EP #39 Should We Be Fearful of Artificial Intelligence? The AI Panel w/ Emad Mostaque, Alexandr Wang, and Andrew Ng

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Frankly, even as someone in AI, I feel like man it's tiring. There's so much going on.

Physical things in the real world are much further from being disrupted by AI.

And it's going to create wealth faster than anything we've ever seen.

The beauty of AI is that they can analyze information faster than any person.

We're just literally starting to explore these. All of us are engaged with governments. We're trying to help them. It's a bit difficult when they're just catching up to the Internet right now. Now it's got to the point where this technology could potentially be dangerous. So not everything needs to be open, but we do need to be transparent and careful when stuff gets out of our control.

I have to admit, I'm not letting chatgpt tell me where to invest at this moment in time.

In school, a lot of kids have been cheating and They've been using ChatGPT to write essays and book reviews and do their math.

Cheating implies as a contest. School should not be a contest. You will never not be without this AI as you grow up.

My question is about content creation, especially in music.

You will have perfect music models by the end of the year. We believe this technology could be existential and we will treat it as such.

One of the greatest drivers for peace on the planet is making sure every mother has their children with the best health and the best education. A more peaceful world for us is a world in which we uplift everybody, which is what this technology has the ability to do everybody this year at Abundance.360 Given the meteoric rise of AI, I decided to put together an entire day on AI with three of the most extraordinary thinkers you've met. One of them, Imad Mustak, the chairman, founder CEO of Stability AI Also brought to the conversation Alexander Wang, who's the founder and CEO of Scale AI. It's a big data machine learning platform that accelerates the development of AI. He founded it when he was at MIT at age 19 as a student, dropped out after the first year to become the youngest self made billionaire ever. I also brought Andrew Eng, the Managing Partner at AI Fund. He's co founder and chairman of Coursera, the founder of Google Brain. Love the name of that. And one of Time's 100 most influential people. Between Imad Alexander and Andrew, you can get an overview of this field. How fast is it moving? How disruptive is it? Is it something you should be excited about or fearful of? My massive transformative purpose is to inspire and guide entrepreneurs to create a hopeful, compelling and abundant future in humanity. And that's what I'm doing with this podcast. To open up every relationship, every conversation I have with you, to inspire you, to support you in going big, in helping uplift humanity. If that's of interest to you, please subscribe to this podcast. Allow me to share with you the wisdom that I'm learning from the most incredible moonshot entrepreneurs on the planet. Let's jump into this episode. It's a conversation that everyone needs to be having in your company, in your family, and definitely at the heads of every nation. Enjoy.

Thanks, Peter. And thanks to our amazing guests here today. We've been talking about this actually for years. When we look at the rapid acceleration of AI and this disruption that's kind of happening very, very quickly from this point forward, and when we look at industries and workers and whether they're getting.

The understanding, the knowledge and the reskilling that needs to happen to approach this current world? And in what ways do you see or do you believe we can do that faster and work with governments and.

Larger corporations and education systems to help enable this?

Because we're all talking about positivity and.

Abundance and I think we're very privileged in this room. The question is, for the rest of.

The world, what are we doing and.

In what ways are you involved as leaders?

By the way, we've got 40 minutes here, so lots of great questions. We asked who wants to take that on?

You know, so it's a very important point. I think the world is changing so fast, it's difficult for a lot of people to just keep up with what on earth is going on. Frankly, even as someone in AI, I feel like, man, it's tiring. There's so much going on. So I think maybe one of the things I'm doing. Years ago at startup co founded Coursera, which to this day offers a lot of courses, often works with governments to train up different people. I think that one nice thing is with online education, where with digital education we can speed up the rate at which we help people figure out, you know, learn the new technologies and figure out what to do with it as well. And I think media also has huge important roles to play. And eventually I would love if we can build tools like if you look at Google, the UI is really simple. The backend is insanely complicated. Just type what you want, you get answers. So I hope that AI tools can evolve to the point where, you know, you could just use it without nearly as deep of education needed. And I think a lot of generative AI tools are headed in that direction.

Yeah, I think it's supernatural. I mean, that's why super space natural like chatgpt was so successful because you just type and it just came stable diffusion, just type and then have images. Right. And so I think making these things more and more usable has led to the explosion because it kind of comes from the natural language understanding of humanity itself. It's trained on these large corpuses of an entire media set. I think on the policy side, I think all of us are engaged with governments. We're trying to help them. It's a bit difficult when they're just catching up to the Internet right now.

