The Future of AI: Leaders from TikTok, Google & More Weigh In (FII Panel) | EP #127

0:00How should companies and countries think about AI to drive growth and prosperity? The mantra of AI or DI is real, and certainly companies and countries that do not engage will die. We made an investment in a DevTool company, and this thing has grown from 0 to 40 million in revenue in three months. We have restaurants that are operating with no people or one person just overseeing the machine. We're quickly getting into that interstellar moment where you're just interacting in a very human way. My family's using TikTok. How do you think about making sure that you've got measures in place where the responsible use of AI?

0:39It's a particularly important problem for us to get on top of. It's reasonable to expect that within six to eight years, it will be possible to have a single system that is 80 or 90 % of the ability of the expert in every field. What do you consider the most dangerous outcome around AGI or artificial superintelligence? We as humans are not ready for the arrival of this. We're just not ready for it.

1:10Alright, I have the very unenviable task of doing this in 40 minutes when each of you deserve two hours on your own. I'm going to take notes from the conversation this morning and go for each of you and wish me luck. Travis, I'm going to start with you. Founder of Uber, CEO of Cloud Kitchens. We talk about AI a lot and all about the super fancy big billion person transformations How is AI going to change business right now and transform and expand and change profitability of businesses? You're doing some amazing things with Cloud Kitchen and AI, please. You know, those are two different questions.

2:06When I look generally at what's going on right now, it feels like we're entering an era bigger is better. That if you are a large company with a strong business model, that the technology that's coming is actually going to give you competitive advantage over folks that are smaller. Like the accretion of value is going to the bigger players. And there are probably a lot of very simple things that can be done to create more profit and bigger mode on those business models as my guess. So there's just like blocking and tackling like workflows, customer support, onboarding, sales, all getting automated.

2:54We'll make an already strong business model like supercharged and I think for the biggest companies create trillions of dollars of value. I mean, we're doing, you know, my company's doing the future of food, it's real estate, software, and robotics for food. And there's lots of fun, practical things that are happening. They're going to be big, but they're also practical.

3:24We have a machine that makes food. Like imagine if you were to go to Chipotle, that front line of people that is making your bowl. We have a machine that does that. So we have restaurants that are operating with no people or one person just overseeing the machine. But if there's only one person in that room, you know, you got to, we now have that person talking to the machine about how the machine is doing as if they were an employee. So yes. So then it's just simple stuff, but this is where we're going now. Like we have this up and running in restaurants today where you're asking the robot, hey, is the food warm?

4:07Am I running out? This kind of thing. But we just said, well, you know, might as well just give it a personality. So now you can ask, like, did the Dodgers beat the Yankees today, which they did? And you can have a conversation. And it's sort of, you were quickly getting into that interstellar moment where you're just interacting in a very human way. I've got to ask this other question just for fun. If you remained CEO of Uber or were still CEO, what would you have done differently? What would you be, what would Uber be doing now? Oh man. We could take the whole hour on this one. I'll give you a couple things.

4:53Look, we had probably one of the pre -eminent AI labs when I left Uber. And we saw the, you know, the seminal paper out of Google, the attention paper. I mean, you guys know how I rolled when I was doing Uber. Like we probably knew it's a pretty interesting stuff on that front. I mean, sort of in a more practical, on the more practical side, like, we were starting to roll out. And we, of course, were doing the atomic thing. I'll put that aside. I think Elon's going to take care of that at this point. But we were starting to roll out. Almost we looked at transportation as a high -frequency trading business where we would buy trips from drivers and sell it to riders.

5:43We were a market maker. And so we were starting to set up quant teams for each city to do the high -frequency trading of the trips so that we could get the lowest cost reliable, ride more efficient, gain market share, get more profits, all this. This is kind of a fun geeky finance thing. One in 30 seconds, you've disrupted two huge markets. You're one piece of advice for someone here who wants to go disrupt a marketplace today. How do they, what's your piece of advice for them? You know, look, over time I've tried to distill what it means to innovate at speed and at scale into sort of principles or pillars.

6:33They basically are cultural values at my company and so we've distilled it down to truth, trust, and passion. And again, you know, those are high level sort of ideas. But doing those really well, each of those really well is sort of how you innovate at speed and at scale. And it's, you know, there's a lot in there, but like think of the child like playfulness and curiosity with a teenage rebelliousness with an old man's wisdom. That's a beautiful mindset setup. Thank you. Thank you Travis. Everybody want to take a short break from our episode to talk about a company that's very important to me and Could actually save your life or the life of someone that you love companies called fountain life And it's a company I started years ago with Tony Robbins and a group of very talented physicians You know most of us don't actually know what's going on inside our body.

7:31We're all optimists Until that day where you have a pain in your side You go to the physician and they burn into your room and they say listen I'm sorry to tell you this but you have this stage three or four going on and You know it didn't start that morning It probably was a problem that's been going on for some time But because we never look we don't find out so what we built at fountain life was the world's most advanced diagnostic centers we have four across the US today and we're building 20 around the world These centers give you a full body MRI, a brain, a brain vasculature, an AI -nabled coronary CT looking for soft plaque, dexascan, a grail blood cancer test, a full executive blood workup.

8:16It's the most advanced workup you'll ever receive. 150 gigabytes of data that then go to our AI's and our physicians to find any disease at the very beginning. when it's solvable. You're going to find out eventually. Might as well find out when you can take action. Fountain Life also has an entire side of therapeutics. We look around the world for the most advanced therapeutics that can add 10, 20 healthy years to your life. And we provide them to you at our centers. So if this is of interest to you, please go and check it out. Go to fountainlife .com, backslash, Peter. Here, when Tony and I wrote our New York Times bestseller, Life Force, we had 30 ,000 people reached out to us for fountain life memberships.

