They could make a lot of money for 10 years, but they couldn't keep it going because nine times out of 10, it's because they didn't update their. Their thinking. They were stuck on this world that didn't exist anymore. And so there's a very long history of Buffett doing that in every 10 years, doing things that he would not have 10 years before that.
Yeah. Are you familiar with that famous napkin diagram that Walt Disney drew showing how the parks relate to the film production, relates to the merchandise? Have you seen that chart before?
No, but it sounds awesome.
Okay, so Walt Disney drew this big chart mapping the entire ecosystem of Disney and how everything works together. And it's cited as this example of, like, oh, like, you know, build this business where everything feeds into the other piece and, you know, what is your Disney map? But I was digging into it, and I realized that Disney made that chart 10 years before he died. Like, he had already been building, just in film for a decade and then 20 years to build the parks. The Walt Disney Born in 1903, I believe. The park didn't open until 55, and he died, like, shortly after. And so it was more like a reflection on what he had built as opposed to. It was a map that was. That was drawn after he had explored the territory. And so I'm wondering your take on this idea that, like, the idea of focus and the idea of empire building being Something that can be charted beforehand versus has to be kind of naturally discovered and then can be potentially mapped after the fact.
I think there's several historical examples of business of like very successful business people who had, were product geniuses and terrible at business. Walt Disney was one of them. He was the product genius of, of, of all time. He was a terrible businessman. Henry Ford was another. Henry Ford is the most successful mechanical engineer in history. And he was at best a mediocre businessman. There's so many of those like that even I would even say Steve Jobs might fall into that category of technological genius, design genius. Very at, at best mediocre business person, which is why you needed a someone like Tim Cook. And I think there's, there's been quite a bit of that. But when the product is so good, you can take it in so many different directions. Disney is an interesting example of, of so many of the, of the, of the film IP that they had that was sitting on the shelf for decades. And when it was made it was like, oh, people will watch this in the movie theater. That was the only medium that they could watch it on. And then the video cassette tape came along and they're like, oh, we could sell all of this. And the DVD came along. They're like, oh, there's another avenue to sell it. And then streaming came along and it was like Sky's the limit. So it was like the, the IP was so good that you didn't need a genius businessman to, to, to come up with a distribution strategy. Like it was so good that it just kind of ran itself. Ford was, was similar like the Cars were so superior to anything else that even if Henry Ford was making blunder after blunder, the company kept going just fine. And so I think, I think a lot of times when you have like a very long running business, it's less because they made phenomenal business decisions and more just because the product that they made was so phenomenal that they could keep it going. If an idiot ran Apple, it would still sell a zillion iPhones every single year. But there's only a handful of companies that are like that.
I want to talk about the book out October 7th. Do you have a log line or like what is the one line pitch? Then how can you unpack the different.
Title is the title, is the title is the pitch.
But can you, can you break it down in a little bit more detail?
A little bit detail? The book is not called the Science of Spending Money because I don't think that exists. There's no way of saying, here's how you should do it. That's going to work for me and work for you, even if we're similar people. Just like, spending is very individualistic. So I called it the Art of Spending Money. Because art is different from person to person. It's. It's. It's subjective. It's often contradictory. And so rather than telling you what to do, I don't want to lecture anyone, but the book is a look at. At envy and social aspiration and keeping up with the Joneses and becoming fulfilled and getting attention and watching other people. It's kind of like the psychology of spending money, which I. Which has always been. Like so much of what I write is just trying to figure out my own life. So I looked at instances where I was clearly. It's hard to admit, but like, when I was clearly envious and when I was clearly trying to get people's attention. And just when you dig a couple layers below that, like, why? Like, whose attention am I trying to get? Is that person even paying attention to me? Do they even care? Was giving that attention, like, taking away from other parts of my life? There are so many different layers to dig through, and I think those things are universal. Even if what you're spending money on is not a science, the psychology of it tends to be pretty universal. So it's just a. Look at that. That was more than one sentence. I have to hone that a little bit sharper, but that's it.
That's great. I mean, is there a key anecdote or story or even just, like, case study that you think is the most tractable for people to grab onto? I think about, you know, all the emotion that goes into the identity tied to the car that you drive or the house that you buy. But what case studies are you pulling from to kind of ground the lessons in something that anyone can understand who's reading the book?
I don't know if this is the best case study, but it was one that I thought was so interesting. I read the biography of Harvey Firestone from Firestone Tire. He was the tire magnet, like, 120 years ago whenever he lived. And he has this part in his biography where he says every single successful person that he knows, including himself, when they became rich, they bought a giant mansion, and every single one of them, to a T, hated it. It was a pain in the ass to run. It was. It was. You know, when. When Your house is 17 bedrooms, it's just more roof to leak, more radiators to break and and he was like, everyone hates it, but all of them do it. Every single one of them does it. And even when they hate the house, they never sell it and get a small house. And he had this line that I loved, and he said, there is no going back, except as a broken man. It's like, once you inflate your lifestyle, you cannot deflate. Even if you hate the inflated lifestyle, you cannot go backwards because it becomes so synonymous with your identity. It's like the size of your house is who you are. I thought that was pretty interesting. And he was like the equivalent of a billionaire living in a mansion. It's not a very relatable example, but I think there's so much of that that if we spend money on something and it doesn't make us happy, it's very hard to rewind. So be, like, be really careful when you're inflating your lifestyle, because it's very easy to go forward. It's extremely hard to go back.
How much time have you spent or are you putting any attention in the book towards the way that San Francisco and the tech industry spend money? I've always been fascinated by it, given how much just this dichotomy between extreme wealth and this, in many ways, desire.
One glass box, please.
Yeah, yeah. This desire to, you know, be. And it's. It's good in many ways, right? If tech. If. Imagine that the negative attention that the technology industry would have gotten if every, you know, series C founder in San Francisco was like driving a Lamborghini. Right? It would. It would have been. It'd be fun, but it would have been.
Well, I think.
I think.
I think there's part of that that they can't spend a lot of money because it's not liquid. Like, they're rich on paper, but there's not a lot of liquid wealth in San Francisco. I mean, there is, but it's all. It's all relative. But. But even that is a sense of social signaling. Like, if people know that you're rich and you are going out of your way to live an austere lifestyle, that that might be because it'll make you happier. It might also be because that's the signal that you're trying to send. That's like, those are feathers.
Buffett's the best example of this. I mean, you have to spend some time on. On Buffett in the book of. Just intentionally.
Yeah. But then, like, I kind of twisted because Mark Zuckerberg was famously driving, like, a Corolla for a while, but then Sam Bankman fried at ftx kind of used as window dressing to be like, oh, I'm the altruistic billionaire. I only, I just drive a beater car. Right, of course he had like a mansion in the Bahamas and a bunch of other stuff that he like and wasn't pointing the camera at.
And, and Mark Zuckerberg's interesting because he famously drove the Acria for whatever for, for many years and now he just bought a half billion dollar yacht. So yeah, it all, it all comes around eventually.
Yeah. He's also evolved his taste in cars a lot where he could buy a supercar. But I believe the most recent car he bought was a Cadillac CTS V Blackwing, which is like a hundred thousand dollar sports car, but it's not a half a million dollar sports car, but it's an American, you know, muscle car. It's like very fun and very different. So he's, he's clearly finding his own path in expressing himself in a more unique way than just like one rich guy car, please. And so I, I, I think he's probably happier and like carved out a unique niche. And I feel like that that's often a better place to land, is not just, don't just buy the most expensive thing. It's okay to buy the expensive thing if it's craft and, and it's interesting to you and it has a story and it has relevancy or performance but it needs to like speak to you in some unique way that actually improves your life.
I don't know what's your most irrational purchase? I know you've talked in Psychology of money that you paid cash for your house or you don't have a mortgage, I believe. But what else is potentially irrational?
I don't know if this is irrational, but it's one I think about a lot. I grew up skiing as a competitive ski racer. And When I was 10, 12, 13 years old, I always felt like all my friends had better gear than I did. They had the nicer skis, the newer jacket and whatnot. And back then it bothered me. When I was 13 I was like, I was so envious of them. And so now, and obviously I got over that. But now that my son, he's nine now, we, we ski a lot together. And I think because of the scars that I had for my friends having nicer stuff, I made this vow a couple years ago. I was like, I'm going to buy my son the best gear every year. He's going to get the best skis, the best boots, the Best jacket. And I'm doing that to kind of, like, fill this hole that I had when I was. When I was a young kid. And the irony about it is he could care less. He does not care whatsoever what gear he has. And so that's interesting, too. Like, I think there's always a story behind spending. For me, it's like he doesn't care because he has.
No, he doesn't care because he's so. All he knows is the best. Right. Is that is.
But I feel like. I feel like I.
Like, if.
If I buy him a new pair of skis, I expect him to be like, oh, wow, let me look at these are so cool. Because that's what I would have done. And I get him, and he's like, this doesn't. Doesn't matter whatsoever.
No, I totally resonate with that, though. I remember growing up skiing, snowboarding. I would. I would always have a snowboard that was, like, three seasons old, lightly used, and it was like, the practical decision. It was $50. It got you down the mountain just pretty much as well as anything else. But then I'd be watching the Burton, you know, videos, and it's like, you know, looking at these, and I'd be just running the numbers. I'm like, I would have to ref 400 soccer games to get, you know, that board with those bindings. It's like, I'm gonna ref, like, 10 games this weekend, but I'm not gonna get there.
Yeah, I was skiing at some point. I got too tall for regular skis, and so they needed to. They were like, you have to go to custom skis if you want to be really in this. And I was like, I'm switching to scuba diving. Like, you know, whales are big enough for the ocean. I'll be big enough for the ocean. It's fine. I do have one last question. Do you have one?
I have one last. But there you go, switching. I hate to switch back, but on the art of spending money, what is the. What do the real Berkshire enthusiasts think that. Or what is Berkshire signaled around how they're going to spend $300 billion or whatever their. Their current cash pile is? Because I feel like the general market sentiment is that, you know, Berkshire is preparing for the next, you know, next time great companies go on sale due to some crisis. But I'm curious if you have any sort of insight there.
I think, you know, the list of companies that you could acquire for $100 billion is not a very long list, but there is a list. Like, it's it's not inconceivable that Berkshire can make $100 billion acquisition. I've often thought that Bloomberg, the media company like that would be a perfect Bloomberg fit. It's probably worth about $100 billion or that'd be perfect for Berkshire. And then Berkshire is so big, it's a trillion dollar market cap. They could probably repurchase $100 billion of stock. It might take three or four years, but they could do it. There's enough liquidity there so you could spend 200 billion. Like that's, that's pretty conceivable. The big question for me is once Buffett is gone and passed away and his, his stake in Berkshire is more dispersed then you could, there's room for an activist investor to come in. Right now you can't have an activist at Berkshire because Buffett owns too much. He would just tell him to go away and then it's over. Once Buffett's majority's voting stake or like big voting stake is gone, then it's interesting, will Bill Ackman or one of those guys come in and say, we want you to do a $200 billion special dividend. We want you to spin off this and that. And that's, I hope that doesn't happen. But you can very easily see it happen, particularly if people aren't going to give Greg, you know, a five year leash to prove his way. If the results aren't there in two or three years, you'll probably have people knock at the door.
Yeah.
And so having that pressure, I hope he doesn't have pressure to deploy that $300 billion of cash, knowing that if he doesn't, someone's going to come knock at the door and threaten his job or tell him to spend off this or that. So it'll be interesting.
You said he's not a stock picker either. So he's not exactly just going to go out and be like, okay, I'm going to start deploying this. And you know, that way. Right. It feels like it has to be more significant.
Yeah.
Yeah.
I have another question, but we'll have to do it next time. This is great, joining us, even us all hanging out. I know it's going to turn into a whole conversation and we can do a whole nother 30 minutes. So why don't we just do another 30 minutes in a couple of weeks.
Let's do it. I'll see you then.
Morgan, we love chatting with you.
Thanks for coming on. Thanks for coming on.
Have a great Friday.
We'll talk to you soon. Bye. Here's the run of today's show. We have Sonya from Sequoia coming in the studio next. Sequoia just hosted the AI Ascent conference with an absolutely stacked roster. Some of the greatest programmers, some of the greatest entrepreneurs in artificial intelligence, or really just in history, all coming together. We saw a fantastic jacket swap between Alfred Lin and Jensen Huang and I'm excited to talk to her about trends in artificial intelligence and what is happening in both the early stage and mid stage startup market. Obviously, as a venture capitalist, she is investing in a lot of interesting stuff today. So welcome to the stream. Sonia, so good to meet you.
Thanks for having me.
Thanks for having me.
You know, Alfred was bummed. His jacket was Hermes and he was sad to lose it. And I was like, don't worry. I think, I think you got the better trade here.
Oh, wait, so that was a permanent swap. He gets to take it home.
Permanent swap. It's hanging in the Sequoia.
Okay, that's fantastic. Yeah, it needs to be framed. I mean, it's I. Iconic. Iconic, yeah. I mean, I want to buy a leather jacket just so if I'm ever in the same room, I have something to swap.
We'll get you the deets, don't worry.
Fantastic. Yeah. Give me the rundown of AI Ascent. Is this something that happens every year? Was this year special? Obviously it's a bigger trend than ever. Who are some of the interesting speakers? Give us the overview.
