#56 - Three Breakthroughs: OpenAI’s Latest Release

Using AI to fight future pandemics, ChatGPT's newest release, and 6G and beyond. Let's go.

The fact that we have the ability to think about these things differently, even, you know, a few years later, will fundamentally change how we think about what would be a perceived limitation.

Who basically said, okay, this thing, I spent an hour and it did what it took me a year to do.

Yeah.

And so I think it's just adding to the mix. They forget what 3G was like.

This is glo— this is global connectivity across all industry.

Hello everyone. Welcome back to another really awesome episode of The Tech Optimist. We have a 3 breakthroughs episode for you today. And of course these guys need no introduction, but they're gonna get one anyway. We have the legendary Mike Collins, founder and CEO at Alumni Ventures. Ventures on one side of the table today. And then Mike's savant in today's episode is going to be Michael Perry, a partner within our walls here at Alumni Ventures. And then my name is Sam. I'm the guide, editor, and sort of narrative writer for this show. So I'm gonna give you a quick sneak peek into the topics that are talked about today. Topic number 1, Mike Perry brings up AI and how it can be utilized to fight future endemic. pandemics, epidemics, and just global crises, right? So there's a really awesome article that we dissect that talks about how, um, you know, AI might be able to dissect social media and therefore how it can dissect, you know, other scientific papers that help, uh, scientists and doctors and government officials get further along in their process with helping, you know, the rest of the population with this said crisis. And then we talk about ChatGPT's newest release, Strawberry. And, you know, kind of how insane it is and how innovative and, um, how like the thought process behind Strawberry and how it works is just absolutely bonkers. We have a video that comes along with it that helps describe, you know, kind of how it works and how insane this new technology is. And then we round off the show with the concept of 6G, right? So we all know about 5G on our Verizon phones and LTE connectivity and all that fun stuff, but we try to dissect what it would mean if we had 6G connectivity across the world. So let's dive in.

As a reminder, the Tech Optimist podcast is for informational purposes only. It is not personalized advice, and it is not an offer to buy or sell securities. For additional important details, please see the text description accompanying this episode.

Hello, everybody. Welcome to Alumni Ventures and our 3 Breakthroughs podcast. I'm joined by my partner, Mike Perry. I'm Mike Collins. I'm the founder and CEO, and we get together every week and talk about what's going on in the world of technology. What are the 3 big breakthroughs that you should know about, people are talking about, people should be talking about. Um, and, uh, welcome to the show, Mike. How you doing?

I'm doing good. I'm glad to be on.

Great. Let's, uh, you're kicking it off this week. What do you got? What do you— what struck your fancy?

All right, I have one that's pretty timely. Uh, Mike, you know this, I'm a new parent, so when September, October rolls around, it's like flu shot, COVID shot, everything shot. The kids are always sick. And, you know, it just had me thinking about how far we've come in terms of COVID Saw a really interesting article that's basically saying, you know, how can AI help, you know, fight the next pandemic?

Yeah.

And, you know, I think the reasons in which you think AI could be helpful are both prominent and easy to understand, but also at the same time pretty nuanced.

Yeah.

So, you know, a lot of researchers, epidemiologists, academics warn that, you know, the next pandemic, which they call Disease X, is likely to be here in the next decade.

Yep.

And as they're thinking about this, what's new today versus even, you know, 4 years ago with COVID is how AI is being used to really understand and prepare us for it. So the research and ability for them to use AI is really cool because it's breaking down a lot of complexities as you think about, you know, global, uh, health. So there's aspects of, you know, predicting the outbreak that they're getting much more precision on. There's the speeding up of vaccine development, which I think we all thought, you know, COVID was like moving mountains. I think that'll only be—

They called it warp drive, I think. Yeah.

Yeah.

It was fast. It was remarkably fast.

So they, you know, they've talked about this specifically where it's like, you know, AstraZeneca, for example, are using AI models now to identify and screen antibodies. for different mutations. So, they're running AI upfront on the mutations and then behind the scenes on the antibodies. And, they're saying that this is cutting down time for vaccine development to literally just days.

Yeah.