By the way, the most linear organizations on the planet, right? If not sublinear, they are.

And you know, and again, the typical approach to this is regret minimax, you know, like stop it, ban it. But it's inevitable now and again. It's kind of a global phenomenon. One of the problems as well is that, you know, you've had an acceleration, but you haven't had a maturation. So there's lots of excitement. How much implementation is there now? There's going to be a bit of a pause because it has to be in the current wave, even as research keeps going and you go into engineering and application. And so I think we're not sure exactly where things are. I think Andrew talked a bit about where the value lands on the stack. And again, we are all kind of at different areas of this stack. So we ourselves haven't figured this out. And we're doing our best with the community to try and do that, to communicate to policymakers and make education courses and others accessible.

Michael, good to see you. You're next, pal. So this is probably a question more to imad, but anybody's perspective is welcome. I am done lots of programming. I usually like to think about abstractions or concepts. You have a concept, let's say drawable, that's fit for some purpose and so it can do that thing. Now with AI, we're starting, we are using English language, we're using prompt. So definition what you're asking for a lot more vague. So when it's vague it may have edge problems. Right? You have to clarify things a lot more. And so my question is, do you still see a value in having well defined, structured, uniquely named things which you can compose for well understood result or do you think will diverge more to. Everything's a bit fuzzy, everybody just provides a lot more text and it just somehow the system figured out for you?

Well, I think that's an excellent question. I think a lot of the applications right now have been very surface level without the contextual awareness of like, you know, Game of Thrones in South Korea or something like that. Amazon had this thing where they had the six page memos, right, rather than presentations. But another thing they used to do was write the press release beforehand. And so if you write the actual overview of the program in the comments now for kind of copilot and things like that or GPT4, it will write the program based on the comments, you know. So again, I think this is a failure for us to understand prompting and some of these other things. It's something that Andrew and I have been talking about. You know, again, it's gone so fast. We've got the surface level we have to explore. Another way to think about this is like game consoles. When the Wii first came out, games were a bit crap by the end it was fantastic. We're just literally starting to explore these. So it's simple words now and then we'll compose and build structures around it to get the most out of these weird thingies.

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Hi, guys. Can you hear me okay?

Yes, we can hear you. Great.

Perfect.

I'm from Chicago. I am in healthcare and I love the idea of healthcare and longevity. I may be your only practicing physician here. I had the idea of joining this group because as a practicing urologist, we are getting pummeled. And as Peter and AI and healthspan go on, most urologists are going to see people who are older. I think all you guys are going to be a patient of either me or my colleagues here soon. The point I'm making here is that there is an overflow of patients and we as clinicians are getting bombarded. And the question is, in light of workflow shortages with our staff and the incoming number of patients, how to use AI most efficiently in terms of point of care for patients getting into our offices as well as having AI be part of the evaluation process, because as many people may know, 90% of the time, we see the same 10 conditions. So the question to the panelists is, number one, how would you advise a physician or healthcare provider to set this up? And do you think that this is something that is easily attainable? I liked Alex's thought about starting small. And then the second question is, if you were to do it, is it the sort of thing that would prevent, I mean, is there anything in there to prevent others from doing the exact same thing so that if you are spending a lot of time and money into this that nobody else just kind of scoops it from you? Thank you for taking my question.

Yeah, I'll say real quick, if you have a concrete idea for what you like to do in neurology, let me know. I think teams could help. Maybe my team could help execute that. And one example is something AI funded. We worked with a fantastic founder, Alison Darcy, and now different CEO Michael Evers to support building up wobot, which is a digital mental healthcare chatbot. You can actually install it on your phone. From the data published Ella Stanford seems to be able to take effect relatively quickly in terms of treating symptoms for users of symptoms of anxiety and depression. So I think that there are actually lots of opportunities to apply AI in interesting ways to healthcare, but figure out those concrete use cases that allows us or others to execute on it.