Well, I'll give you the origin story. I'll take us back a bit. We invested in OpenAI back in 2021. So this was back when it was very much it was a few guys using the API. Definitely no ChatGPT yet, but we just felt like they had invented magic and we wanted to make sure that our portfolio companies would be kind of the first to be able to see that play with it and transform their own businesses. And so we set up a field trip actually for like 40 of our portfolio companies to go visit OpenAI back in May 2022. And so that was like pre ChatGPT moment. And everyone loved that field trip. It was like people were playing with Dall E for the very first time when there was no public access yet, starting to build with GPT3. And so our founders loved it, both for the inspiration element of, oh my gosh, we are in the belly of the beast of the thing that is building the magic, but also from a very tactical perspective. Here's how we should be using this stuff to transform our businesses and so founders loved it. They asked, can we bring this back next year? I honestly, I'm not like a party thrower. I hate throwing events. And so I was like, oh man, do we have to do it again? But everyone wanted to do it. So we did our first kind of non OpenAI specific event and more across the entire ecosystem the following year. That was like right after chatgpt moment. And so this is our third year throwing that event in a row. We've had amazing speakers. Sam Altman has spoken at every event. We've had Jensen twice. We've had even the audience is incredible. In our opening talk, we kind of called out what we viewed as the biggest AI product innovations of the year. And we had NotebookLM, Deep Research, Sesame. I think some of the biggest innovations, those people were all just happened to be sitting in the audience. So it's just a lot of firepower in one room.
That's great. That's amazing. What are the top discussions that people are debating right now from talking to people on the show? This idea of the pre training wall needing to move into more RL focused techniques to kind of get the next level of breakthroughs. Is that a. Is that the right question to even be asking? Were people debating it? And do you have a take on the idea of like this hitting a pre training wall?
Yeah, totally. So we had no one Brown speak at last year's end and we had Dan Roberts this year. They're both on OpenAI Strawberry Team. And we had actually gotten a preview of this from Noem, actually before he even joined OpenAI. And so he had done a lot of research historically in AI gameplay. And if you take the lesson from Go, for example, with AlphaGo, which I think was one of the seminal results in reinforcement learning, the top humans are like at 3500 ELO at go. The best bots are like 3000 before you give them access to inference time compute. But if you actually let the model actually sit and think for a minute before it places itself piece, you can get that Elo up to 5,500 points. So way better than superhuman. And so the key insight there is to get roughly the same order of performance once you've it's diminishing marginal returns on multiple vectors, right? But once you've kind of hit diminishing marginal returns on one vector of pre training, if you start scaling post training from there and sorry, specifically inference time compute, you can get like 100,000x scale up in performance there. So we're just starting to climb that second curve. I think OpenAI deserves a ton of props for seeing that and investing decisively behind it because I think if you talk to a lot of research in the ecosystem 1 a few years ago it wasn't even obvious that the lessons from AlphaGo could even apply to the LLM world. And so if you went to visit research labs a few years ago, it was like there's the RL group and there's the LLM group and they're not the same people and it's like it's very different. And I think Noam and various other people like really push forward that vision. And I think Sam invested heavily behind a reasoning infrastructure because the hard thing is like scaling up reasoning infrastructure is different from scaling up pre training infrastructure. And when I talk to my friends, a lot of them have joined certain labs like OpenAI XAI that have really invested ahead in reasoning infrastructure because it is such an important vector for scale.
Yeah, I was always wondering about the AlphaGo pre training kind of scaling law and wondering like, okay, we have all this major compute, what happens if we go back and train AlphaGo on 100,000 H1 hundreds, like are we going to get even better or really have we actually topped out? And it sounds like we basically did and we kind of learned that lesson. But is that a refutation of scale is all you need, kind of the bitter lesson? Or do you see it as just a continuation of that thing theme that we will need to continue scaling and it will just be new algorithmic paradigm on top of what we have and then scale that and then another one and then scale that and then another one and then scale that. Because it sounds like when I hear 100,000x improvement in test time compute or inference time compute, that sounds like a lot of data centers.
Yeah, it's a lot of data centers. I'm very much in AGI maxi like pro Bitterlesson and I think that this is just another vector that we're going to scale on. And it's not like pre training is dead right. It's like you kind of like from an Economics 101 perspective, you go to like where's the lowest marginal cost of the incremental unit of intelligence? And so right now a lot of that is on reasoning, but I think it's going to break to other vectors as well.
Are you seeing that in image and diffusion as well? It feels like the images in ChatGPT is doing something different. It feels like they're layering a few different techniques together. I was playing with the text and Trying to get like the text is so good now, but I was trying to get like a snake to weave in and out of the text and it was kind of getting confused and I was like, I feel like there's some layers going on here or something. I'm trying to like kind of understand it. And I'm just wondering like, you know, we might be past just like the big transformer paradigm of LLM and text responses in the reasoning era. Are we evolving past the big diffusion model in image generation as well?
So I'm not a researcher, but I get to talk to a lot of smart researcher friends. My understanding is that it's a combination of a transformer diffusion architecture and I think that most people don't believe that diffusion models will fully get us there. Whereas transformers have a lot more juice in them. And so even if you look at it's not just image, it's video, it's robotics. A lot of those have transformers as their backbone. But I do think there's so much that's happening in the harness around it. What's the for loop that you run the model in? What tools do you give it access to? We did a little pull at AI ascent of what innovation is going to drive the most amount of progress in the AI ecosystem in the next 12 months. And biggest answer was MCP and tool use and forming an ecosystem around that. So I think like the models themselves get smarter, but they're also surrounded by.
A big ecosystem on mcp. How are you viewing that as a position in the market? Is it just a standard? Is it just an API? Is it, is it a framework or will there be companies that build around it? Are there going to be open source frameworks that then we find a red hat Linux of MCP and it winds up being a big company even though it's mostly open source. How are you thinking about that from an investor's perspective?
Yeah, I very much see it as a protocol and like something for the industry to standardize on. And so I think there are, there are obviously some benefits that accrue to Anthropic from having steered that.
Yeah.
But I think it being an open standard is really important and you know, that's why a lot of the big other, a lot of the other big model labs are standardizing behind it as well. And so I think it's a net positive for the ecosystem. There's a bunch of startups spinning up trying to make money off of it in some way. I don't know if I'm really bullish on any of them really having a shot at it. I mean, I think there's certain people that have. If you have an infrastructure advantage for some reason, like cloudflare for example, is making a big play, then maybe I buy that. But if you're a small startup trying to spin up a MCP shop, I just don't really see the right to win.
Yeah, maybe the value accrues to McKinsey coming in and saying, hey, we're going to help you implement an MCP server for your existing Fortune 500 company or something.
Was there any interesting conversations around benchmarks and do you think they were talked about more or less than the last year?
I would say this is an audience that very much knows that the benchmarks exist and doesn't really care too much about them. We ran a poll of if you could only use one model for the rest of your life, what would it be? And OpenAI by far number one, more than 50% share. Even though, like, if you look at where they are in the model leaderboards, they're like, you know, they're not there on LM Arena. And so I think there's a little bit of a. The benchmarks aren't really, you know, they're saturated. They're not really the vibes test. I think people care a lot more about vibes test right now.
Well, yeah. And just end user value. Right.
Well, speaking of benchmark, do you have a take on the Manus investment that's kind of burning up the Internet right now?
Oh man.
Seems like an odd choice in 2025.
I'll give you a hot take, John. Apparently the U.S. treasury this is examining a benchmark capital's ties to mana, so feel free to pass on the question if you don't want to talk about it.
I will say they've built really cool tech. I think like the devil's in the details for like, what exactly, you know, you know, where's user data, et cetera. And I would imagine that they did their homework, but I don't know.
Switching gears, the big story this week around OpenAI, obviously after the event, was the new CEO specifically coming in to focus on applications. I'm curious if you could highlight any of the conversations around value accrual. Sam, I think has been pretty explicit in the past that if you're building products with the assumption that the models are going to continue rapidly get better, you're probably in a good spot. If you're not, maybe you're going to struggle or get made redundant at some point. But I'm curious what the general kind of vibe was around that.
Yeah, I would say the memetic cry in the venture ecosystem right now is just like the value is in the application layer. The value is in the application layer. I actually have a great meme on this. We had the meme on the values in the application layer and then we had Jensen in the audience and I just had a picture of Jensen on top of Scrooge McDuck just raking in all the dollars. But we very much think values in the application layer. And it depends how you want to play it. I think that there's going to be a place at least in the near term for vertical agents applied to a very specific sector and we have a bunch of those companies in our portfolio. Sierra Harvey, Open Evidence I think that what the foundation models have proven though, which was debatable a couple years ago, is that they have every right to win the application layer. And so like it wouldn't have been obvious that, you know, a company building foundation models could like figure out the application magic, but like ChatGPT is like a, to me it's like a runaway freight train in terms of consumer adoption. Some of the metrics, they've published like 300 to 500 million weekly actives year to date. It's just, it's phenomenal user growth. One of the things that Sam shared at our conference in terms of how people are using ChatGPT was really interesting to me. If you're old, you're using it as a Google replacement. So I'm old. If you're in your 20s or your 30s, people tend to be using it as more of a life advisor, life coach type thing. And then if you're really young, the Youths are using ChatGPT as an operating system. And I found that framework really interesting and especially in combination with they're clearly building things around memory, around tool use, around connecting to your other applications. It really does feel like if you're a young person and really, really connecting ChatGPT and mind melding with it, that use case seems really interesting to me. And so if you think about Google as front door to the Internet and $2 trillion market cap company, right. It feels to me that ChatGPT is in many consumers minds that front door to AI and as what AI can do, as the ceiling on that goes up, we just each deepen our product usage. A couple years ago at the first AI sent, I posted this chart of the ratio of daily to monthly active users for ChatGPT and some of the other mainstream mobile apps. And the punchline at the time was like usage is terrible. Like people are like, it was like a 14% down Mao if I remember. It was like people kick the tires a little bit and then churn. And we've been like tracking from externally from data science signals just like seeing those down MAO ratios increase. It's pretty crazy. Like download is now in line with Reddit. It's approaching Google levels. And so like if you think about Reddit being like a super engaged like you know, you're in there having like multiple conversations, you see that same behavior both anecdotally and in the data for ChatGPT. And so to your question, where will value accrue? We think it's in the app layer. I think a lot of the horizontal app layer opportunity will be won by foundation models like OpenAI, like XAI. And then a lot of the companies we're backing are going after a very specific vertical opportunity.
Are you particularly bullish on enterprise application as independent? I mean I'm thinking about like Google very much one consumer search. But you know, in legal there was LexisNexis and then Palantir helps, you know the government search through data sets and there's, there's all these different enterprise use cases that Google wasn't able to go after. We were even talking about Armada, which is an enterprise like you know, service on built on Starlink. The Starlink team has dominated in consumer but you know, the enterprise needs of certain enterprises is just too unique and so there's actually a business to build there and that's seems like it maps with your strategy most recently. But what do you think?
Totally, totally. I think the enterprise war feels like it is like we're in the first inning still. It's not clear who's going to win yet. I think in our portfolio Glean for example has done a really amazing job as a horizontal chatgpt like platform that kind of connects to all your enterprise data. But then it's like a question of how deep do you need to go. Harvey has a ton of legal case specific data or Sierra has a ton of customer support specific data and workflows. And so I think there's you know, the enterprise AI battlefield is very much a work in progress at this time. I think like the shape of workflows and problems is like so diverse in the enterprise that like my guess is a lot of these companies will be successful.
Yeah.
How are you thinking about humanoid robotics? I've talked to, there's a lot of high flying Companies that feel like it's mostly renders at this point. There are some really amazing researchers working on some stuff. I'm personally waiting not to see the demo of one humanoid walk around because we've seen those with Boston Dynamics for decades. I want to see the satellite photo of the data center that's getting built out to do a massive training run for an end to end robotics model. And I haven't seen that yet. Is that the right signal to be looking for, for takeoff in humanoid robotics? Or should there be something else that I'm tracking as we go into this, like humanoid rollout? Which it feels like it could be tomorrow or it could be two decades away.
It doesn't feel like tomorrow to me.
I was going to say the same thing.
Generous. There's a lot of CEOs out there.
Who share the details, but let's just say I've. I think the humanoids are a lot closer than we may think they are.
Okay.
And it's like, I thought this stuff was science fiction. And I've talked to a lot of smart people who have told me and shown me things that have made me realize like, wow, this is probably on the time. Like, I would guess in like two or three years this stuff will be in tens of thousands of households at least. Maybe.
Households.
Yeah.
Wow.
And that actually echoes kind of like the timelines from. I think Sam said on stage that, you know, we had Jim Phan from Nvidia on this on the show. He, like, he's like, you know, there's the, there's the digital Turing test of like, you don't know if it's a human behind the, the computer or not. Or not. Sorry, a computer or a human behind the screen when you're talking to it. It's like the physical Turing Test is when you leave your house and it's a mess in the morning and you come back and it's all perfect and all cleaned up. And he also thinks we're about to get there for him. A huge part of the breakthrough is going to be synthetic data pipelines and robotics. Unlike LLM, you just don't have Internet scale data to train on. But one of the amazing things about what's happening in AI right now is just with LLMs, but also more specifically with these generative world models, you can generate tens of thousands of variations of the same environment to simulate. And these robots can get better and break through that data barrier extremely quickly. And so I was personally a robot bear for the longest time and talked to a bunch of very smart people in robotics over the last week. And I flipped. I feel like the human identity are.
Coming and in terms of, in terms of capital intensiveness, of like actually getting there in a few years. Obviously it's very expensive to build a factory that produces robots. But do you think we're also going to see raises from humanoid robotics companies that are where, you know, a ton of the raise goes into Nvidia GPUs to build a huge data center to train some massive model? Because yeah, I agree with you on the synthetic data. You could wind up with web scale, you know, trillions of tokens like we've seen with the GPT4 training run.