So, you have the hard science. And then, what I also liked on how the article's presenting it is there's also a view of cutting through the noise of public sentiment, unusual patterns, obviously fake news, people just saying everything. So, To me, it was just this notion of like, wow, it will happen. It's not a matter of if, it's when. And I think the tools that we have in our toolkit are going to be fundamentally different in all aspects of how we would address a pandemic moving forward. Hopefully, we don't have to see it in our lifetime. But if we do, I like that AI is now being used front and center, like full value chain of how we think about this stuff.

Yeah, a couple of thoughts. One, I am just struck every day by how short people's memories are.

Yeah.

And, you know, that where we were, you know, in the spring of, I think, you know, just 4 or 5 years ago and how quick it happened, how disruptive it was, how scary it was. And, you know, now it's just like, oh, this, that, or the other thing and something where millions of people died. And arguably, it could have been 10, 20 times as worse with just a couple of little differences. And so that's one point. Two is I am very excited about the modeling of these things. So we're moving from kind of human physical models To digital models with drugs, drug discovery, drug testing, all the things where we need trials. It's like the wind tunnel, the digital wind tunnel to test aircraft. So much of healthcare is moving into this digital realm, which is just way, way better.

Yeah.

Right? Kind of thing. But I do think We live in a global world. People intermingle, people travel, and we are still captured in a very fragile biological body. Yep. And these bugs don't give a shit. And so, good tech optimist. I am glad people are working on this problem.

Yeah, yeah. I mean, it's, um, they've done it. They did a nice job at the end where it's like, listen, this isn't a cure-all.

Yeah.

But the fact that we have the ability to think about these things differently, even, you know, a few years later, will fundamentally change how we think about what would be a perceived limitation, right? And breaking through those barriers moving forward. So

And let's just give a nod to the people that get up every day to work on these problems while others are worried about more trivial things.

Yeah, this is, you

know,

we talk about patient capital as investors, right? I mean, this is patient innovation. These are the people waking up every day that have a calling for global good. But,

you

know, it's going to be really fascinating to see just how this develops moving forward. And, you know, certainly as AI continues to advance, you know, I think really and truly everyone talks about, oh, you know, here's this big issue. It's also going to be a huge key factor in safeguarding humanity for the next, you know, pandemic, let alone global catastrophe.

So let's be sure the good guys have the best.

Yes, exactly.

Okay, you guys know the drill. Now it's time— before I get into my little spiel about, you know, this article that Mike Perry found, we're gonna hop into an ad. Um, and then after my tech note and everything, um, we're gonna get back into the show where Mike and Mike start to talk about ChatGPT's release of Strawberry and, you know, kind of what that means for the AI world. So we got some exciting stuff coming up for you. Don't go anywhere, we'll be right back.

Hi, just a brief interruption to introduce you to the HealthTech Fund from Alumni Ventures. Alumni Ventures is one of the most active and best-performing VCs in the US, and we have raised over $1 billion from more than 10,000 individual investors. With our HealthTech Fund, you'll have the opportunity to invest in a portfolio of around 20 health tech startups, from transformative healthcare services to groundbreaking diagnostics. Our founders are paving the way for a healthier future. To learn more, visit us at av.vc/funds/healthtech.