Yeah, I'll say two more things, which is that I think the first is that getting to market first is actually an advantage. Certainly other people can copy the idea, but I think this is one of these things that's well studied in business. But there's going to be a moat from whoever's able to establish the use case first and then able to use that pole position to get more and more data into the system. So let's say you built the best possible system for identifying some sort of disease or condition using AI, then you're going to, just by launching that service, get far more data than anyone else and race ahead of, of where anyone else could possibly be. So the sort of currency of the realm of AI really is data. And if you have a niche data set or a unique data set, that's going to give you an initial advantage. And if you're able to build a strategy, continue amassing more and more data that will keep you ahead.

We're going to go next to John here at Mike2. Let me remind you, please look at the questions in Slido. Upvote them if you're here in the audience or on Zoom, we'll be pulling them. John, please, what's your question? And keep the question short, if you could.

Sure. So I'm a medium to small business owner, I'm a physician, I own a diagnostic laboratory.

So I hear a lot of buzzwords.

You need to implement AI, you need to create, you know, you need to.

Put your data on a balance sheet.

That sounds awesome. But the. But my initial question is how do you get started going down that road of, you know, we have a ton of data, but how do you put it in a package that you can actually monetize it?

Put on a balance sheet.

So what are the process of just going about doing something like that and then number two, implementing AI into something.

That I think is a Very concrete.

Us, like a case point for our company is digitizing pathology and allowing an AI over engine to help pre diagnose or triage cases or whatnot. How do you go about implementing something like that in a company that's my size? By either pairing with someone else or do you try to bring a team in to develop it? So like what kind of playbook just.

To get you off the ground, move your company. Alex, I think you're.

Yeah, so we have tools. You go to scale.com, we have data set management tools that you can upload all of your data and basically build that into a data set. That's step one is to get all of it into one tool, build up an entire data set and then you can do a bunch of things from there. You can label and annotate the data, turn into a data set that you can train a new model on top of. You can bring in a host of companies, we could be one of them. Or there's a bunch of other vendors out there that can take that data and turn it into a customized model for you and then launch it and figure out how much impact you can possibly have.

Then you find out who that data is valuable to. Ultimately. We're going to go to Slido. There's a great question here. I'm going to send it to you. Imad. It says here, is there any commercial activity which AI will never be able to disrupt? What will be the factors to understand that? I mean, it's an interesting question, right? It's like the question asked of Bezos. What, what won't change, right?

There's nothing that will never be able to disrupt it because you'll have autonomous robot agents that basically it's Blade Runner, right? Indistinguishable from humans. So you can't see any commercial activity, cannot disrupt.

Do you guys agree? Alex, let's go with you.

You know, I think at least in the short term and who knows, this stuff could all change. But in the short term, physical things in the real world are much further from being disrupted by AI. So, you know, anything that we have to sort of like interact with or do something physical in the real world, robotics is relatively behind a lot of the sort of pure digital, pure online kind of AI systems. So, you know, I don't know if the word is never, but at least for a long time, you know, we won't have AI system. You know, an AI robot that can do construction or that can do, you know, mining or some of these things that are very Very interesting.

I'm, I go into the, I go into EMODs category here, but that's my opinion. You guys are actually, Andrew, you know.

My friends and I, some of my AI tech friends and I, we used to challenge each other, name an industry that I will not be able to disrupt. So we challenge each other to name that. And I had a hard time coming with until one day I thought, all right, maybe hairdressing industry, you know which industry? Hairdressing.

Hairdressing. That's easy.

And I used to say this on stage until one day, one of my friends who's a robotics professor, she was in the audience when I sat down on stage. And afterwards, she stood up, she pointed at my head and she said, andrew, for most people's hairstyles, I don't know how to put a robot to cut their hair like that. But your hairstyle, I could totally robot to do that.

Oh, that's great. All right, we're going to go to Kiran on Mike 4. Do you think with the large language.

Models like GPT, will they ever be.

Able to explain why they generated what they generated, or will they need a new breakthrough?

So right now you can ask the models to explain why it said what it did. It's not clear if those answers are actually correlated at all with the actual reason why they aren't. Probably correlate with why they actually said that. And so there's sort of, you know, humans have this bug, which is that we will do things and then if somebody asks us to explain why we did the thing, we'll come up with some post hoc rationalization that oftentimes is not literally the reason why we did a certain thing. Usually it's, you know, there's the analogy of the elephant and the elephant rider, which is that our emotional brain is an elephant and our rational brain is this is this rider of the elephant that just sort of is trying to explain what the elephant's doing. So I think the large language models are similar, which are that they're going to go through some process by which they make a decision or they say something and then you can ask it to explain and they'll come up with something on the spot to try to explain it. This is something that Ahmad and I were actually just talking about. How do you get greater levels of interpretability? How do we do research in the direction of actually truly understanding where it's coming from? But that's all active research.