I think it's going to be extremely capital intensive. And it reminds me of autonomous autonomous vehicles five plus years ago where like, you know, at the end of the day like we have, we have Waymos and we have Tesla's driving around those. Those companies had enormous economic engines to support the development. I think the same is happening with humanoid right now. And so my guess would be it's like it's going to, it's not just Nvidia GPUs, it's everything. Right, because you're co developing the hardware, you still have to collect a ton of data on actions and so it's a ton of spend everywhere.
Yeah, I mean huge trends in AI broadly. It feels like all the metrics are up and to the right at the same time. Valuations are very high. What's your overall take on the venture market? Are we in a bubble right now? Can there ever be too much venture capital? All the key questions.
Never, John, never.
There is, there is too much venture capital already. Look, I'll say a lot of companies are raising on like what I'd call vibe revenue right now. And like, it's like, it's like it's you know, pilots being counted as revenue. It's like really, really terrible retention stuff. And so like once you peel past that, I think there's like a cohort of companies that are like growing high quality revenue at the highest pace that we've ever seen. And that includes like I mentioned OpenAI before, but it's also companies like Glean and Harvey and Sierra and all these companies. And so to the extent like valuation is a function of like how much of you de risked, how much product market fit do you have? Like what is your, what is the growth rate of your, of your business and what is the ultimate TAM potential? I think these AI companies are demonstrating just, you know, growth rates outside of what we've ever seen before. And then TAM potential, like, because it is very much you're selling into, you know, if you're able to get outcomes based pricing, you're selling into a, into a services replacement, not a tools replacement. It's a, it's a TAM in the trillions.
Right, okay, but yeah, so sorry to interrupt you on that point. Something, something I'm curious about is, is so yes, if you have an AI tool that can replace services spend, you can capture some, you can whatever, ideally capture a lot of that, you know, market. But the thing I keep coming back to, and maybe this isn't the right way to think about it, but you're, you're not simply competing with end humans that are delivering that services. A company will also be competing with other AI tools that have, you know, a similar cost structure. So does that not over time just drive the sort of dollar amount that you can capture just down to something that looks more like a software market?
We have this debate all the time, so I'm glad you bring it up. I think it really depends if what you're doing is really low switching costs, really low differentiation above what the models provide. Yeah, I think that margin is going to get competed down. And so I think that's why we've historically debated a lot of these GPT wrapper companies. I think that if you're building something that's really hard to build or that's integrating into a customer base that wants to choose an AI champion and move on with life, which by the way, happens. We just did a bunch of references in the healthcare transcription market. You talk to these healthcare CIOs, they're like, I'm choosing one transcription vendor. I am not ripping that thing out for the rest of my life. And so I think there's nuances to the stickiness of these things. I work with a company called Gong and they do, they're a sales AI company and the theory was all like always like transcription. Love it.
We love gongs on the show.
You baited us.
It's a huge part of the brand.
Oh my gosh, that's amazing. And they have such a perky brand too. There's so many gongs around their office. But like the theory was always like, transcription should commoditize. And I think that very much hasn't happened. And like sales teams standardize on them, they standardize their processes on them, they train all their reps on it and like it has all your data. So like, I think the theory of how you build Build moats is, is different from like rubber meets the rubber meets the road in terms of like how these companies in practice do build the moats. But like I think you are in a run like hell business because there's so, you know, there's, you know we, we backed it, we backed an AI DevOps company like an AI troubleshooter. There's four other companies that are trying to do the same thing right now. And so like we are kind of in like a run like hell segments of the market right now.
How do you think about private equity stepping into the AI race? We've seen a few venture backed approaches where the idea is like instead of the Harvey approach, let's buy law firms. And we've seen even in the pre, about a decade ago Justin Kahn was working on Atrium, this kind of like tech powered law firm where it was a law firm but Harvey's made the choice not to. But what is your take on private equity? Dipping their toe into more venture scale opportunities and venture investors starting to look more at private equity style roll up deals.
Yeah, well, so I used to, I came from private equity so this is something I think about a lot. I think it makes a ton of sense and it's a continuation of the private equity play.
Right.
A lot of the investments I did in PE only worked because you took 20% of the cost out. And so like now you have a much better tool to go and do that. But like it very much is the playbook and it's what they're best in class at. And so do I expect that they'll be great at adding, you know, AI to the arsenal for how they get those margins up? Absolutely. I think that, you know, when I think of the businesses that I'm excited to invest in, it's like okay, at the end of the day it's who's, who's creating gross profit. It's gross profit dollar creation. And you can choose to do that by investing in the billion dollar revenue company and taking their cost down 10% or you can choose to do that by backing, you know, that amazing Dev Tools founder that knows how to build like the AI native dev tools company that's going to create $100 million of gross profit off the bat. And so I very much personally like to invest in the founders that are kind of creating net new revenue dollars and net new gross profit dollars. But multiple ways to play. I will say I had to really retrain my brain when I went from private equity to venture and just, I mean everything you like the way you operate is just so different. And so I do think it takes a different type of culture to operate a roll up or a cost out strategy versus invest in startups. And so while I agree, like I agree with the strategy of firms doing their thing and venture firms doing their thing, I have a question mark on, on the blurring of the, of the core competencies.
How do you think about the different businesses that Sequoia is running right now from early stage growth stage beyond, how do all these things play together in the strategy? We've seen some venture firms even dip their toe into general catalyst buying a hospital network. Some, lots of people are thinking outside the box these days. There's the crossover funds. What do you think Sequoia does best and what are you excited about in the future?
We're not buying any hospital trains yet. Okay. I would say like if you think of our strategy, it's like it's seeds, IPO and beyond for like the most ambitious entrepreneurs in the world. And so sometimes we're able to catch them early at the seed, like Airbnb, like Stripe, and sometimes we catch them later on in their journey. But like the point of adding additional kind of pools of capital to our fund strategy has been when we find a winner in our portfolio. For example, take like a SpaceX, we want to be able to invest a lot of money behind that company as it, as it goes on its journey. And the reason for the Sequoia Capital Fund is like even after these companies go public, we think a lot of that return is still to be had. And so we've, we've modified our structure over the years to be able to kind of support these companies as they, as they grow and become later stage and go public. But ultimately it's invest at the earliest point of conviction and ideally that's at the seed.
Makes sense.
Jordi, do you expect to see more? Sam had some interesting sort of quotes over the last week or so. I don't know exactly when they were happening. Talking about the cost. Sam Altman. Sam, which other Sam, isn't it? Which other. Sorry, sorry. To the other Sam.
Yeah, sorry. Sam lesson.
Yeah, no, the quote to summarize it was, or the line was something to the effect of the cost of AI or the cost of intelligence will just converge on the cost of energy or electricity. And I'm curious, you guys had Chase from Crusoe talk and I'm curious if you think that that is a potential area that you expect to see more net new early stage startups exploring because it probably hasn't got enough. You have nuclear and we're talking with.
This with Sean McGuire. We were saying like there is no elon of energy yet, but it feels like the last massive, massive market that no tech founder has really gone and dominated in kind of the founder mode way. We were talking about big oil. There's still a bunch of huge companies. Can't name any of the CEOs. They're not really in founder mode. They're kind of boring and maligned and it feels like there's an opportunity there. But yeah, so that's a lot.
No, I mean that's a great question. We, we had Chase from Crusoe on our, on our podcast and I, I will, I'll put in the bet that Chase might be that elon like figure. He shared some stats that were amazing to me and it's like I'd always kind of thought about AI from the oh, I can generate cool Ghibli images perspective but I didn't realize the extent of like the sheer extent of the industrial build out that is happening to support all of that. And so Chase shared, like, if you look at like typical data centers today, like 20, 40 megawatt data centers, like the biggest data centers of the world are in Northern Virginia or sorry in the US are in Northern Virginia. The aggregate capacity is four and a half gigawatts there. Chase at Crusoe himself has 20 gigawatts in pipeline right now, more than 2 gigawatts built out. And so like the sheer scale of the build out right now is just like nothing that we've supported in the past. And the bottlenecks are moving around. So like people, it's actually impossible to get chips now. A lot of that is easing and power is a new bottleneck. And so this is why there's so much happening in West Texas right now in Abilene where they just have this like massive overbuild of renewables, especially with wind. And so like I think very much you'll see a lot of the AI build outs following, following power and energy because that ultimately is the binding constraint right now.
That's a lot of sense.
We'll let you go. This is super insightful. This has been fantastic conversation.
Come back on.
Went all over the place. But we'd love to have you back.
This is amazing. Come to our party next year. And I heard you were asking Andrew about swag. We have these amazing scented candles. I actually have one on my desk. We have these scented candles. I'll send, I'LL send one your way.
Thank you.
It was evidence that I didn't know our audience at all, but I enjoyed the scented candles very much.
I love scented candles. Mother's Day is coming up, so, you.
Know, I know you're. Your segments on the Himalayan Birkin. I was like, I love these guys.
Yeah, they're going to be flying off the shelves.
Yeah, yeah.
After, after we do this show, everyone's going to go out and get one. Anyway, thank you so much for stopping.
Thanks for coming on.
We'll talk to you soon.
Have a great Friday.
Next up, we got Will from Slow Ventures, the other side of. Of Slow Ventures, Sam Lesson's business partner. Obviously, he's been on the show many times. We had to swap him out where we're replacing Sam with Will from Slow Ventures. Very excited to have him on the show. I've been digging into a bunch of those questions. I still want to know more about the robotics timeline. I'm going to try and dig into that. I still need to know how. I need to talk to more researchers about how images and ChatGPT works, because I feel like there's something going on there. You know, you see it with the, with the text models that there's very clearly, you know, certain filters running on top. You get these weird rejections with the images where sometimes it will like just the Studio Ghibli thing is bizarre because Studio Ghibli is real intellectual property. Studio Ghibli is a real company. And when you say that, it doesn't say, hey, this violates our. Our intellectual property rules. But if you ask it to generate a picture of Superman, it'll say, hey, that's copyrighted. And so I'm wondering if OpenAI did a deal with Studio Ghibli behind the scenes or something. Or maybe there's some definition of how the IP shakes out, but hopefully going to have a lot more AI researchers and investors on the show to kind of answer some of the bigger questions that I have. But in the meantime, we're continuing to yap about venture capital with a venture capitalist. Welcome to the stream, Will. Good to have you here.
Boom.
Are we live? Are we doing this?
Oh, we're live. Yeah. Hit the soundboard every five seconds for this one. We need to raise the energy in the studio. We gotta go. Venture capitalist yaps about venture capital. Every time we have someone on for Slow, we. We go crazy with the kyron. Expect some. Expect some wild, wild Chiron going on. It's Friday, but we're not letting the Energy go down. How's your Friday?
I'm all good, man. I'm about to amp up. I. I got this. I got a few more things to get out then. We got two Little League games this afternoon, so we're just starting.
We're just getting going here and we're.
Coming up on the playoffs, so it's a big Little League game.
Are you a screamer? Are you. Are you yelling the ref?
I'm a coach. Yeah, yeah, okay.
You are the ref. The other guys yell at you.
I'm a. I'm a Zen out coach.
Okay.
I'm a Zen out coach. That's my philosophy.
That's good.
Anyway, what's up, boy? It's great to see you.
Have you ever.
Have you ever been thrown out of a game?
No. No. I had a dad who was a screamer. I had a dad. No, no. I had a dad who I love dearly.
Rest in peace.
We were best friends, but he was, he was a yeller at the, at the refs. And so I kind of swore that off a long time ago.
Adapted, learned, improvised. Over.
Hey, when I coached, actually when I coached water polo, I did get thrown off. I got thrown out of a game when I was coaching high school varsity water polo because I was being too sarcastic. I wasn't, I was, I wasn't yelling, but I was too sarcastic. And the referee didn't appreciate that. Anyway, you guys look great. I almost thank you my suit out, but it wasn't for the next one, we hope. Didn't feel like my role.
Didn't feel like by the time we're done, all of Silicon Valley is going to be dressing in suits every single day.
And we're going to be. We're going to be switching to business casual.
Well, if you go to our website, you'll see Slow zig. When everyone was zagging.
That's great.
And decided to show our LPs when things are a little tight. That we are extremely. We're not just serious capitalists, we're extremely serious capitalists.
Buttoned up.
A suit is one thing, but a tuxedo really shows people that you're serious about managing money well.
Yeah, that's right. That's right. Well, I've wanted to have you on for a while. Always enjoyed our conversations. And I want to know what you.
Disagree with Sam on. He's got a lot of hot takes.
Probably.
Probably everything.
Probably everything.
Welcome to slo.
What about his idea of like, you know, he's pretty anti AI. He likes the AI cherry on top Businesses. Are there any of these pure AI plays? We were just talking to Sonia at Sequoia. She's had a lot of luck finding enterprise AI application layer companies that are pure AI, they are kind of rappers, but they find these particular enterprise niches that can go really big.
The honest answer is Sam Yoni, Kevin.
I have a really.
We really enjoy pushing each other and using Twitter as internal slack and highlighting where we disagree. But the reality is we're all pretty well aligned. We say it differently, we get there differently. But no, I'm just as anti AI as Sam and I think, listen, the important thing, we're not anti AI, you.
Know what I mean?
I think that's like the easy way to take it. Our answer is like AI is rad. AI will definitely. What do we do with swear words on the show? Aloud.
It's a family friendly show, we won't cuss. But we also don't have a bleeping mechanism so we can't bleep you out.