Okay, we are back. So now this article that Mike Perry brought up was from the BBC. It was written by Suzanne Byrne, a technology reporter, and it was, you know, released last week. So now this article does a really good job of sort of exemplifying different ways that medical professionals and, you know, government officials can use AI to sort of help prevent or tackle the next global pandemic. Like, um, there's a section of this article that I want to read. Um, so the question is, how could AI help to alleviate, you know, the frightening prospect of, um, another sort of global pandemic? Researchers in California are developing an AI-based early warning system that will examine social media posts to help predict future pandemics. The researchers from UCLA And the University of California, Irvine are part of a U.S. National Science Foundation's Predictive Intelligence for Pandemic Prevention grant program. Quite a mouthful, but they're doing some awesome work. So this funds research that aims to identify, model, predict, track, and mitigate the effects of future pandemics. So the project builds on earlier work from UCI and UCLA researchers, including a searchable database of 2.3 billion U.S. Twitter posts collected since 2015 to monitor sort of public health trends. The tool works by figuring out which tweets are meaningful and training the algorithm to help to detect early signs of a future pandemic, predicting upcoming outbreaks, and evaluating the potential outcomes of specific public health policies. We have developed a machine learning model for identifying and categorizing significant events and that may be indicative of an upcoming epidemic from social media streams. So that's One pretty fascinating way of you know looking at this, and then this is where sort of AstraZeneca comes in. AstraZeneca's vice president of data science and AI R&D Jim Werthel brings up a point that the pharmaceutical giant uses AI to help speed up the discovery of new antibodies. Antibodies are proteins used by the body's immune system to fight off harmful substances that can be used to make new vaccines. So. Mr. Weatherall says the firm can generate and screen a library of antibodies and bring the highest quality predictions to the lab, reducing the number of antibodies that need to be tested and cutting the time to identify target antibody leads from 3 months to 3 days. So it's fascinating, you know, just the 2, uh, sort of polar opposite sides that AI can be used to help such a vast issue that could plague the planet, uh, in the future. One that, you know, tackles social media and tackles what the, the actual body of society is saying or sharing with each other. And then it goes to the science side where the AI can, you know, reproduce hundreds of man-hours in, you know, as you can see here, this article, 3 days. So all this stuff is very, very exciting. Um, but now let's hop into the next subject, um, which is You know, Mike's topic, which is Strawberry from ChatGPT. So let's get into it.

Okay. So on a related note, my breakthrough of the week was the release, which, you know, ChatGPT-01. Yeah. Again, talk about a company that can't name things to save its life. You know, use your own product to come up with some better names, please. So this

is

rumored and affectionately called Strawberry because of the ChatGPT-4.

Yep.

Oh, couldn't count the number of Rs in strawberry. So they released a model built differently, which its strength is in harder reasoning problems and some really clever examples. And again, for me, I've played with it a little bit. It seems to be very different, but really good at some things that the other models aren't, and vice versa. So one of my takeaways is I think we're going to be in a world where there is not one model, one god model for a while, but various models that do different things really well. And I think over the past 6, 12 months, people that have gotten invested in Gemini or Claude or ChatGPT-4o, you know, have learned kind of, oh, it can do this, it can't do that. It's just here is another one that is very good. I used it just personally to outline a tech spec.

It

required pretty significant reasoning. I also gave it a business problem.

Yeah.

And, you know, it was thinking, you know? And again, some of this is good design interface, I think, by the OpenAI guys, which is like the time it's taking, the words that are showing up on the screen. It's like, oh, this thing's thinking really hard about my problem.

Yeah.

And the answers are way more involved, showing their work, showing the logic, showing you their homework. So again, not a lot of time, just released maybe a week ago, but I think it is a big deal. I think there are people that are working on really hard problems. I saw one posting, some PhD student or who basically said, okay, this thing, I spent an hour and it did what it took me a year to do.

Yeah.

And so I think it's just adding to the mix. And then again, the kind of the, the, the third point I'll just underscore again, Mike, is just the speed at which these things are coming out.

Oh, yeah.

Which is, you know, every quarter there's new capabilities and—

It's exponential. I mean—

It's exponential. We are on the Ray Kurzweil, we are on the steep part of the geometric curve. People don't see it, people don't get it, but we are on it and hang on.

Yeah. I'll give you some examples too and maybe for the audience out there, how you think about it. You know, I, we could all read, right? Like they, they put it through International Math Olympiad type questions. It's performing, you know, 8 times better than their current model. You know, it's, it's really excelling in math and coding and whatnot. And I was tweaking it a little bit in the perspective of what we do day to day.

Mm-hmm.

And I was positioning, you know, questions as a venture investor more through the lens of like the scientific method. where you take what a company was trying to do and I reframed it a bit as a hypothesis, like what would have to work, what wouldn't. And I saw that this model was just, it responded like I was talking to someone, right? Versus just regurgitating something.

Yeah.

And you could really see that the model was, I don't know the, you know, the actual terminology here, but it was thinking, right? It was really thinking about it from a hypothesis standpoint, how you would accept or reject it. Through the lens of an investment. And then it got me thinking on this notion that we see in all these companies, which is, you know, an AI, maybe a copilot or an agent for a specific task. I think, you know, very subtly and in an elegant way, OpenAI is almost positioning these models this way, where if you work in a creative field, this is what your content needs to be at the end of the day. Mm-hmm. you know, use Model 4.0. That's actually going to be great for you.