Nice. Giselle, you're the next contestant. Good to see you.

So given what has happened to Social media. I actually rated the way I feel about AI as scared shitless. Because you guys, you are the leading edge of this.

This is your space.

Is anybody doing anything to build parameters around this technology? So that what you were saying umat about someone calling you in your mother's voice and selling you st? That is, we already live in a world where we don't know what truth is. How are we going to fight this?

Well, I think you see information curation going through social networks. I mean, this is the Twitter verified, it's Apple identity. It's kind of a bunch of other things. Webank, contentauthenticity.org, which is Adobe thing around visual media. But we do need to have centralized repositories of trust because the cost of information becomes zero and creation becomes zero. And unfortunately, there is nothing that can really regulate this output. Like, there are laws in various countries that you must identify AI output. Like with stable diffusion, there's an invisible warp mark of things, but it's become so accessible that we need to have standards quicker than the system is adapting. So this is why I think information distribution systems need to standardize around this right now, which is something we're pushing a lot.

Yeah, I mean, there's a big question, can we even govern against any of this? Right. All of this is bits we have. We live in a world of porous borders, data flows. So, Giselle, we're going to have a lot of these conversations around ethics and around implications. Guys, this is happening right now, right? This is this year, next year, not 10 years from now, five years from now, what gets played out. This is why we need to be paying such attention to it. Giselle, thank you. I'm sure we'll hear from you a bunch more times. Let's go to mic number three in the back there and then we'll go to Zoom and we'll go to our slido. All right.

My name is Hajime, running an AI startup in Japan, Series D now getting much closer to the Japanese government. And they're concerning about the disaster and resilience because there's a huge risk on an earthquake as well as like font Fuji erosions.

So my question is, like, what could.

Be the interesting but the practical way to apply AI for those like disaster recovery?

So we actually worked on something in this direction for in the Ukraine conflict, which has obviously been, you know, this horrible thing to happen to a region and a country. And you're able to. One of the things that is really unfortunate in any sort of disaster situation is that, you know, seconds really matter, you know, every second spent that you aren't, you know, deploying resources to help resolve one of the, you know, people who are, who are in a damaged structure or, you know, tackle a certain area is, is going to result in either lives lost or further damages to infrastructure. So one of the things that you can do with a combination of satellite imagery plus drone imagery on in major cities or major areas that are being impacted is use AI to automatically identify damage on a building by building level and a change in that damage in every area and use that to coordinate humanitarian response. So this could be applicable, you know, this is applicable in any sort of natural disaster, any sort of scenario where fast action really matters. The beauty of AI is that it can analyze information faster than any person.

Yeah.

We're doing a variant of stable diffusion for satellite imagery and time series data as well. And so that I'm sure we'll be using that toolkit.

Amazing. All right, to our Zoom audience, we're going to you next. Nico. Nico Drynik, where are you on the planet and what is your question?

Hi, Peter, I'm calling in from Austria, from Europe.

Beautiful.

And I have a question. I have a question regarding the profile.

Of a Chief AI officer.

So what private profile should this AI officer have to fulfill this role best?

Should it be technical?

Should it be another profession?

Should it be a mix?

Because it seems to me that combines a lot of traits that are found in entrepreneurs and CEOs. Anyway, so what else is needed? And I ask this specifically, coming from a non tech traditional background as law in my case.

Thank you, Nico. Great question. Let me preface a second. What my advice as a first step for folks is. I like the idea of get your team to experiment and so forth, but what's been working for me is finding somebody who knows the field out there, understands who to partner with, is advising as a strategic advisor to the CEO about the platforms and such as a Chief AI Officer in that regard. Do you guys agree with that idea? And what would be your. What do you think that person should have as background?

Yeah, so actually, as far as I know, I think I might have been the one that coined the term Chief AI Officer.

I stole it from you then.

No, actually, years ago I actually wrote an article in Harvard Business Review. I remember googling, but chief AI Officer didn't really exist on the Internet. So I actually wrote a piece in Harvard Business Review with my specific recommendations to the Chief AI Officer profile. I think a person needs to be technical enough to understand the tech and then also business oriented enough to work cross functionally to figure out what are the valuable business use cases for your specific application. But I have like a multi page article on HBR talking about, I would.