I coach little league, I can cut it both ways.
Okay, let's keep it clean.
Say swear like you're five years old.
Drat.
Like, listen, I think we all agree AI is going to break the economics of the world as they work in a massive way, right? So and the problem, Silicon Valley, like that's step one to a compelling venture capital thesis. And a lot of people just stop at that step. They're like, okay, cool, economics are going to break, let's start investing against it. And I think for us, once you click, okay, but where are those economics going to flow disproportionately, right. Against someone that has a really compelling business model, right. That that can get from here to there on very little equity. That's where our AI thesis breaks down. And I don't. It's hard to argue, you know what I mean, that a lot of the game, I mean, I think the hottest take that I do agree with of Sam's is this is not nearly as disruptive as people talk about and it's more of an enabler. And the winners are going to be big companies with balance sheets and distribution and data and all those things for a long while. So I'm totally on board with that. That doesn't mean we're not doing things with AI, but I think they meet the next couple click steps for us. Right? And a lot of those do look like AI cherry on top businesses with great founders who get, who get sectors and understand what's going on. Right? And then they leverage AI in addition to A bunch of other stuff.
At the early stage there's been this pattern I've been tracking with the new generation of like Gen Z founders essentially where they need to break into Silicon Valley. It's really noisy. There's a lot of, I mean honestly, the millennials are dominating like the latest hundred billion dollar company is Sam Altman and you know, a decade ago it was Mark Zuckerberg when he was in his 20s. We have a new big power law winner and it's, and it's as an.
Elder millennial that makes me extremely, extremely excited.
Yeah, yeah, yeah, yeah, yeah. But, but the Gen Z entrepreneurs have been, they haven't had this massive power law when yes, there's scale AI which is doing fantastically, but there that there aren't, there aren't as many like, like Gen Z hasn't really found their zuck yet and so they need to break through in a different way. And I've been seeing a number of, of young founders break through through viral stunts on Axe and in the media. And when we talk to them we often come away saying like, well like maybe we didn't love the fact that they have to play this game, but it just feels like a game that they have to play. And I'm wondering if you have a take on like the, the requirement of modernity that you have to be such a showman now to get attention for your startup, that you often have to push it really hard, make all these crazy claims and do all these stunts. There's a kid that we had on the shows hiring 50 interns to do social media for him and he's you know, getting kicked out of Columbia and it's allowed him to raise money and it's allowed him break into Silicon Valley. But there's always that risk that it's taking you away from just going heads down, building the product, doing like the Dylan Field thing at Figma where he was just grinding for years and then produced a great product. So are we in a new era or is this kind of just the natural evolution of breaking into Silicon Valley?
I think a lot of that is like compensating for not actually having extremely interesting novel hypotheses that screw with the economics of the world and a sick business model. So number one is like, I think it's copium for the most part. I have another take that I've been wrestling with which is like I don't think we have founders that are capitalist enough. I think like when you see wiz print that outcome and then you find out it's like Sequoia Doug Leone, a second time founder who was idea like you start going like, oh my God, those are people that, you know what I mean? They play, they play to win the scoreboard for them and everybody is in dollars. And so I think that's like another thing that comes to mind when you talk about founders struggling to do that is like, I, I've been kind of curious on like has there been an entire generation of founders on the back of hey, it's product, right. That like aren't as capitalist as necessary. And my, my take on that is like there's actually three markets you gotta back. People are like the big rad companies end up coming for. People that can do like are addicted to winning in three places. The market for customers, the market for talent, and the market for capital. And they have like a tremendous amount of interest and respect in all three games and they want to go maximize and manipulate all three of those. I'm not saying the illegals like, no, don't go that. But like they're looking at all three going constantly, how do I move chess pieces to like win this game more? And so I think a lot of the stunts are, are either from a product oriented mindset of like, I just need people to see my thing and try my thing, which I just think asymptotes out at a certain point. So I, I'm not sure. I mean, listen, I think if you're really good at it, it is a way to bend some of those markets, you know what I mean? But I think you need to understand, I would say, and again, that I don't want to talk about Sam last time our takes overlap. No, no, he had a good point.
About this, which is like you sell.
AGI to raise free money for a consumer application, you know what I mean? And you sell self driving in order to have enough equity to get the margin structure on your cars to a place that's sustainable. And like there is a role for that, but it can't be the whole thing.
Yeah.
And my interesting working strategy, I've been trying to figure out who patient zero was that like robbed founders of their like cutthroat capitalist nature. And my working theory that I'm curious, I want to get more feedback on, I think Google was patient zero because they built a product and a business model that itself was like the most beautifully efficient capitalist thing that was like constantly operating at the efficient frontier all the time where they could come off of like, hey, we're just vibes and product. You know what I mean? And that was like the exception that proves the rule, you know what I mean? Because it was such an amazing. I mean, I still, I live in awe of AdWords every day.
Yeah, Google is 100% right. Like they built a monopoly that just spit out cash and then they could just do whatever they wanted because like they didn't need to be ruthless at all in anything else because they built the perfect well.
And, and Morgan earlier was saying you could potentially say the same thing about Steve Jobs around, you know, the, the original, the product goat in some ways who wasn't.
Yeah, I mean, wasn't as.
He didn't have to be as obsessed about the business model of the.
Oh.
So I, so I, I totally disagree on that take actually. And I, and I think I. Sorry not to cut you.
No, no, no, no, go for it.
We love disagreement.
So.
No, so this, this, I, I didn't pick this up till recently or maybe I knew it and forgot it. But I mean, everybody knows they founded Apple. He got thrown out when it was time to run a serious business because he couldn't do that. Went away, wandered in the woods. For reals started next. And I didn't realize he plowed almost all of his Apple profits into Pixar. Did you guys read this article?
No. No. I mean, I'm loosely familiar with that story.
Okay, so not only did he do that, he ended up getting super deep in the weeds and like running the game theory on their IPO and strategic investment from, from Disney. And he basically like ran the most gnarly capitalist playbook there. Like he ran brinksmanship using the capital markets as a lever.
Yeah.
And that's when he went back into Apple and crushed it. So I actually think he like, is it this counterfactual? He's exactly the rule, which is you need to be on, you need to be on tilt in all three ways. Like, what are customers, how do customers value? How do you win them? How do you win talent and how do you win capital markets? And I, and I, when I read that story, I felt, I felt like my cooked up theory is actually correct. Which is like then he reenters, right? And Apple's up a hundred thousand x as he reentered.
Yeah, I mean, I agree with that and I have like kind of a similar take. Just the, the difference between Apple and Google is that Apple does operate a little bit in the world of atoms. They have to actually make a thing. And so there is some sort of ruthlessness that comes from like the Screws have to be screwed into the metal. And if you're not on time, you're not on budget, like, things can really go wrong. Whereas if you just have this beautiful algorithm and this website that people just have as their default homepage better and.
More profitable with exactly like it is.
It is a little bit easier to run Google than it is to run Apple. Like, Apple, like, you know, your supplier could kind of screw you. Like, what is going to happen in, in Google's world anyway? I don't know. I mean, it's a good take.
Sorry, you mentioned millennial founders and stunts and it got me on one of my nine talk tracks that I grabbed.
Yeah, but I mean, we were just talking about this, like there has been this trend and we were tracking it from. Yeah, it probably started at Google, but then Mark Zuckerberg drove like the Accord for a long time and then Sam Bankman fried, kind of took that, like, yes, I'm a billionaire, but I'm like the, I'm like the down to earth billionaire, the benevolent billionaire. And he was like driving a Toyota Corolla. And it kind of, you know, created this meme around, like, you can be really successful and wealthy, but like, you don't want to display it. And then the next generation kind of got caught up in this meme of like, it's all about the experience. I just want experiences. I don't want any material things. And it's a big question about if you can't concretize what you want in life from a material perspective. Like, you can't say, hey, I actually want a house for my kids to live in. I actually want that cool car that I've been obsessed with since I was a kid. Can you concretize building an empire, building a big company if you're not thinking concretely in materialist, in materials, like perspective.
Maybe I just think that other people want to. Want to win. You know what I mean? They're just like, I'm playing a game.
Yeah.
I mean, and he knows about. Zuck is like extremely competitive. Whatever he gets into, like, I'm going to learn Mandarin faster than anybody else. So I don't disagree that, like, I don't. I joke. Everyone talks about. Sam Altman is this like visionary product guy. He also drives a $3 million car he like, cares about. You know what I mean?
He cares.
He knows the scoreboard's got the money.
But it's a really good $20 million car, by the way. Oh, he does.
There you go.
Three million.
Koenigsegg that's the daily, I think. And then the F1 is in the.
Okay, well, so on the young founders note, something that I think is happening is that so much venture capital appeared and became available to very young people that weren't necessarily exceptional in San Francisco.
Yeah. Let's blame this on Will.
Right? People. People that are. No, so, so, so founders that are. That are talented, but not. Not the sort of necessarily top of their class. And if you give a young founder $5 million and you tell them to run their first business, they're going to act like somebody who won the lottery effectively. They're going to spend money in a way that is.
Just give me a YC take. I thought.
Yeah, and I saw there was a. No, so there was a founder who recently raised around. We've. We've had him on the show. I think he's super talented. And he was like, you know, hiring 50 interns at once. And then he put out a post. He's. He's going to hire a videographer this summer for like half a million dollars a year.
And.
And I was like, that's the one thing that YC gets right? Because they basically say, spend no money until your thing is really working and then you can start pouring, you know, fuel on the fire. But until your thing is working, spend 20 grand a month. Right.
Proven time is really, really hard to buy product market fit. Like you can buy growth post product market fit, but it's very attention or we heard if you could buy product market fit, big companies would be doing it all day long for new products. Anyway, I heard about another.
I heard about another company that had that. That's planning to spend 20% of basically two rounds that they've put together on a single launch day effectively. Right. And this is for a product that doesn't have any users right now.
Yeah.
And so it's like stuff like that where it's like you're giving talented young people an obscene amount of cash. And it's the same thing that would happen to, you know, somebody that's scratching something off in, you know, you know, at a gas station and they get $5 million and they blow it in a year kind of.
But it's almost worse than that, which is like, hey, here's a bunch of money that was like, pretty easy to come by. And we don't actually want to hold you accountable to the money coming back because it's product. And it's almost. We fell down this trap and I'll get on my rant about value proposition. But we fell in this trap of like backing people to do subjectively valuable things. And that's like a really hard capitalist endeavor to scale, which is like, we talk a lot about value proposition existing on a two by two of quantitative and qualitative, causal and correlating. And you could build great businesses in all quadrants, but what you do to scale them out of the gate is totally different. And I think we got down this like, hey, what's the value of that product? It's like, I don't know, it's like, it's different to me than it is. It's like handbags are clearly valuable, but like, why are they worth $10,000 for some people? Like you can't. There's no math, science, logic or anything behind that. It just is. And so I think Jordan is actually another thing where like, here's a bunch of money and go do things that like do not have. We talk a lot about our job and our money is to figure out does something work right, like with a true or false answer. And the problem is a lot of things got started that like don't have that true or false answer, right? So it becomes about derivative signals that actually aren't like connected to building killer businesses. So I guess. And your comment?
Yeah, Sam's been really big on AI as a sustaining innovation in the mag 7 in the big tech world. At the same time it feels like the big tech, like the stocks are performing very well, the financials are fantastic, but the products seem to be faltering. You can't find the right Gemini app for Google very easily. Apple Intelligence. No one's really raving about it, at least in the tech community. What is your take on big tech? Is it a better time than ever to start a company that takes a shot at a product that normally would be, you know, owned by big tech?
I still think that if I were running Google, well, I don't think 90% of the use cases in AI are actually like interestingly monetizable. I, I don't know that. I don't know that it like and I'm starting to watch my own usage now and question that a little bit. But like the majority of the con, the, the, the content being generated from AI and the majority of my usage is like not AdWords. So I, I don't know that I'm like that stressed if I'm Google, you.
Know what I mean?
Like what am I? I'm like going into chat gay and talking to them about what I'm going to talk to you guys. I didn't do that. But like that use case is like really great, really valuable to me. What's actually been back to subjective value prop. Like what's the value of that? Very hard to put a number on and very hard to monetize. So I, I was on, I tweeted it a while ago but like someone did. I forget who did. Someone did a really good take on this which is AI is going to be awesome to change the world. And AdWords is mostly safe from that. So I, and I, I just, I don't like, I don't love the hey, I want to take on the product because they're not good. You know what I mean? I think problem statements when it comes to building companies are not nearly as powerful. They don't lead to important companies nearly as much as like, I just believe the world works in this way. Nobody else thinks it works. And if I don't work on that, somebody else and I'm not even big on like will the future. It's like, no, no, go work on things you think are like just truths. You know what I mean? Because you'll be pissed if somebody else works. So I don't have a good answer for you on like you take on Google right now because I think the answer has to be you have to like come out and think the world works dramatically different in 15 years and start building against that.
Can you give us an update on. On your guys's franchising thesis? These sort of for. I feel like the venture world got excited about four wall businesses because there's. There had been a bunch of M and A over the last few years and people realizing like, hey, you can kind of spin up a brand and you know, prove it out a little bit and get a bunch of other people to, you know, scale it. And I feel like this idea of, you know, this business in a box has been very prevalent for the last few years. You guys have had your own thesis around it. But I'd be curious to get an update there on where you see that kind of category and how you see that opportunity today.