Yeah.

Now, vice versa, if you're doing something much more technical and/or, you know, reasoning from a math perspective, you're going to be living here. So I'm starting to see and maybe connect the dots on how they're building this as a true enterprise function that meets the needs for everyone. And then, of course, at the end of the day, all of these models reinforcing each other. So it was, yeah, it was one. I mean, I consistently have been blown away by what they've been able to do, but this This was a different rigor that was coming out of it. And, I was like, this is speaking as though Mike and I would be about an investment.

Yeah. No, it's just a couple things. One is I've seen they put these models through, I think, the Finnish IQ test, right? And again, a lot of them have been at the 80 level. And listen, an army of 80 IQ helpers can be incredibly valuable. This is like 120, right? So, you know, getting smarter on just that dimension, I just think is noteworthy. My personal kind of heuristic right now, and again, I'm sure in 30, 60, 90 days this will be totally different. But today, you know, September 18th, 2024, I would say I have my own Personal agent where I've trained it on the way I talk, my job, our company, how we think, our culture. Private, that is my personal AI on the shoulder that I use as a generalist assistant, chief of staff. Then I have a series of task-specific—

Mm-hmm.

ChatGPTs, where it's like, I'm creating a model, a template. I do this repeatedly, and I just want you to save me time and increase the quality. And I've got an army of those, right? Small army, but an army of those. And then I think over here, I've got an arsenal of tools that I'm going to use. Google, I'm going to use Gemini, I'm going to use Perplexity Claude, I'm going to use ChatGPT. Yeah. 4.0, 0.1, and I'm just going to apply them where I just have what I'm going to call it, just that I want to learn something. I want it to tell me how to do something. I want it to help me solve a problem or figure something out or scope something. I'm going to try to match what I need and what they're good at. So right now it is still— it's not just turn on my God agent, it does everything for me. I think— I don't know, I think we're a bit of a time from that. But right now it's still kind of, I need to be the— I need to orchestrate it all.

Yeah, I mean, it's just, you know, I— and I will tell you from the perspective of, you know, economy, right? Any job, you know, if you're not using this stuff today, I don't know what you're doing. Like really and truly.

Yeah.

If you're not a leader of an organization saying every person here should be leveraging these tools to find efficiency, you know, we've engaged with big corporates or our portfolio companies have, and it's like red tape all over the place. Regulatory. Don't do this. Don't do that. You are going to fall so far behind so quickly.

Yeah.

As an organization.

You're going to get killed. Your organization, your team, you personally and professionally. This is— you've got to, you know, you got to lead or, you know, get run over kind of thing. I just— I'll give you another example. Like, I had an idea. I had an idea that wouldn't it be neat if I could type in a job in a year and what would come back is the likelihood that that job would be Dead, materially changed, or booming, and why? And while I ate lunch with ChatGPT 4.0 and a little bit of coding software, that I was able to kind of knock that out in 15 minutes using— and I'm not a programmer.

Yeah,

this is all just natural language back and forth. Do it while, you know, interacting with it. And it was like, you know, just, uh, it's very exciting.

Oh yeah.

It's a little, it's a little mind-bending.

Yeah.

But I do think it's, um, I, at the end of the day, I think it's very, very exciting to the where you started out, which is this can be Scary, you can be a Luddite, or you can embrace it and just say, hey, let's lean in and make the future better.

Yeah. I mean, it's going to propel humanity in so many ways. And of course, you have to always take a commitment to safety and recognizing what that means. But, you know— But

it can help you do that, right? I mean, that's the whole point, right?

Yeah, yeah, that is the whole point. And just being able to— I mean, you articulated it well. Sometimes when it's hard, it's mind-bending because you could visualize something in your head. You could attempt to articulate it with a friend or a colleague, but you don't know where to start. All of a sudden, at your fingertips, you don't just have a place to start. You have something that can totally execute on what the vision is for you.

Yeah, you have a tutor and a tutor who is going to meet you where you're at. You know, if you don't understand it, it'll tell you, okay, give it to me at a lower reading level, break it down into more steps for me. And you don't— you're not embarrassed by it. So again, I just— I also believe this is just profound impacts on education and learning.