Imagine the CEO or the head of whatever division says this is what I think is possible, this is what I need. The chief I officer is sort of an interface to the world out there to bring in a scale, to bring in part of what imad what you're building. Does that sound like a reasonable role in a company?

Yeah, I think I'll have be technical enough to make good judgments and then also to make the buy versus build decisions. And often for many companies you should buy a lot and build a little bit. But to make those decisions requires both deep technical judgment as well as the ability to figure out understand the business well enough to figure out the use cases.

Simad, I can't tell if you're agreeing or disagreeing.

No, I think so. I think that there's an implementation side of it, like an applied engineer is a good thing. I think passion is kind of key. Yes, you have to throw yourself, otherwise there's no way you can keep up. Actually, my suggestion would be that given this suggestion that you have, there should be an internal A360 repository around the ecosystem, the latest trends and others that can go to all the chief officers here so they can keep on touch through that.

All right, Steve, you heard it, you're in charge. Wonderful, thank you. I hope Nico, that answered your question. Let me go to Slido next and thank you. Some great questions. Katie, I apologize I didn't note your name earlier. Actually. What is the first step companies can take to evaluate the data they have? How can we get started extracting from the systems we have in place today?

Yeah, so I think the first thing to do right now the new large models are quite capable of just sort of ingesting in existing data you have and basically whatever format you have. You know, in some cases it can be literally as simple as uploading a bunch of PDFs into the models and sort of extracting all the information from there. So I think by the way, something.

You just said, which is very important, right. It's like you can almost upload anything.

If it's text, right?

Your Outlook files, everything.

Soon images as well.

Soon images, yeah.

Multimodal text and images.

Yes.

One point of caveat. Turns out a lot of enterprises have what's called structured data, which means basically giant Excel spreadsheets, so structured Data models like ChatGPT and so on. Are less directly well suited for, but text and images is getting really good.

Yeah, that's true. Yes. Right now, general models are still worse at Excel than many of us, but. Yeah. So these are the data formats. I would basically start the initial process, catalog all this data that you would want to upload into an AI system and then reach out to one of us to help you put it into an AI system.

I want to go to Christy's question on Slido here and I'm heading this towards you. Imad. If you had to put all of your money, your family's money, your friends money into one of the technologies here or industries, which one would you put it into?

Cha Ching, I'm all about risk diversification. No, I mean, it's an incredibly hard thing to say. My thing is that what I advise all the young people is actually I'm advising young people. Don't go to university anymore. Do PhDs. Yeah.

Don't get an MBA. Go work.

The thing can get in GRE right already. So I think, you know, put it into Andrew's fund. I think it'll do well. But there are very few kind of options here, apart from you have to use it to basically upskill yourself. This is the thing. Or upskill your community.

Invest in yourself, invest in your company.

This is literally the case because this is such a disruptive, massive game changer and there are no easy ways to do that other than like, actually let's spend money reasonably quickly to get up to speed on this technology because you will have an edge of everyone else. As Alexander said, it's first to market in the stock market itself. There are no real investable things here at the moment.

Are we going to see the first trillionaires in this area? Most likely. Is this where the greatest wealth creation is going to happen? Or do you see that in Bitcoin first?

Yeah, I think we see this. I think again, like Bitcoin had a GPU and then it had an ASIC era. We're at the GPU era of this technology, but it's real. And we're going to go to Asics and it's going to be everywhere and it's going to create wealth faster than anything we've ever seen. I call it the AI bubble, actually, which is why I'm not joking. Like, you know, if you have funds that are focused on this, almost a rising tide wave lifts all boats. You know, even if you have the alpha side that will come through, like a trillion dollars will go into this. Like 20 billion went into Delivery startups. Last year, a total I think probably of 6 billion has gone into this sector to date. 100 billion has gone into self driving cars. A trillion went into 5G.

Yep.

Just anything here that's investable.

Go to Farzam next.

I want to add one thing to what Iman said about jumping in. There's actually one. There is. I think sometimes people think, am I too late? And the answer is you're not. You're actually very early still. AI on, you know, don't know if it's exponential, some very rapid growth. But if you jump in now, I think you look back a few years from now and people say, wow, you know that my buddy over there was really early jumping in because it's still growing.