Yeah, I mean top of Funnel's been lighter than we wanted. I think the overlap with people who think this way and like think of slow is not. So that's, that's something we're constantly working on is like seeing more in that space. Listen, the way we got to that space is like, what are the raddest businesses out there? You know what I mean? Just from a year in, year out efficiency. Efficiency on equity. Just like, what are the things you would want to own for 30 years and hand off to your family? Which I think is like a really great framework on this stuff.
Yeah.
And you kind of quickly get to franchises, you know what I mean? Like, they kick off a ton of free cash flow, pretty durable for the most part, really efficient scale. So, like, that was just always. My interesting take is somehow venture capitalists became software investors and not. And not folks looking for novel hypotheses that have killer business models attached to them. And so anyway, that's how we ended up there. How's it going? It's like, really fun. I think it's a very logical output for a lot of innovation. I don't think we're doing nearly as much as we would like there, but we continue to look every single day. And again, for us, it exists on a. It's like one expression of you created some novel IP that has rad economics. You know what I mean? That does something that creates a ton of value in the world. And so we talk a lot internally. We're spending a lot of time on our GBO thesis, our growth by buyout thesis that we rolled out probably, maybe first. I think we did, but with some friends in our. In a company called Metropolis. And it's like, I'm not wedded to that. I just thought that.
That.
You know what I mean? I looked at vertical SaaS and I was like, oh, my God. It actually came to me. If it's interesting. An industrial rail. I got pitched by these guys with a sweet industrial rail logistics company. And I was like, I love this. I want to be involved. Right. And then I started digging in and realizing there were some tough go to market dynamics where you might actually double the earning power of an entire industry, but be an 8 million ARR company.
Wow.
I mean, directionally correct. I'm making that up. But I was like, that's wild. You know what I mean?
And I was like, how did.
Like, how does.
How did we get to this place that you could actually do something wildly disruptive and everyone else but you gets paid for it? And that's where I started peeling away the layers of like, what? Right? So like, it's like, oh, what if you bought a railroad and you doubled its profitability? You'd make more money than an 8 million ARR. SaaS company.
Right.
And then you go, buffett.
Yeah, Right. Then you go to one of the other versions of that. It's like, oh, maybe some. Some places it's more Efficient to vertically integrate maybe some places business in a box. And then a woman who works for me is much smarter than I am. When I was spouting all this off quickly was like what about Toast? And I was like yeah, Toast should definitely be a software company. So that kind of informed our framework that franchises slot into.
How do you think about buyouts? I mean there's venture capitalists that are getting in and on the equity side there's some funds, private equity funds that do equity investments and they have bank partners that do the debt piece. I imagine that you don't have a credit fund separately that's managing that. But yeah, is that coming? Okay. And then, and then there's also like the private credit guys that come in with just the credit piece. How do you think that that's going to evolve? And is it important for VCs to kind of have at least partners in the whole capital stack?
You'll have the partner. I mean like so again Metropolis is our kind of lighthouse case study in this. If you look at I think the where there's a hole is kind of the growth equity portion of this, right? So we'll fund someone to go do some breakthrough product work and go oh my God, the economics are changed. And we'll fund them to do a small scale buy of a business and EBITDA and see if you can like there's basically two experiments. Does the product actually transform economics and does it translate when you own and operate the P and L then there is a hole on the equity side for like great, let's go buy 10 of EBITDA. Not one. But if you look at who's the Metropolis deal, it's Wall street, you know what I mean? So I think I don't have evidence this all slots right into their models and Vista's credit fund comes in and da da da da.
I'm curious. We had Harley on from Shopify yesterday and it feels, you know, in many ways it's the most significant SMB platform in the world. It's a product that at scale entrepreneurs it's so critical to the business that yes they're going to have issues with it but generally people feel great about Shopify and I've been interested to think about in a lot of other categories you have these sort of like JIRO dreams of sushi type opportunities where linear was able to look at Everybody hates jira but like we need tools like that. And so what if you just built an amazing issue tracker from the ground up and really cared about the craft and if you look at Shopify, you could look at, oh, this design thing's not great, or what if this was better? Or what if we made this more intuitive? But I don't believe that you could take the most talented people in the world right now and try to get them to rebuild a commerce platform like Shopify. And just given the developer ecosystem and now shop pay and all these other things, I don't think I'm struggling to see how somebody replaces Shopify in the market right now. And I'm curious how, you know, if you guys have looked at any other, any other players that is, anybody even daring enough to try to, to take on Shopify.
I'm with you.
I think it's a fool's errand. So back to like, value prop, which my whole North Star is like, I need to buy someone that's creating a ton of value and can capture a lot of it.
Pretty efficient.
That's the end of the day, what we're trying to find in the world. But value prop has to sit on two axises. And again, this is like, everyone calls me Professor Will and you're hearing why I go on some long tangent that's like all theoretical.
Love it.
But you got to have an absolute value prop, but also a relative one. Right? Like, if you go out great, you create a dollar for people that are stoked. If the other solution creates like 98 cents a value. Right. And it solves the same, you guys are going to be in a dog fight from a sales and marketing standpoint.
Right.
You're gonna. You're like, you, yes, you create value, but you're communicating that to the market is going to be super hard. And so I think the issue with taking on someone like Spotify Shopify is the value. Like, it's hard to create relatively more value. Can you do things nicer on the edges? Yeah, but like the core functionality of like, I have a business that generates profit for my family.
Yeah.
You know, it's like, that's a lot of it. It's very hard. The switching costs are super high. There's a ton of risk, and it's hard to do that dramatically better and be like, hey, just by using our platform, you know what I mean? You will get. Make dramatically more money.
And Shopify can say, to be clear, they can say, look, if you have shop pay, you're gonna get an incremental. You're gonna get an incremental 10% of revenue just by default because the check, you're gonna have less abandoned carts.
We Lose you. Well he's frozen. Let's kick it over. He's absolutely some ads go to getbezel.com your bezel concierge is available now to source you any watch on the planet. Seriously, any watch. Let's bring in some more soundboard and we can also sing the wander song. Find your happy place. Find your happy place. Book a wander with inspiring views. Hotel graded many dreamy beds, top tier cleaning and 247 concierge service. It's a vacation home but better folks.
Can you imagine if. If Slow is just so committed to just being lean like their companies that they didn't pay for zoom the Internet bill or something.
No, no isp. Anyway, we. We have three founders coming on back to back to back. Tell Will he's happy to jump back on. We can close out but we don't have anyone in the studio right now. But we are going to talk about Nourish Matic and Fastino. Three wildly different companies. One in the healthcare space, one in the. We actually have the robot in the box over there. We should unbox it on the show with him. It's kind of a next generation Roomba talking about cleaning in your house and very excited to talk to him about that. And then Faustino is training AI models on commodity graphics cards. So I'm sure there'll be a bunch of interesting things that we can dive into. On how deep Seek was able to train on low grade unoptimized cards. If they can do it on gaming quality cards, I'm sure you know, other people can do it on all sorts of different cards. Should we do some timeline in the meantime?
Let's do it.
Let's talk.
I message Will. I'm actually concerned hopefully like you know.
Oh, we have someone. Okay, great. Yeah, let's bring them in. We have Aiden. Welcome to the stream.
How you doing?
Welcome.
What's up guys? Thanks for having me. Congrats on all the success you're having with the show.
You guys are blowing up.
Yeah, I mean success, you know, technical difficulties. It's one thing after the other today on the stream, but we're doing well. Our last. Great to have you. Boston, two seconds. But it was a great conversation and excited to have you here. Would you mind kicking us off with a little bit of an introduction on yourself, the company and the news from this week?
Sure.
Yeah.
So I'm Aiden Dewar. I'm the co founder and CEO of a company called Nourish. Nourish connects chronic condition patients of all different types with a registered Dietitian over telehealth, and we get it covered through their health insurance. We have the largest network of dietitians in the country. We have over 3,000 dietitians on the platform. We served hundreds of thousands of patients and the vast majority of patients pay nothing at all through their. Through their health insurance. We're a network with most major commercial insurance payers, Medicare, you know, some Medicaid plans at this point. And, you know, I've made a lot of exciting progress that we can speak about today.
And then.
Yeah, in terms of the news you mentioned, we announced a Series B round recently. It's a $70 million round.
70. Let's go. Fantastic.
Yeah.
Ring the bell, ring the bell.
Congratulations.
Thanks. Yeah. So it was led by JP Morgan's Growth Equity Fund and then participants from all of our existing investors. So Index Ventures, who had led the Series A and Thrive, who had led the seed round, and then Box Group, who I know our mutual friend David Tisch, who's invested at the seed round, has doubled down at every round, including this one.
Yeah, we got mutual friends all over the place. James Pierpont Morgan doing him proud. JP Morgan in the deal. Is this, like, why was this not covered by insurance before? Is this a regulatory change? Is this technology? What's driving the growth in the business? Are you just the first to think of it, or is there something unique that's allowed you to start covering this type of treatment with insurance? Because that seems like a major, major unlock, right?
Yeah, yeah, good question. So this actually first started getting covered in the early 2000s by Medicare. I think it was 2005. Medicare had done a study and seen ROI for this sort of care. And really the insight that Medicare put together, which is kind of the same one we put together, is that you look at the healthcare crisis and trillions of dollars to spend and hundreds of millions of people with chronic conditions and millions of deaths each year actually kind of, you start double clicking. Most of those are downstream of nutrition, and the vast majority of spend is just downstream. A handful of conditions, obesity and heart disease and high blood pressure and cholesterol and kidney disease and a few others. And so they had seen ROI for working with a dietitian. It's a really effective intervention, and started covering it. And then the Affordable Care Act, 2009 carved it out as a preventative benefit. And so that's this coverage. And then kind of the commercial payers followed and more Medicaid plans. And then the more recent unlock, which is right around when we started the business. The business, a little over three years old, was telehealth coverage at parity with in person because of COVID And so that was kind of maybe the biggest recent regulatory unlock that made this a lot more accessible. Of course you could have built this business in person, but would have been much harder than the way it's built today via telehealth.
Yeah.
On the subject of the raise, how is it different raising from major financial institutions institution versus a typical Valley vc? I imagine it's both similar and different at the same time.
Yeah. So I think actually in terms of the actual firm, the person we're working there, Paris Heyman, who we're excited to partner with, he actually was previously at Index Ventures and been part of the team that run our Series A. So actually wasn't so different in practice in terms of just we'd already known him and. And I think the processes are similar. I think the biggest difference really was obviously at each incremental stage there's different expectations. So Series B very different in terms of maybe more focused on the actual metrics and getting really deep on the data than Series A or seed. And so that's definitely an adjustment. But we're fortunate that the basics of the process and the buy in on the mission and vision and stuff like that was pretty similar to last round, given we already knew.
Paris, that makes sense.
What is the tech stack like for one of these companies? Is there like a plaid of insurance that you can kind of build on top of like, or are you writing integrations and is there a piece of like, you know, service as a software where there's a lot of humans in the loop in the short term and then in the long term it'll be AI driven. Like what does the actual buildup of the company look like?
So there is not a ton of what you said in terms of the insurance contracting piece. That's something we've. And kind of a big unlock in the value we provide for dietitians is actually going directly to these insurance companies and negotiating these contracts. I think that's one of the reasons most dietitians didn't accept insurance. Historically, it's a pain to go directly to one of these really large enterprises and negotiate a contract and then even if you get the contract deal with the ongoing administrative burden, licensing, credentialing, billing and whatnot. And so for the most part we've built all that, whether it's from a tech perspective or just from a operational competency perspective. In house, we have leveraged a great vendor called candidhealth for billing. And it's kind of API forward billing platform that we've built on top of. And so that's been a big unlock on the billing side. But I would say most of the other stuff from a contracting and credentialing and licensing perspective has been a lot of manual work and kind of competency that we've built up in house.
Yeah. Can you talk about trends in the evolution of dietitians and how they work? We were talking about how there was some research that showed that artificial intelligence was particularly good at therapy. And you could imagine the future is, you know, you just have an LLM giving you diet advice.
John, of course they're on, they're on TikTok. They're like, okay, all my clients are keto now. The next week they're on TikTok again. They're like, okay, we're going paleo.
Going carnivore now. How's it evolving?
No, yeah. I mean, you're hitting an important question, which is like, you know, we've seen AIV a big unlock for the business, and I think, you know, you're kind of asking more about, you know, the patient side, which what we've started to build in, into the app is, you know, essentially a lot of tools for the, for the provider to use or the patient to use without the provider in the loop to get a lot of the, you know, info you're, you're, you're talking about. And the way I think about it is like, about 80% of the equation is actually behavior change, but about 20% and accountability. And that's where the human is especially good. But 20% is a little bit more educational. Blocking and tackling, and Google is not especially good at that, but the LLMs are. And so that's a lot of where we're leaning in is how do you give the dietitian tools with AI to really provide amazing care on the things that only they can do and then leverage AI for the rest of the, you know, if you're, you know, if you've gotten to the point where maybe you're obese and have multiple chronic conditions, it's, it's not that you're just kind of, you know, a couple educational tips away from, from having success. You know, you've typically built up these habits over years, if not decades. And so while the LM can, you know, provide some help in terms of educating you on, on what's good for your diet and personalizing it and, and whatnot, the dietitian is really important for having the human in the loop and really the accountability to that behavior change. And so, you know, as the LLMs keep getting better, like, we, you know, we want to really lean in there. You know, we think we're, you know, really well positioned to leverage AI in this way, given, you know, we've seen hundreds of thousands of patients and have a lot of data on what works in terms of driving outcomes and, and habit change and behavior change. And so we think kind of the, you know, the synergy is having, you know, both the dietitian and the, and the AI in the loop kind of drives better care ultimately.