Yeah. Oh yeah, definitely.

Okay, y'all, I have a little interjection here regarding this. So I was just doing a quick search on You know, the changes of ChatGPT-IO and Strawberry and the Mini and, you know, all the stuff that has come out recently from OpenAI. And I'm a huge fan of YouTube and like visual explanations of things. And I came across this really awesome YouTube video by Matthew Berman. He's this like AI sort of technology extraordinaire on YouTube. He's got a really cool channel on there with You know, almost 350,000 subscribers. So he's got quite a following. And he put out a video on ChatGPT's newest release, and he explains really well how it works and what it does and, you know, how this is super important to the world of AI and how this is an awesome sort of innovation in that realm. So the whole video is 20 minutes long. I'm not going to play the whole thing, but I'm going to cut it up here and there to sort of give you the highlights from it, because I think the information that it provides is really powerful. And I really think it's fascinating, uh, to understand how it actually works. Whereas, you know, we've heard from Mike and Mike about their real-world implications and how they use it and how important it is for the future and everything, but I want to provide more information on how it actually works. So there's some really awesome sort of terminology that Matthew, uh, uses here in his video. Um, But yeah, I'm going to cut it up, get you the highlights, and just dive in from there. So after that, we're going to do our last ad, and then the last topic for today is going to be about the sort of concept of 6G. You know 5G and LTE wireless capabilities, but have you ever heard of 6G and what's after that? Okay. If you haven't, stick around.

So the new model is called O1, and it's a series of models. So we have 2 models available today, O1 Preview and O1 Mini. We developed a new series of AI models designed to spend more time thinking before they respond. They can reason through complex tasks and solve harder problems than previous models in science, coding, and math. We train these models to spend more time thinking through problems before they respond, much like a person would. Through training, they learn to refine their thinking process, try different strategies, and recognize their mistakes. In our test, the next model update performed similarly to PhD students on challenging benchmark tasks in physics, chemistry, and biology. We also found that it excels in math and coding. In a qualifying exam in the International Mathematics Olympiad, GPT-4o correctly solved only 13% of problems, while the reasoning model scored 83%. That is a massive, massive multiple-time improvement over GPT-4o in math. Their coding abilities were evaluated in contests and reached the 89th percentile and Codeforces competitions. You can read more about this in our technical research post. I'll get to that in a moment. As an early model, it doesn't yet have many of the features that make ChatGPT useful, like browsing the web for information and uploading files and images. For many common cases, GPT-4o will be more capable in the near term, and I suspect it's actually going to be a lot cheaper and more appropriate for the vast amount of use cases for a while. For 99% of use cases, we just don't need PhD-level reasoning. But for complex reasoning tasks, this is a significant advancement and represents a new level of AI capability. Given this, we are resetting the counter back to 1 and naming this series OpenAI 01. So they're also releasing 01 Mini, and by the name Mini, you know it's going to be a smaller, faster, and much cheaper model. So let's read about it. The 01 series excels at accurately generating and debugging complex code. This is going to accelerate the transition to AI writing the majority and then eventually all of our code. To offer a more efficient solution for developers, we're also releasing OpenAI O1 Mini, a faster, cheaper reasoning model that is particularly effective at coding. As a smaller model, O1 Mini is 80% cheaper than O1 Preview. All right, so that is fantastic. And by the way, you know I'm gonna make test videos for all of these models. So what's next? This is an early preview of these reasoning models in ChatGPT and the API. In addition to model updates, we expect to add browsing, file and image uploading, and other features to make them more useful to everyone. So it seems like this is the future of OpenAI's model family. And of course, they released a demo video of O1 creating the game Snake. So let's take a look. So the prompt is implement Snake with HTML, JS, and CSS. The entire code should be written in a single HTML block with embedded JS and CSS. Don't use any remote assets. And then it continues. So let's see how it does. So it's thinking, thinking, thinking, and then boom, it outputs it and it seems lightning fast. Now granted, GPT-4o and even GPT-4 were able to do this, so it's not that that great of a demo, but it's still fun because that was the test that I used to test every previous model before I switched to Tetris. And you know I need to test Tetris with this new model. And there's the Snake game, there you go. So it's good, it's fine. All right, so let's read a little bit of the technical paper. And again, don't get too excited because they're not really releasing too many details about how it works. So O1 ranks in the 89th percentile on competitive programming questions. Codeforces places among the top 500 students in the US in a qualifier for the US USA Math Olympiad and exceeds human PhD-level accuracy on a benchmark of physics, biology, chemistry problems. Wow, just imagine spinning up hundreds, thousands, millions of these to run 24 hours a day to discover new science. This really— I know I said it before, but it feels like the intelligence explosion. Our large-scale reinforcement learning algorithm teaches the model how to think productively using its chain of thought in a highly data-efficient training process. So it seems chain-of-thought is built in to run at inference time. That is why it takes longer. That is the thinking it does. We have found that the performance of O1 consistently improves with the reinforcement learning train-time compute and with more time spent thinking test-time compute. The constraints on scaling this approach differ substantially from those of LLM pre-training, and we are continuing to investigate them. So here we can see This is train time compute, and the accuracy just increases with the more train time they put towards it. And then of course, test time, same thing. The more time that they put towards it, the better accuracy it gets. One last test for this video, but you know I'm gonna be testing it in full, so stay tuned for that. How many words are in your response to this prompt? I wonder how it's gonna do because it has a bunch of chain of thought in the background. Is it going to include all of that in the answer? We'll see. Addressing paradoxical query, figuring out word count, identifying word patterns. Look at that. There are 7 words in this sentence. 1, 2, 3, 4, 5, 6, 7. Wow. This is actually the first time where I think it got it right. Officially got it right. This is crazy. Addressing paradoxical query. I'm working through a paradoxical question which involves self-reference and determining the response length. Avoiding unnecessary content is crucial to ensure clarity and consciousness. There it is. Unbelievable. I am so excited to test this model out more. If you're not already subscribed, make sure you subscribe because there are gonna be a lot more videos about this new set of models from OpenAI. This might be the beginning of the intelligence explosion. If you enjoyed this video, please consider giving a like and subscribe, and I'll see you in the next one.