So right, it's bitcoin. It's literally 6 billion. It's going to go to 600 billion in the next few years. 100 times increase. Right.

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I've been sitting here and really blown.

Away with all the great technology AI.

And, and I'm in a business of real estate, which is, I'm not playing in that arena, but I'm here to find out what do I need to do. But what I'm. What I'm actually brought me up to the.

How many folks are in real estate here? Raise your hand, please. Get a sense so you're not alone.

Okay, thank you. But my main question is really comes back to the sort of what do we do with all these great things? And how do we hack the world.

Of peace around the world? And how do we understand with the.

Data that it's the need of what Russia, China, Iran, North Korea, what is their problem? What are their challenges? What are the stuff that they want to blow everything up? And what is our problem? And how do we look at ourselves as a citizen of planet Earth and how do we work with the geniuses we have in front of us to really be able to bring this thing? Because there's a lot of not cool things we hear around the world.

All right, we got your question. How do we save humanity?

That's an easy one. Right?

Thank you.

Seriously, I mean, Imad, please dive in because this is something you care deeply about.

These are universal translators. Go to ChatGPT, paste something and say write it from the perspective of a Tea Party conservative. It'll do that and then you'll say rewrite it from the perspective of libertarian and it'll do that.

So you're going to have the ability very soon we're all going to have some version of Jarvis, right? An AI that is in your ear, on your body and so forth. And that AI will be able to tell you, are you being biased in this conversation? Because it can look at the conversation from other points of view. Right. I think one of the greatest drivers for peace on the planet is making sure every mother has their children with the best health and the best education. If you are educated, if you're healthy, if you have opportunity, you're not going to want to throw your life away. A more peaceful world for us is a world in which we uplift everybody, which is what this technology has the ability to do. Thank you.

I think there's one more thing as well. It comes to trusted third party when you Have a disagreement with someone and you have someone trusted between you, then a lot of this stuff that can speak both your languages as it were, understands both your contexts. So again, this is the hope now that we have this universal translator not for language, but for stories, context and other things. We just got to build it right and make sure it's distributed as opposed to centralized and controlled with one specific worldview.

I'm going to ask a question and jump in here. OpenAI's approach right now. And Elon Musk tweeted the other day that I guess OpenAI dismissed or Microsoft dismissed their ethics committee or something like that. Is there a general sense in the community of concern around that or is that not a valid concern? Thoughts? Not tweeting this out and if you don't?

Well, I think one thing, I'll just speak for everyone. I think we all have to admire what OpenAI has done. The work in large models has really been driven by OpenAI and kind of, as I mentioned before, I shouldn't say that all of AI was on the wrong track, but certainly we were not as focused on large models and the incredible capabilities that we get from these large models if not for OpenAI. And I think so far they've been very responsible in their deployment of the technology. I think they've been very thoughtful, they've invested a lot into research to make sure that these models are deployed safely. And I think they have a very. It's a hard thing for any organization to do to build such incredible capability that has never existed before and try to deploy it safely.

Okay.

I feel like the easy answer would be to say, oh, we need to be super concerned about ethics and it's all going south, it's all going poorly. I think we do need to be really concerned about ethics and responsible AI and to be really pragmatic. I think when EMOD released his model, which is fantastic, love what he did, I think that EMART had a lot of flack about how could you release this thing like that. But net net, I'm sure some of the models was used for negative use cases, but I think EMART created massively more value than harmful use cases. So I think that we should be very clear eyed about the problems and the harm and do our best to mitigate that and then also be clear eyed about the huge benefits they're releasing these models and all the wealth and abundance that this also creates. And that trade off is a very tricky one. And I do see many highly ethical, well meaning AI teams agonizing over that.

Yeah, I think I agree with kind of both. And as Alexander said, amazing technology and it's been really a breakthrough that allows now humans to scale and they've been at the core of it. I have disagreements with OpenAI. My core one is just a case of now it's got to the point where this technology could potentially be dangerous. Like as we scale more, we don't know exactly how it works. And so I'd love for them to be responsible, to be more open, transparent governance, transparent kind of procedural stuff. And again, really adhere to a very strong charter. They don't have to release their models. You can have proprietary models. Like I funded the beta of Mid Journey and if you look at Midjourney version 5, it's amazing. I said you never have to open source it because it's great for humanity to be creative, you know. So not everything needs to be open, but we do need to be transparent and careful when stuff gets out of our control. In their own AI AGI, the Artificial General Intelligence Document, they say, we believe this technology could be existential and we will treat it as such. We believe this technology.