Very cool.
How. What have you seen around the adoption of GLP1s? The concern that I've always had with them is that people that should just focus on their diet end up taking a magic shot that makes them lose weight. And that's good because for a lot of reasons. But I have to imagine a lot of the end patients that you guys work with are both using GLP1s and thinking about the diet very intensely. But what's your reaction been? And I'm sure that's a question you got a lot even during the fundraise, I imagine.
Yeah, yeah, for sure. And it has been really interesting to see the evolution of that over the past few years. And our dietitians had a lot of Expertise working with GLP1s even before the recent explosion. I think, as you all know, they were originally approved for diabetes. And so dietitians have been working with diabetic patients on them for a long period of time. But of course, the, the recent explosion that everyone has seen for weight loss has also affected us. And what we've seen is that they are really important innovation, are really valuable for a lot of patients, and a really useful tool in the toolkit. And we've definitely seen it skyrocket in terms of our patient population and people using that, but they aren't a panacea. So there's a lot of side effects. A lot of people fall off the medication because of the side effects or either just like, you know, the logistics of adherence of getting access to the medication and injecting yourself every week. And so what we've really done is kind of pair ourselves as a complement to the drug. You know, these drugs are FDA approved to be paired with diet and lifestyle change. And so they. We see ourselves as that part of the equation. And, you know, there are a few different ways we've kind of built out our care model across kind of the journey of a GLP1, which is first, you know, we have a care program that's before you even get on a medication. So a lot of folks want to, before they try a medication, see if lifestyle change will work for them. And so we'll kind of have a step therapy type product where you try it before you get on the medication. And then if you do choose to get on the medication, we have, of course, a companion program that will maximize the efficacy of the drug by mitigating side effects. And we've seen a lot of cool outcomes with people losing about 33% more weight with the dietitian plus the GLP1 than they do just with the GLP1 alone. And then the final piece of equation, which is maybe the most important, which is actually getting off the drug. Yeah, a big problem with the medications, which are, you know, our payers see, but also our patients, is that when you get off, you often see rebound weight gain. And then, you know, for, of course, for the patient, that's really frustrating and difficult, but also for the system and for the insurance payers, from an ROI perspective. Now you've spent all these dollars to have someone lose weight and then regain it, which of course is, you know, worse. And so we have, you know, a program built around getting off the medication, making sure that's, that's sustainable for the long run. And so, yeah, we've seen it be, you know, a really big tailwind for the business because it's top of mind for payers in terms of managing this cost and lifestyle change is a part of it. And then, of course, patients are really motivated to change their behavior once they're on one of these medications.
What's the use of the funding? $70 million, a lot of cash. Is that R and D spend? Are there growth channels that you're investing in? How are you thinking about growing the team and the company over the next couple of years with that new Series B? Yeah.
So I mean, the way we've always kind of thought about our success is scale and outcomes. So it's, you know, how many people can we help and how much do we help them? You know, the quality of the care and so want to use the capital on both. So, you know, scale maybe most obviously, we want to really invest in expanding our network of dietitians. So as I mentioned, have 3,000 today, you know, the largest in the country. But I've had a long wait list for a long period of time. Dietitians who want to join, who haven't been able to, and so really want to expand our network of dietitians quickly to be able to support more patients. Of course, on the patient side of the equation, we'll, we'll invest in, go to market to get in front of more patients to raise awareness that this is something that's effective and covered by their insurance. And then on the payer piece of the equation, want to keep investing in partnerships with insurance companies. As I mentioned, we have pretty good national coverage, a couple hundred million lives covered at this point, but there's a lot more plans we can get a network with to expand coverage and want to continue doing so. And then maybe last but certainly not least, maybe the part that I'm most excited about is really accelerating development and product development effectively. I think we talked about some of the AI use cases we've seen for patients and dietitians and I think basically everything we've built there has been successful for those parties and driving outcomes and saving dietitians time. And patients really love it. And so we're really eager to continue investing in a lot of that product development and long term. I think the reason we got into this, I had my own chronic condition, I had really bad migraines and I'd worked with a dietitian to solve it. And of course dietitians were really valuable for me and that was part of the reason. And my co founders, and that's part of the reason why I wanted to expand access to it. But we know that part of healthy lifestyle change is not just nutrition, but things like mental health and sleep and fitness. And I think there's a lot of interesting applications we can do of that in our product to drive better outcomes and so really want to run at that pretty quickly.
What else are you seeing in the overall health tech market that's interesting or complementary? We talked a little bit about GLP1s. There's a lot of online pharma companies that are working in that market. But where else are you seeing exciting companies or trends that could be complementary to what you do?
Yeah, I think they're kind of on the, on the vectors that I just mentioned. So of course there's been a lot of movement in the, in the GLP1 space and we've partnered with, with players there to help get access to these medications to our, to our patients. You know, a lot of our patients work with a, you know, a therapist in tandem. And so, you know, there's, you know, great companies in the mental health world that we've, we've referred to. I think labs are really Interesting. You know, about 85% of our patients get, you know, labs done each year. It's, of course, a natural part of the care journey of both getting a baseline of, you know, discovering, you know, where you're at in your health journey and where you need to improve, but also as you're making progress over time.
It feels like the lab was just destroyed by the Theranos story and no venture capitalists will touch it now. But, yeah, I mean, it does seem like there's a lot of new entrants there. Superpower and Function Health kind of doing the upmarket version. But there's lots of other ways to get labs done, obviously.
Yeah.
And I think, of course, Theranos was more about the actual kind of base level of getting the lab work done. I think a lot of these players that are doing cool work that you mentioned are more about kind of facilitating getting the labs through the large lab companies and then when AI is really great of, like, interpreting the labs. And so, of course, a lot of our, you know, our patients are getting labs done consistently and think the people there are doing a lot of cool work.
That's cool, Jordi.
Amazing. This is great.
This is fantastic. Thanks so much and congratulations on the massive round.
Say it again.
Thanks, guys. Thanks.
One last size, guys.
It's great to be on y', all asking questions. And, you know, I was thinking about as I was getting on as we. Feedback's really big on our team, and I always get feedback about talking too fast. And so as I was going on here, I was like, oh, I got to make sure to talk slowly. But then I realized YouTube and podcast ad, that's probably where most your views are. People will just change the speed they want anyway.
A lot of people say they just listen to the show on 2X because it's too much content.
The real high performance 3X. That's the future. Yeah.
People can listen to whatever. Whatever they want.
Anyway, thanks so much for stopping by. We'll talk to you.
Great to meet you.
Cheers. Next up, we have Matic Robotics coming into.
I'm pumped for this one.
Yeah.
Yeah.
You've been talking to the founder. I was DMing with the founder. He sent us a robot. We're going to have it be cleaning our new studio in no time. We're excited for that.
Wired said this is the best robot vacuum we've tested. Fantastic. Scored a rare 10 out of 10.
Let's hear it. Can I get the Ashton hall sound effect?
There we go.
I haven't heard this at all today. It's killing me.
Let's go.
Bring them in and play that effect again. Jordy. Welcome to the stream. Welcome. Congratulations on the Wired article. Congratulations on, on all the progress. Can you kick us off with a little introduction?
Robots and homes.
Robots and homes.
They said it could have been done. They said it was a 2035.
Most people, they ship a render, they ship a video. This guy ships a real robot. What a concept. Welcome to the stream. How you doing?
Thank you guys for having me. I appreciate it. I'm a president co founder at matic. We build home robots and my background is in computer vision and product and we prior to this we were at Nest. So that's a quick background.
Oh, that makes sense.
Yeah.
Okay.
So how many people thought you were crazy to go make another take on the next Roomba, you know, or whatever, Whatever the pitch was, I think they still do.
I think it's still. Why are you doing floor clean robots? That's the, that's the question we get quite a bit. And the answer really is that this is the only robot with scale.
Yeah.
This is the irony or of what we are doing is that a thousand robot ship. We are already the second largest American consumer robots company.
Wow.
So we talk about this point of view, that there is this perception that navigation and mapping and localization in indoor environment is solved problem. But I tend to think of it as a Fermi's paradox, that if it is a solved problem, better all the robots in our lives, why aren't they at the airports? Right. Why aren't they at the airports, grocery stores? Why aren't we swarmed with it? And the answer is that it's actually quite a hard problem. Problems, number one. Number two, economic viability, which is making it profitable and surviving as a business itself is a challenge and on a flip side, making it valuable for customers.
Yeah.
Talk about the evolution of the relevant breakthroughs in artificial intelligence and which ones you are true beneficiary of ImageNet, obviously. Very groundbreaking, the transformer architecture. Haven't heard about that having an impact, at least in the Amazon's Roomba context. Are you using transformers? What about LLMs?
Matic uses like a vision. A vision first vision only, which John has been nerding out about totally for months.
So I want to know. Yeah, like it does, is this, does this lead into the why now? Or how do you tell the story of the underlying technologies that have led to. To an improved experience here?
A great question. We actually left Nest and Google in 2017 to start working on it because of two trends. One is a self supervised learning techniques that were emerging, which is what LLMs are, essentially they're learning on their own. And then second one was that my co founder and CEO Navneet helped spec out Google Coral TPU from nest perspective. So that trend of AI chips coming out and compute skyrocketing was a trend we saw coming. And between with those two things, we thought it was possible to build edge device robotics. And the reason we thought edge device was critical was we as humans, we don't have hard minds. Latency is really critical, especially in a dynamic environment that we live in. So we always thought that robots have an ability to make decisions really fast. And specifically for indoor robotics, we just felt like indoor world was built by humans for humans, for our visual perception system. So vision only robotics was the only way to go that it needed the same perception system as us. If you're trying to build let's say level five robots, well, level five robots for cars means that cars drive like humans. So inside home it means that they behave like humans, clean like humans, manipulate like humans. So it should have the same perception system. And those were the trends that helped quite a bit in doing that. And now if you look at our robot, what it does is it builds a Google street view like map on its own. So the way we thought about it is we as humans, we go into a new home, new environment, new indoor space, we self explore, self map and then remember exactly where we are so localized. Can robot do that? Well, the answer is yes it can. Our robot does that, but it still has the same ability as cats and dogs. We can't tell our cats and dogs to go sit by the couch or go in a living room. They don't understand that yet. And that's where VLMs and some of this open source source dyno and clip, some of the models that are being released are really useful because now we can extract semantic embeddings and information at the image level out of it and we can actually transfer that into our map at a voxel level. So each, our maps are built using voxels, which is like a 3D pixel 1cm by 1cm. So each voxel actually knows that it belongs to a chair or a human leg or a child or a piece of furniture. And that's when you can start asking and doing all kinds of things like hey, go clean by the bookcase in the living room and it knows what you're talking about. So it's really, that's the next layer which is turning it into much more of a natural language interaction. Interaction between a robot and a human being.
Talk about the actual training runs that go into your models. Is there a concept of iteration on the training runs like GPT 1, GPT 2, 3, 4, 4.5.
He said they spent less than a million dollars on Nvidia on compute.
Okay, yeah. So break that down. How do you think about. Obviously you're acquiring data constantly, but then is there this pace of let's do another bigger run and is there capital at risk when you, when you actually roll out a big training run?
Great question. So I'll take a little bit of a higher view and come down. But there is this concept in self driving car as well as robotics that there would be one God model and that God model would do everything. When you look at practicality of a deployment, almost always there are multiple models at a smaller level that you, you do it. So we've always taken this approach that we're not trying to, we're trying to build product. So whatever is available to us, let's go do it. So our approach has been combination of obviously neural nets and some of the work that's happening. But also what we do is refer to as a special AI. So that's a term that Dr. Fifi Lee really prioritized and we use human information bottleneck principle. So the way we do this we have image to voxel neural network and then we combine that with long term slam using both classical and techniques and build this world and then the physics of the world is permanent. Now as a human being I can know that there is a wall here. There is. I know how what will gravity do? So based on that for us it doesn't take 26,000 iterations to learn how to tie shoe. This is so in the same way, once you know the physics, you can predict things of that physics that I know certain objects will topple over if I were to do that. So that's how we think about it. So we use information model like principles. So for us, computes and data has been critical. But it's less of a traditional logistic gigantic data set and let robot do everything on top of it. So it's less of a compute intensity. But there is obviously iterations.
Is there something like a mixture of experts model that you could kind of pull from and design like. Yeah, to kind of scale up the model. Is that relevant at all?
Absolutely. So we have our own master student models and stuff. Exactly. And what we and the way we use it is that hey, the 3D part of it we use traditional techniques of a special AI then adding semantics and understanding and context part of it, that's our master and student model works very well. But even for the neural net, sometimes for the precision, there are master and student models that we can use for precision as well, just to see the way humans see. So occupancy network that we have, a lot of it is inspired by the approach that Tesla has taken over the years for to build their full self driving.
Talk about simulation. Are you using a lot of simulated data? I imagine that you could procedurally generate a million or trillion households with different furniture legs and stuff pretty easily drive virtual robots around that, use that to generate data. We've heard about a lot of that in the humanoid context. Are you seeing luck with synthetic data for your product?
Absolutely. I think we started with self supervised learning. Then we realized that simulation and supervised simulation actually works very well as well along the way. So we built our own simulation environment using Unreal Engine with our own robot. So we've customized it over the years and have a large set of environment, but that usually takes it. What we've seen is that it takes US to about 0 to 80% but that the final 20% always comes with the real world data. So we initially trained it to create the master model, but then the precision and fine tuning almost always comes from adding real world data.