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Okay, so what's your last one?

Okay. All in the next wave of technology. So this is a little funny because I was reading and it was like, what comes after 5G? And I was scratching my head like, are we at 5G yet? Where are we? But so the Pentagon is literally already prepping for 6G. And, you know, for those out there, this is going to be the next frontier of wireless communication technology. Of course, through the lens of Pentagon, obviously, you know, it's going to transform military operations, global defense strategy, you know, communication. But really what this is in essence, and I think this is a good part, right? Like defining what this stuff means.

Yeah.

At the end of the day, 6G, what it's going to do is it's going to yield promising faster speeds, lower latency, much better and more enhanced connectivity. So that can be thrown into so many different use cases that I think we tend to struggle with because it's very Pentagon-driven, you assume military applications. But if we talk about any of these use cases we have over the last 6 weeks, right?

Yep.

Improved healthcare. All right. So now you have much better vital parameters through wearables. You have high-speed data transfer that would allow remote surgeries that we've talked about, would allow like real-time triggers of, hey, this is going to happen, throw an intervention. And those use cases pull through to every part of the economy and every industry from actually being able to realize what virtual and augmented reality is going to be. to an Internet of Things operating system that, you know, actually operates how you think it would. You know, I— this stuff to me, I think, is often, you know, passed on by most individuals. You think like, oh, I have a cell phone, great, it's much better connectivity.

They forget what 3G was like.

This is glo— this is global connectivity across all industry. Yeah. And, you know, to see that they're already pushing, hey, try to get this out in the late 2020s, early 2030s. You know, in the same way we're seeing AI unlock a ton, this type of connectivity is also going to unlock and just reinforce each other. So I think it's very timely. You're starting to see some other, you know, pushes for innovation broadly that would otherwise be, you know, perceived as not as innovative.

Yeah, I mean, I think this kind of global coverage, I think satellite coverage, which obviously won't be at 6G levels. But I think, you know, we're going to have broader coverage, we're going to have smarter coverage, we're going to have lower latency, higher bandwidth. These are these enabling things that are just not as sexy.

Yep.

And that we very easily, all of us, take for granted, you know. But this is, this is very much as a part of infrastructure in a society, every bit as much as, you know, water and

Oh yeah.