I was surprised when I read that as well.

So in that case, you should be transparent and you should be really transparent about your governance. Extra. More than anyone, similar to companies that can affect the environment.

Hey everybody, this is Peter. A quick break from the episode. I'm a firm believer that science and technology and how entrepreneurs. Entrepreneurs can change the world is the only real news out there worth consuming. I don't watch the Crisis News Network. I call CNN or Fox and hear every devastating piece of news on the planet. I spend my time training my neural net the way I see the world by looking at the incredible breakthroughs in science and technology, how entrepreneurs are solving the world's grand challenges, what the breakthroughs are in launch longevity, how exponential technologies are transforming our world. So twice a week I put out a blog. One blog is looking at the future of longevity, age reversal, biotech, increasing your health span. The other blog looks at exponential technologies. AI, 3D printing, synthetic biology, AR.VR blockchain. These technologies are transforming what you as an entrepreneur can do. If this is the kind of news you want to learn about and shape your neural nets with, go to dmanandis.comblog and learn more. Now back to the episode. All right, we're going to go to Zoom next. Charles, where are you on the planet and what is your question?

So, I'm in Palm Beach, Florida.

I welcome all of you to come down and visit.

Most of us from New York have.

Already left the city and we're reestablishing ourselves here.

This is going to be very specific because Andrew, you asked us to be specific. So this is actually addressed to you.

And perhaps to Peter as well if.

He wants to chime in.

But how do you use AI or CHAT GPT to recommend an investment for your venture fund? You have a lot of inputs, a lot of variables.

In my business of investing, there are too many variables to do it. So if this is a thumbs up.

Thumbs down, are we going to invest in this company?

How do you do it using AI?

Thank you. Great question.

So I think ChatGPT is amazing. I play of it, building multiple businesses using it. I have to admit I'm not letting chatgpt tell me where to invest at this moment in time. Maybe it gets much smarter. Well, I won't mind, maybe replace me and I'll retire, but not yet there. Maybe the reality is making an investment decision or decision to build a business is so complex and so multifaceted, I don't know if the mechanisms that even digitize all of that data right now. And even if we had the ability to digitize all that data, I think that while very exciting, progress is being made to improve the reasoning capabilities of large language models. I think it will still take a while to get through the very complex multi step reasoning that I think investors are using to make decisions.

By the way, I remember one of the founders of Google Ventures, who is a friend, he's not there anymore, told me that Google Ventures actually had built algorithms for making decisions on who they invest. It's based upon where the company was based, what year is established, a whole bunch of other parameters. I don't think they're doing that anymore, but it's an interesting idea. But with that, let me go to Madhu who's going to have a brilliant question for us. Madhu. All right, speaking of positive use cases.

I'm going to play out a scenario and I want to hear from all three of you if that's possible. I'm a large health system, I've done the sick care for all of our existence and I'm trying to build a chatbot that supports our nursing staff or our triaging staff. And I have all this proprietary data. The specific question is what foundation models should we start with? If my team's working on this project, what foundation models should we start with?

Ima, do you want to start?

Yeah. You'll be able to use StableLM and StableChat soon. Right now, probably it's going to be GPT Neo JNX on kind of that side of things. And that would be the open models that you can use inside your cloud or on Prem for the proprietary ones. I'm not sure like Claude. Is Claude available yet?

Privately available.

Privately available, yeah. So basically the next generation of language models aren't coming via APIs just yet. So right now the people that we know in the healthcare industry, they use GPT Neo X and Plan T5. Precisely. But there's no real services around that. Again, we're still in the research to engineering phase, but in the next couple of months you'll have services that enable you to do this far more seamlessly than before, including the Microsoft GPT4 chat service as well that you can fine tune on.

Yeah, Llama as well. I'd mentioned Llama, although it's non commercial.

That's a problem, right?