Switching gears a little bit on product strategy, I imagine you have ambitions well beyond this initial form factor. Walk us through. Yeah, walk us through. Maybe the. Was this always the form factor that you were going to start with? And at what point do you look at kind of expanding from here?
Great question. So we always imagine goal was always to go build Rosie the robot. All of us want that something sort of Alfred that comes in a home just takes care of everything. But we thought that the best way to do it is the way human child grows, which is in the first five years of human child they just learn how to navigate from a perception perspective. They're just trying to make sense of 3D rules and they pick up the object and learn that it drops. So in the same way floor cleaning robot allows us to do that, but then we evolve and say just like a 5 to 10 year old child, can it start picking up shoes and moving it around, can it just organize unbreakable Items? So for 5 to 10 year old we don't give them knives and scissors and all the risky stuff. So in the same way can it start with this task and can we along the way productize it and start shipping and then ultimately put it all together as a full blown robot. And we thought this approach was better because as we did consumer research and we always start with customers and work backwards, we realized that there is a lot of apprehension about robot and whether they can do things accurately. So even though robot vacuums have been around for 23 years now, they've only penetrated 13% of the US households. 87% don't even have it yet. And the reason is because they're just not that good. They're not accurate, they're actually kind of dumb. So for 2002 they were amazing device but they hadn't moved forward. And we thought that purpose built device that solves the problem to the nth level is way to earn customers trust and then iterate to the second, third forecast. And, and the way we built it is if you see our current robot, we have a black crown, we have a black border on the top. That's where the eyes and the brain sits. And it's very much like a human being. And we always thought that we just have to build that once and then it just grows up just like a robot. So as robot scales, it will scale. So the beautiful part of what we built is that. And then we have demos of it in our thing where we can just raise the robot, maybe even put it at a 6ft level and everything just works out of the box. So you can put it on top of the humanoid and will map the entire space for humanoid and with the 6 degrees of freedom with the same precision at 1cm level.
So are you thinking about adding like a robotic arm so it can pick up a shoe and put it back in the closet?
Absolutely. As we go into users home, I've been about 200 homes now, real homes now. And parents always talk about can you just give me a tall cleaning robot? That's my biggest pain point. So that comes again and again. The second thing we've heard is a lot of kids talking about their parents who live on their own in Florida or Texas and they don't have a time to go there and they're not technologically savvy as well. So they're like we'll take this robot, we'll actually control it, clean their home. But can you also send me a 10 second time lapse at the end of the day to confirm that they're okay.
How do you think about privacy? I imagine you have to message like hey, we need the data but we're going to anonymize it, you can trust us. But then there's data leaks that happen. I'm sure this is an important part of your messaging, but what are you saying to people?
Huge, huge part of. So prior to we worked at Nest, I was a product lead for Nest Camera. So I know privacy is a big deal. So that's why we do the whole thing on the edge device. And then the way we do is just opt in. And we always knew and this is our prior startup at Flutter, we also did gesture detection where webcam and did this that if you build a trust with user, there will be a spectrum of users. On one end there will be users who says don't ever take even my telemetry data. I don't want to share any anything. On the other hand, there will be user who says, take everything you want, I don't really care. In between, there are lots and lots of users who would say, hey, these are the long tail at which your robot fails and I actually want you to help get better. So we'll share the data. So we haven't even done it automatically, but there is a record button on our app and users have already uploaded thousands of hours of data with permission on their own.
Do you have evals like, like when you train a new model, do you put the robot.
The final eval is can the matic robot clean up after two toddlers after they've had dinner?
I was gonna say frat party.
You know, throwing frat parties. Toddlers.
Toddlers are more messy. Spaghetti and meatballs.
A regular vacuum can't even.
No, no, no, no. Instant disaster. It needs a scoop and all sorts of stuff.
Anyway, Jordan, how do you expect the humanoid how do you expect the humanoid market to play out over the next few years? Right? It's obviously an area that you guys want to. You guys will be competing in that market over time, but clearly made some, some big decisions around how to get there. There's a lot of companies that have raised so much money that they, and, and you know, once you've raised a couple billion dollars, people are going to want you to be shipping or at least having, you know, robots that are, that are creating value in these settings. But at the same time, like iRobot, you know, and we talked about this offline. Irobot is the biggest robotics company in the US with 50 million units shipped. Amazon Robotics is a second at 750k. And then Boston Dynamics is only shipped 1500 robots in its entire lifetime. And so when. But at the same time, we just had Sonia on from Sequoia Capital a little bit ago and she's like very humanoid pilled. She was like, I think they're coming like you know, quickly. And so I'm curious as somebody who's actually building and shipping robots now, kind of how you project out the next few years and I imagine you must be kind of entertained by it all. It's going to be, you know, there's a lot of capital on the line, you know how hard it is. But I'm curious how you think that's a great question.
There are two pieces of the puzzle there. One I think you guys have touched in past interviews around accuracy and how accurate can robotics get. And the thing that we talk about internally is with AI today we are collaborating. If it gets 90% of right, we're pretty happy with it. With robotics, especially in a trivial task, we almost always want to delegate. We want to set it and forget. We don't want to do that last percent because that's, I don't want to finish that last corner cleaning my of the cleaning or that one last plate. And that actually puts bar much higher. There is a corollary there as well, which is we go to school maybe four years, eight years, learn how to do coding. So if AI gets 90% of right, we are mesmerized. But we don't really go to school to learn how to navigate our home or how to pick up a glass or how to vacuum floors. So the trivial the task, the higher the accuracy expectations for customers. Because if you make mistakes in just picking up a glass, they think of it as a dumb robot. Like, come on. And the analogy is imagine someone is helping you set a dining table for your dinner party one out of 100 times, and one out of 100 times they break one glass or one set of plate. Yeah, There's a good chance you're going to fire them. So the buyer of accuracy is much higher there. So that's one piece. And then second thing is the adoption. So this is where General Magic is a good example in our mind. General Magic tried to build iPhone in 1995, didn't really work. Amazing team, all X people. Tony Fadal was there and instead what we got was purpose built device. From cell phones to PDAs to iPods to BlackBerries and then we combine everything into an iPhone. So in a similar way, we tend to believe that purpose built robots will see light of the day first and then they will get combined into multipurpose devices. And the more you have a human form the more expectations that customers would have. So there is a home side of it and there is an enterprise side of it. So we tend to think that in enterprise or factories there is a good chance robots would be used in few years with homes. We think it's a little bit far away.
Yeah, that makes sense.
Yeah.
And if you're buying, let's say a humanoid comes in at even comparable to something like what Unitree is selling right now and it's $40,000. Your expectations on that are gigantic. Gigantic. So it's going to be an uphill battle. But we'll have to have you back on as there's.
Yeah, one last thing. What were you about to say?
I was thinking that you were touching on a really great point. We actually talk about it internally that there is no ubiquitous consumer electronics device higher than $2,000.
Yeah.
TV cars have been. Right. Cars have been around for 100 years. Utilities clear even though. And that's usually 10,000, $20,000. And even then it's a considered purchase. We just don't wake up and do it. So the utility and the value has to be proven. And then you have to convince customers to say, okay, it is worth spending 10, 10,000, $20,000 and it will survive five years. 10 years. So there is a productization element to the robotics that needs to be paid a little bit more attention to.
Well, thanks so much for stopping by. This is a great chat. We will talk to you soon.
We are going to use our.
Maddox, thanks for having us.
We're going to use our Matics at the new studio.
Yeah, we're excited.
Absolutely.
Tell us how it goes.
We will let you know.
We'll talk to you soon.
Bye.
Next up, we have Fastino coming in the studio. Sounds like an Italian name. Faustino. Faustino.
Ask him about it.
John.
You, you love to. You love to. Your Italian accent is your favorite.
Yeah, it's my favorite. Big news. Fastino trains AI models on cheap gaming GPUs and just raised 17 and a half million dollars from Khosla. Let's bring him into the studio. We got Greg here from Faustino or George. George. Welcome. How you doing?
How you doing?
You guys hear me all right?
Yeah, yeah.
First off, how do you pronounce the company's name? Is it Fastino or Fasteno?
So funny enough, fastini in Italian means a feast.
Oh, okay.
But Faustino, it's kind of a play on fast and tiny, like very thick and small.
At naming, you've been feasting on Nvidia graphics cards. You've been feasting on Khosla venture dollars, putting them together. Can you break down what's the news this week?
All the above. Yeah.
Yeah.
Well, great. Great being on, guys. Am I your last one of the week?
Last one of the week.
Tapping it off, hoping to save the best for last. You guys pretty fresh, by the way. I feel pretty underdressed.
Yeah. Hit the soundboard. Let them know that we still got energy. I want to hear the Ashton hall effect. Not that one, the other one. Let's go.
It's.
It's Friday.
But we still got energy. We're not slacking off here.
Next time I'm gonna have a suit.
Please buy one.
I'll go.
Please.
Bring it on, Bring it on.
Suits are, are underrated. Should have one for every day of the week.
Yes, yes, yes.
Yeah, I gotta go to New York in a couple weeks. I think I gotta go first.
By the.
Taylor, we got a suit guy for you.
Yeah, yeah, yeah. We'll introduce you anyway, break down the news and then we'll start talking about the business.
Yeah. So great being on. This week we launched tlms. So it's a family of language models called Task Specific Language models. They're small lightweight models that are really fast and they're built for AI developers. So being task specific really means that we're more accurate on enterprise tasks than large models like OpenAI or Gemini. And they cost a fraction to train. So we spent less than 100k on GPUs to train our models. But we're beating industry benchmarks for enterprise tasks.
Okay, so are you fine tuning open source models? Are you ripping apart a mixture of experts model to just have a smaller set of weights? Give me the scope. I've seen the GPT 3.5 circles like this and the GPT 4 circles huge. How big is your circle?
I guess so we're not fine tuning or distilling any open source transformer based models. What we're doing is very different. We took a different approach from the large labs. We built a new architecture that maintains high accuracy even with very low parameter count. So we're not fully revealing exactly how many parameters, but all of our models are far below a billion parameters.
Oh wow.
Our accurate, our architecture actually gets more accurate as the task becomes well defined. So they're not generalist models. You cannot ask them to do anything, but they're extremely performant for the tasks that we built them for.
Okay, talk about the data sources. I imagine that if you're doing summarization, you need a Whole bunch of examples of that. To train on text to JSON. Probably need some text and some JSON. A lot of stuff's out there on the web. Are you scraping, are you crawling, are you buying data? Are you using open source data sets? Where's the data coming from?
Yeah, really all of the above. I think there's a big debate out there in academia as to whether synthetic data or real world data leads to a more accurate model. We've definitely been using a blend of all the above but the first models that we're rolling out and you nailed them perfectly. We have models for developers doing text, JSON, text SQL. We have an agentic function calling model that we're putting, putting out. I know you guys talk quite a lot about agents and an agent that can book a flight for me or can book a hotel for me. So we have a very lightweight model that inferences in milliseconds that can basically take what the user wants and call an API. So very much developer focused. We've got models that can parse documents, redact private identifiable information from documents which is huge for banks, insurance companies. We have a really fun model. It's our favorite model in house. It's a profanity censoring model.
I love that.
Amazing.
We don't swear on the show so yeah, yeah, we try to keep it.
Light in the office but you can imagine we've had some fun late nights building synthetic data for profanity model which gaming can be used anywhere. It's pretty much the funnest red teaming we can do. I try to plug my ears or turn the.
That's great. I mean if you're inferencing this in milliseconds, is there then a desire to deploy this at the edge? Run this in the cloud of the business that's actually deploying this?
I just have to ask for the profanity model. Could we run it in real time while we're doing the show? So we can drop say an F word. F word, bleep.
That's what I want.
Yeah, it'll work in real time. It'll be much faster than an existing LLM.
Yeah, I think the real TV shows, they have a system that puts it on delay and does something like this. But the, the delay has got to be so much faster. If you're imagining like using Whisper and then this. There's a lot of things but in terms of that latency. Latency is really important to us. I imagine it's important to your clients and customers. Are you seeing Demand for let us run your model and we'll still pay you, but we just don't want to go back and forth with your API.
Yeah. So there are a lot of ways you can deploy smaller lightweight models. Obviously we're going to be heavily reliant on our API. But when models are small enough footprint, which actually comes from a low lower parameter parameter count, you can run them on prem, you can run them on CPUs, low end GPUs. I think Ash and I, my co founder, Ash, he had a dev agent similar to cursor in 2023 after I sold my last company, I was actually an investor in his startup. He had a problem where his LLM costs ended up being higher than his headcount cost. And it's a problem that a lot of agent companies face. So I was actually, I spent a little bit of time as a GP after I sold my last company and all of our portfolio companies were facing the same thing, rising cost of lm. So it's not only latency, as you mentioned, accuracy is a big problem with large alarms. But frankly, the key issue that we've seen is that LLMs just aren't built for the enterprise, they're built for consumers.
Right.
So GPT Gemini, they're trained on trillions of data points. They're used by our friends, our family every day. They help you code, they help you get food recipes, they help you prep for podcast interviews. They're not built for high scale enterprise tasks. Right. But enterprises are spending millions of dollars a month on these large monolithic APIs. I want to tell you guys a story.
Sure.
How GBT is being used. So my, My wife's dog got really.
Sick a few weeks ago.
Cute little guy, 13 years old. He has cancer. We went to the pet hospital and the doctor basically recommended that we put him down. We had her best friend on the phone and we're trying to make a decision based on the doctor's recommendation, symptoms, dog's age, what to do and who is the tiebreaker. We asked GPT. Hey, GPT. Here's what's going on with my dog. Here's the situation.