Roads and things like that. So,

all right, I'm gonna pump the brakes a little bit. So I looked into how 6G works and, you know, what it is, um, and I found some really interesting factoids that I want to provide before we, you know, round off this episode. So 6G, the 6th generation of wireless technology, is expected to revolutionize communications and connectivity in ways that go far beyond current 5G capabilities. While still in the research and development phase, 6G is anticipated to launch around 2030, just like Mike was saying. Here's an overview of how 6G is expected to work and what it can do. So how it works. So it uses advanced spectrum usage, AI-native networks, advanced antenna designs, and edge computing integration. So now if you're asking, what the heck does any of that mean? I'm gonna tell you. So 6G will utilize higher frequency bands including sub-terahertz frequencies up to at least 100 gigahertz. So this expands the use of radio spectrum and will enable much faster data rates and increased network capacity. 6G networks will incorporate artificial intelligence and machine learning at their core. So then this AI-based air interfaces will adapt in real time to optimize performance and energy efficiency. The antenna designs— so innovative multi-antenna technologies like massive MIMO, or multiple input multiple output systems, will be further refined, and these antennas will enable simultaneous transmission and reception on the same frequency, improving spectral efficiency. And then as far as, um, edge computing integration, mobile edge computing will be built into all 6G networks. Unlike current 5G where it's an add-on. So this integration will provide improved access to AI capabilities and support for sophisticated mobile devices and systems, which are coming out more and more every day and every year. So as far as like what it could do, what 6G could do, right? Um, it, it can provide ultra-fast speeds and low latency, just like Mike was saying. It can enhance IoT and M2M communication. 6G aims to support up to 10 million connected devices per square kilometer, so it'll greatly expand the machine-to-machine connectivity and internet. Advanced sensing and imaging— this is probably where the Pentagon comes in. 6G's higher frequencies will enable more precise wireless sensing technology. This could lead to advancements in threat detection health monitoring, and air quality measurements. Just a few others: seamless integration with physical and digital worlds, space communications, autonomous systems, smart infrastructure. To get like super into the future, you know, 6G could enable more sophisticated smart city applications, improving urban management and sustainability. So in essence, 6G aims to create a seamless, intelligent network that blends the boundaries between the digital and physical worlds. Opening up possibilities for applications and services that are difficult to fully envision and implement today with the software and infrastructure that we have currently.

Yeah, it's well said, right? I mean, it's almost the infrastructure that's somewhat forgotten. But as you think about this, right, I mean, sure, in the military context, you know, obviously faster, more reliable connectivity connectivity across soldiers, satellites, drones, vehicles, et cetera. That totally makes sense. But as you think about what it can do in playing a critical role for AI-driven operations or enabling almost like near-instant data sharing and decision-making, talking about that exponential growth curve, you see that type of connectivity start to happen. Yeah. You know, endless possibilities in what we could start to do in real time with AI.

Yeah. And as venture capitalists, you know, it's just a reminder too, is how well you can do in infrastructure, tech infrastructure. Everybody's always focused on kind of the sexy high-level names, but there's been enormous value creation You know, in tech infrastructure, putting together the picks, shovels, roads, byways, highways of these new frontiers, you can do really well.

Yeah. I mean, we've built a strong portfolio across AV and, you know, a lot of these picks and shovels type plays, a lot of, you know, big infrastructure type companies that are going to enable a whole lot.

Yeah.

So, you know, this is one I always tend to keep an eye on. Yeah. Like I said, it might be funny for some people to think like, oh yeah, like my Verizon phone. But no, I would encourage folks to read up a bit more on it and really, you know, keep tabs on it because it unlocks a whole lot of future economy and industry.

Yeah, for sure. Well, Mike, you've done your tour of duty. Congratulations.

Yeah, it was fun.

We're moving on to another AV partner next week and you've been great. It's been a lot of fun.

Yeah, likewise.

And, uh, we'll, uh, we'll put you back on the circuit. So, yeah, looking forward to talking again down the road. And who knows what's going to be— what kind of crazy future we'll be talking from at that point.

Yeah, exactly. Thanks for having me, Mike. It was a blast. I look forward to, uh, to the next tour of duty.

Great. Excellent. All right, have a good one, Mike.

All right, bye.

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