But internal. Well regardless, I think one thing that's critical that Ahmad is sort of implicitly mentioning is that on health data you're very likely going to need a model that you can control and own because there's a lot of Phi and Pii that's going to go into these models. So because of that I think these sort of offerings where you have to give data to another service are probably not workable. So I think you probably need to take one of these open source models of which Ahmad named a bunch Llama's, a new one from Meta and a host of others and train them up.

While choosing the right language model is important, I feel like a lot of one of the things AI Fund would recommend to different companies what language model to start building on top of. So these trade offs with the model size and cost and do you want to fine tune or do you do prompting? There are all these things, but I feel like the language model is important. But my mind is also going to a lot of the decisions you need to make after choosing a language model and the processes to execute those. Well.

All right, we're going to go to my deputy son over there. Hi Bear, what's your question buddy?

So I'm a kid, so I still go to school and in school a.

Lot of kids have been cheating or.

Cheating and They've been using ChatGPT to write essays and book reviews and do their math.

And I guess my question is how do one, how do you think like.

Schools should evolve to deal with that?

Or do you think that it's really.

Declared cheating if it's a tool that we're going to be able to Use later on.

Brilliant question. Let's give it up for Bear here.

You know, to me, this big question of transparency, it's a great question. Thank you for asking that. I feel like if you use ChatGPT and you're willing to openly tell the teacher I'm using it and the teacher says you can use it, that's fully transparent, that doesn't feel like cheating to me. The thing that is concerning is if students do it but the rules require or leads them to hide it and that kind of I'm going to do it but I can't tell them about it. That's what doesn't feel very good. And candidly, schools are struggling. The debate is people will be able to use these tools in the future. So should we train them to use it or is it a crutch that will limit a person's growth? I have a controversial opinion. So I have a 4 year old daughter trying to teach her math and because she's four years old I could stop her from using her calculator. I just don't buy her calculator. So she's learning to act with her own brain. One of the challenges challenges of ChatGPT is most students using it are in an age where parents and teachers don't have an ability really to easily stop as use. And so it does concern me would be a crutch that stops people from doing certain things. Because I love to I use calculators but I feel like maybe learning to act with other calculators is useful. So figuring out what we need to do with ChatGPT and educational system is something I see a lot of schools struggling with. I wish I had an answer.

Yeah, I've got something. So cheating implies it's a contest. School should not be a contest.

Yeah, got it.

So I think most schools are basically child care systems mixed with status games. I think schools should embrace this technology and they should really think how can we impart knowledge into individuals? How can we impart critical systems? Because again, you will never not be without this AI as you grow up and you have to prepare for that.

Awesome. We have three minutes left. I'm going to do the following. I'm going to ask you to mention your questions very briefly and we'll do a speed round. Karthik, what's Your question? In 20 seconds or less.

Thanks Peter. And gentlemen, thank you so much for your brilliant insights.

Quick short, what is your question?

My question is about content creation, especially in music and arts.

Okay, Ellen, what's your question? Very short.

Privacy And AI in healthcare information.

Okay, Ben, what's your question? Should my 15 year old continue taking Python and should he go to college? Okay, so we've got privacy, we've got. Say again, Karthik.

Creation of music and arts.

Creation of music and arts. Okay, ask your question, answer what you want.

Yes to Python, yes to college.

Yes to Python, yes to college. Okay. Creation of music and art.

Music has its stable diffusion moment. Audio LM and others. You will have perfect music models by the end of the year.

Ellen's question again. Privacy in terms of healthcare.

I think it's a really big topic. Privacy of data when it comes to AI systems. I think that this is going to be probably the biggest regulatory battle when it comes to AI is what data is allowed to be used to train these models and what are the sort of what consent do you need to get over data and people's data to be able to train models on top of them? I think it's a really big societal topic that we're all going to wrestle with over the next few years and I, I, I encourage everyone to get involved if you have an opinion.

I think also AI for health care has to be auditable, interpretable as a medical device typically. So it's going to have to be based on open foundations for that particular use case.

Nice. All right, Harry and Babs, what are your last two questions here? Real quick?

ChatGPT asks what measures can be taken to counter the misuse of AI by countries like China.

Okay, we're going to talk about China in our next session, so hold your question for that. Babs, close us out. I was going to ask about the evil empire using the our AI against us. We're talking about ethics and all that kind of stuff. They're not into ethics. Okay. We're going to be talking about ethics and empathy and us versus China in our very next session. I'm going to try and keep us on time. Let's give it up to these incredible individuals.