Wow.
Should we put him down? Right. So my wife was using GPT to. To play.
Yeah.
Play maker. For the record, GPT told us to put him down and we didn't listen. He's doing well today, but wow, that's a crazy story.
Why would AI is the antichrist trying to take out the dot, the poor pup?
Yeah.
Why would a large bank, bank of America, Citi, jpmc if all they're looking to do is analyze your bank statement or look at some log for fraud, why are they using the same model model that my wife used to consult on her dog's mortality? Right. So using these massive models, it's like trying to come up with a, with a cool metaphor for the show. It's like, like, it's like the doordash guy riding Saturn 5 to come in for a pizza.
Right?
It's so unnecessary. And frankly, that's why large enterprises, large banks haven't put ChatGPT or an LLM into a chatbot.
Yeah, super fascinating analyzing your bank statement and it's just like 500 on dinner. You cannot afford to have a dog. You got to put that dog down. It's like Chase, what are you doing? J.P. morgan, cool it with the recommendation.
Reasoning is a very sexy word in space right now. But from Speaking with almost 100 Fortune 500 enterprises since we announced our precede round in Q4, they don't want models that can reason. A bank does not want a model that can reason its way through your last 100 chatbot users logs and figure out their personal information. So when you're building lightweight task specific models like this, our models are in domain. They're only trained to do the task that the enterprise using them for. So I think we have that edge very much just in how the models are built.
Okay. Talk about the gaming GPUs worth less than $100,000 in total is what TechCrunch is reporting. Did you build that yourself? Do you have your own data center? Or are there clusters out there of low end GPUs that are all rigged together from like, like legacy bitcoin mining applications or something like that? Where are you getting these?
Yeah, so we have GPUs in house, we use GPUs in the cloud. But we all told our models take about a couple hours to train. The training cost for one model is less than the cost of a Chipotle burrito. So much said about how but a.
2012 Chipotle burrito or 2023 one that.
Didn'T give me food poisoning. Hopefully. But there's been so much said about when Deepsea came out and they only spent $10 million on H1 hundreds, however questionable that number was. I think what we're trying to do as a super small team is show that you don't even need H1 hundreds to build generative models for enterprises. Right? So we didn't use a single H100. We used T4S gaming GPUs, low end V1 hundreds and. And you can do that. I think we've proven that banks don't need a model that takes six months to run or it's going to drain Lake Tahoe for a training run.
What's more important with that training run? Flops or memory? Because I imagine lower token counts. You haven't released it, but I imagine you can fit it in memory and so that unlocks it. But talk to me about the dynamics of like building a cluster and thinking about the different parameters that go into the cards that you select.
Yeah. So we have a family of. It's going to be less than 10 models, most likely for the next six months. I'll say that they're far below a billion parameters each. So we don't need a cluster even. We can just run these on one or two GPUs each.
For inference.
For inference, yeah. And for training it's the same thing. It's a very low end GPU for an hour or two. So we definitely believe that there's going to be a giant shift in how language models are used. Right. So you guys have seen waves of the last couple decades. So these massive IBM mainframes shifted into client server architectures and open source software used to have these massive monolithic builds that would take, you know, that would ship a month at a time. Software applications were shipped so much slower and then out came microservices and you have a different release for your payment gateway and your APIs. This kind of workload partitioning as we call it, it's completely going to change the landscape in language modeling. So there was a report from Gartner that came out about a month ago saying that small task specific models are going to outpace LLMs and enterprise usage by three to one in three years. And we want to lead that. We definitely think that every developer is going to become an AI developer. So every dev today will need to be able to integrate a language model into their code. Just like they're integrating a open source NPM package or Python library. It needs to be much simpler and that's very much how we're looking to change the game. It's going to be really hard to compete with the big labs if we're just focused on the models, which obviously we're a foundational model company. But we need to make much smoother developer workflow integrations. We need to make life easier for devs. And right now it's.
Where does this go? I mean, I know some of the stories about companies like Ramp, for example, our sponsor, they need to digitize receipts so they get a lot of images. They do ocr and I think Google provides an API for that. There's a bunch of companies that do. OCR comes through as kind of messy cluster of text, then pipe that through GPT4 and boom, you have structured data. Llama comes out. Okay, maybe it's getting cheaper, but this seems like something where you'd want to go to you guys and get an even cheaper model that's distilled just for that one task. But that feels like almost like you're a consulting shop or is there, is there a place where a company says, hey, we've been using GPT4 or llama and we've done, you know, 10 million inferences and so we have a lot of data about what works, what doesn't. Can you train a custom model for, for us to drop our inference cost by a couple orders of magnitude? Or are you trying to focus more on more versatile foundation models that can be just tools in the tool chest and aren't kind of one off specific systems for a specific task within a specific company?
Yeah, I think there are a few ways to answer that. The first one is probably talking about agents and how agentic systems are evolving. I'm definitely in the camp of thought that says that agentic systems will take over legacy SaaS systems within four to five years. Right. So when you see how these agents are being put together, it's typically daisy chaining 8 or 10 LLM calls. So in a chatbot, you want to parse a query, you want to then figure out the right document to give back to the user, summarize the right chunk of that document, give it back all in real time with a very smooth chat interface. So we definitely see a world where you have different models for different tasks. And, and we're not saying that we're going to replace large generalist LLMs. The models that are larger, they're good at reasoning, they're good at research, they do things like orchestration, so they'll help orchestrate this entire pipeline. That's still going to be the large model, that's still going to be your GPTs, you're going to be your Geminis. But the actual agents, the workers that are calling APIs that are doing these sort of deterministic, high scale, high throughput tasks, those are all going to be very small, intelligent, task specific models. That's how we see it play out.
Cool.
Nvidia is down 0.6% today. Is that because of you? Is the market, are they pricing? I mean, billions of dollars, billions of.
Dollars have been evaporated from the markets on the news.
No, but how do you, you know, how do you think, you know, assuming Fastino just gains, you know, massive adoption over the coming years.
Yeah.
How does, how do you think that impacts the GPU market, GPU demand broadly?
Yeah.
For, you know, for the record, the low end GPUs that we use are still Nvidia GPUs. We're still, you know, we're still a big Nvidia.
Another 10 trillion to Jensen.
Jensen might appreciate if you weren't so efficient and you, you know, raised, you know, $500 million and gave it to him.
Yeah.
Have you thought about doing that?
If he can help us scale and go more viral. We'll need more of them for inference, for the record, but I think there's going to be a huge demand for, for consumers, for LLMs as they are. I think we, we were lucky enough to have two of the first OpenAI investors on our cap table.
That's right.
In the very beginning when there was a pitch deck, there wasn't a business model. They didn't think that they were going to be a consumer company. But the consumer appetite for LLMs has gone crazy. Even during the deep seq moment. Didn't Deep Seat get to number one on the App Store? My, my wife, my friends are all downloading Deep Sea. So the need and the, the hunger for consumers to, you know, automate their lives will constantly be driving the need for these larger generalist LLMs. We just don't believe they're needed for the enterprise. So we're taking a very different approach.
Very cool.
Makes total sense.
Anything else?
I love this conversation.
Me too.
This is super fun.
He's an absolute dog.
You're an absolute dog.
You're an absolute dog.
Anytime you guys want to talk about LLMs and I might get some help on buying a suit for New York.
Oh, for sure.
We've got you. And seriously. Well, we, we got you.
You got us.
I want to figure out, I want to figure out this real time censoring thing. I think it'd be hilarious.
We have, sure.
We have some guests that come on and try to drop F bombs.
It's unacceptable.
Our children listen to this.
It's unacceptable.
And I think it'd be hilarious if it was like, you know, like a duck.
Sound great.
So our people will talk to your people.
Yeah. Appreciate it, guys. Thanks so much for having us On.
Thank you so much.
Hey, big news. Yeah.
Yeah.
Rippling has raised 480. Or, sorry, 450 million at a $16.8 billion valuation. And bigger news.
Let me see.
YC is a customer.
Really?
And that is big, considering YC has created all the big payroll companies. Gusto deal. Rippling.
Yeah.
Gary must have been finding it hard to pick favorites.
Well, I'm texting with the team. Hopefully get Parker on soon to talk about the business. One last thing. We have a couple posts we want to go through, but, Michael, can you check the printer? Because I think we got a special printout for today. We haven't been printing posts very frequently, but we got one post that I wanted to print. Hopefully it printed. Let me see. I don't even know if it printed.
It did not print. All right, let's see. What else? Is it working?
I'm trying to print it again, and we might be out of paper, but. Okay, but we can pull up the digital version. We're gonna run it back anyway. Luke Metro said this show used to print out my tweets and read them. Now they have the head of the army, so. Thank you, Dalut Metro. I tried to print it, but we haven't printed in so long that the printer's not working. Anyway, there's some other posts. Did you see the drama in and or a world about Matt Grim taking notice co to task for selling some fake equity in the company?
Yeah, so I. It's hard to know. I mean, the way that notice was decided. Displaying this information was not consistently candid is how I would describe it. And then the funniest thing, you called this out to Matt. Apparently the CEO of notice messaged Matt and said, hey, I'm finra registered, so not supposed to post publicly on social media. Happy to continue the convo privately or do a call if you want. Let me know. Buddy.
Buddy. It's a war crime.
Hitting Matt Grimm with buddy is a war crime.
Str to jail. It's so bad.
So brutal.
It's so bad.
I actually think the notice platform is pretty cool.
Oh, yeah.
Like that. They. They have a bunch of.
You know, I mean, I imagine that there's probably some steel man here. There's a million ways that, you know, it's a big company. There's a lot of investors. Someone could have come and. No, I think figured out a way to put some.
No, I think what was happening is an employee.
Oh, really?
The reason that the. The way that you would have zero fees.
Sure. Is that common.
But it Was, yeah, it's common. That wasn't being.
And there should be transfer restrictions.
I mean these are very standards.
So there's something odd. I mean there's been a big, big history of these odd like secondary sales. Like for a while people were doing forward contracts. Did you ever follow that story?
Oh yeah.
So basically, I mean, I think they still work. I think they're definitely banned. In most companies you're not supposed to do forward contracts and it's in your.
But the whole nature of a forward contract is that the company doesn't really. There's very good chance a company would never find out.
True. But they can still ban it in your employment agreement. Like it can still be something you agree to when you join the company. So basically a forward contract, if you're not familiar, it's the right to purchase the shares at a future date, much like a stock option. So you're basically writing an options contract against your shares, shares in, in the third party. And, and the, the shares themselves don't actually transfer. And so the company in theory doesn't need to approve it. But it's very necessarily no and they wouldn't necessarily know. Yeah. And so this is a big thing. Very, very controversial. A lot of people don't like this. And so even though it doesn't, it doesn't really, it doesn't result in a whole bunch of like legal complications that obviously you're not transferring the information rights because you're not actually transferring the shares. They couldn't sue the company. That's the big reason why you want a clean cap table is because you have to deal with every investor. You have to give them information. They can sue you if they just own a forward contract. They probably can't do that, but it's still a problem and creates all these distortions in the market. And so Matt Grimm taking them to task, he says we are one of the good guys, says CEO of a company who solicits retail investors to buy shares at a significantly inflated price. For what it's worth, in a privately held company they do not own shares of, have direct access to or have any information or information rights from which to discern financial performance or market positioning or anything whatsoever to inform the proposed investment, all while not clarifying publicly or for that matter to the clients they are soliciting how exactly this exposure is structured or what precisely these clients are buying. And while privately hiding behind a claimed veil fake by the way, their FINRA registration means they can't comment when keeping it real goes too far. Rough. So clean it up. You don't want to.
I mean, this is on your bad side. He could basically say this about most secondary brokers and platforms.
Anyway, we got some massive breaking news. We got some personality. Jacob Efron's been promoted to managing director at this point. We love to see it. Very interesting the rumors.
This is a maxed out contract.
Rumors have been swirling for a long time. He was in free agency, considered free agency. Stuck with Red point, got promoted. Congratulations to him.
Couldn't be more excited for everything ahead.
And weird, weird terminology over at redpoint. Not gp, not partner. Managing director, very investment bank.
Like, you know, official business.
Andrew Reed had a funny post. He was coming from banking. No matter how senior I get in venture, I'll always think that a managing director is more senior. To me, mogged feels.
Feels very senior.
It does, it does. Anyway, Arvind Srinivas over at Perplexity is taking more shots at Bloomberg. Bloomberg is such a joke. While Perplexity does real time call transcriptions for free, Bloomberg has a 15 minute lag and it costs $30,000 a year.
To be clear, that was Marcelo who said that somebody at TechCrunch will listen.
To this and say do not miss.
Bloomberg is a joke.
Yeah.
Anyways, what Perplexity is doing around real.
Time call transcription tech crunch reports is my quote. Me quoting someone else as Arvin.
That's what I was saying. That's the risk.
The bar's low these days, folks. The bar's low. Anyway, any other posts we want to go through? The Pope is American. Vatican City has a Buc EE's now and a Waffle House and a Costco and that's great. They've taken over. America is in control. It's fantastic and we hope you have a great weekend. We hope you have a great Mother's Day. Pick up something simple.
Thank you for joining us this week, folks. We had a great time doing this show.
Yeah, it was fantastic. It was a good show for tuning in and we'll see you next week.
And remember, it's Mother's Day. We talked about this three hours ago.
Bowl of pronatalism, folks.
Take care everybody.
Have a great Mother's Day.
Cheers.
Bye.
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