9:03If you go to fountainlife .com, backslashpeter, we'll put you to the top of the list. Really it's something that is, for me, one of the most important things I offer my entire family, the CEOs of my companies, my friends, it's a chance to really add decades onto our healthy life spans. Go to fountainlife .com, backslash, Peter. It's one of the most important things I can offer to you as one of my listeners. All right, let's go back to our episode. Jack Hitterey, my dear friend, one of our Peter's D's CEO of Sandbox, AQ. You have your chairman sitting right next to you? No pressure. No pressure, whatever.

9:39So, first of all, please explain AQ, but then what are large quantitative models and what role do you envision they'll play in the current evolution of AI? Well Peter, first of all I'm very happy to see that we still have humans on the panel instead of just AI's. So I think it's just another few - I mixed the AI in this panel. Okay, another few FII's which is going to be avatars up here. The mantra of AIO -Di is real. It's real. It's not just a phrase, it's happening right now, it's happening on several levels and certainly companies and countries that do not engage will die. But now the question is, okay, let's say we all agree on that, which AI, what AI, what kind of AI, what mix of AI?

10:24And the marketplace now is starting to offer more than just one slice of AI. And that's what's exciting. So we have, of course, large language models. Many people in this room are, and on this panel are involved in that, and making huge strides. And we're seeing AI now take on reasoning, and I'm sure Eric and others will also address that. But there's a whole other side of AI that has had less focus and that's quantitative AI. That's AI that's based on equations and data, quantitative data, numerical data. When we think about starting a biopharma industry in a country that never had a biopharma industry, that was really not even possible five or ten years ago.

11:04But now we can come to a country like KSA or other countries and say, hey, let's get that going, but it's not large language models that will win the day there. It's models that have been trained on biology, physics, chemistry, electrons, that kind of interaction. So quantitative, large quantitative models, LQMs, as complementary to LLMs, allow us to do that at scale and speed. And we do that on the same GPUs, we have Nvidia here on the panel, that LLMs use, but we tweak them in a very, very different way. We train it on a very, very different kind of data. The data doesn't come from the internet.

11:39The data does not come from downloading Wikipedia and Reddit and social media. Instead, we generate the data from the actual equations that govern our world. And this is now a whole new superpower for humans that we just never had before as a species. Until three years ago, it was not possible to calculate with any kind of accuracy how one molecule that's meant to be, for example, good for Alzheimer's or Parkinson's or brain cancer or pancreatic cancer, would fit, would lock into that receptor. Now, as of just 36 months ago, with the collaboration of many people in this room, actually, and on this panel, it is now possible.

12:19So LQMs are really about another key tool in the tool chest, complementing LLMs, sending alongside the many LLMs out there, but a core tool that LLMs will interact with going forward in the future. So you mentioned data. And one of the things that we talk about is the importance of data and how the world may be running out of data to train these. So how do you, how should leaders think about the proprietary data generation they have and retention as AI models become more commoditized? We all talked about Gen AI. Gen AI is a very real and big thing. But now let's talk about Gen data, generative data.

13:03How do you generate data? Well, when you want big data sets that govern our world of either quantitative finance to look at portfolio optimization or again, a new material to build a car that will be lightweight, make the car lighter weight so it's more fuel efficient, we can't turn to the internet for that data. That is not where we're going to get it. Instead, we generate the data from these equations. Those become interesting. Heisenberg, Schrodinger. Yeah, exactly. That's where quantum comes in. When people hear the word quantum, I know people get scared, sorry, but quantum is not just about quantum computers.

13:38It's about today on GPUs from alphabet, TPU from alphabet, GPU from Nvidia, and others. There's many others coming out. We're able to run the quantum equations. that is the equations that actually govern our world at scale on these GPUs and TPUs. This is new. These chips, by the way, were never designed to do this in the first place, and it's the human ingenuity that is quite fascinating that came up with this. You know, you did an incredible job spinning sandbox AQ, AIs for AIQs for quantum. I'm just, if you remember that, out of X at Google. And you have real products today. Can you just very quickly give us a sense of what sandbox products are that you're sure?

14:25Sure. I'll give some actual real case studies here. At FII, we have, I think, Paul Hudson, the CEO of Sinoffi, one of the largest pharma companies in the world. And our two companies actually are announcing just today. We were just on CNBC earlier announcing that we're working together to apply this IQ, this PI, this LQM, this quantitative AI, to accelerating biomarker development, that is development of diagnostics that will help all of us and drugs as well. So that's a real world case study of how we're using it there. We're also working with companies like Dow and others on the chemical side to say, how do we get new catalysts that could bring us new materials?

15:03When we think about the hydrocarbon space, think about the output of a refinery. And we say, okay, they high -octane fuels, very profitable, jet fuels, kerosene, profitable, NAFTA. But how about the bottom of the stack Peter? That bottom of the stack petroleum companies don't make much money on. It's sold to smelters and others and burned in the air. And so we think about what we can do with AI that understands chemistry. We can now take the bottom of the refinery stack, up -value it to things like carbon composites, carbon composites are what make a McLaren car so powerful and yet so light, Asyn Martin Ferrari and others, but it's not accessible technology to all cars.

15:45By working with the hydrocarbon producers we can say how do we now make this kind of technology available on a democratized basis? So these are real world impacts, be it in biopharma, in chemicals, in fuel, and energy, and Elon was talking about energy and energy storage, the battery technology we have today, Peter, is 45 years old. And we need to leapfrog that and this kind of AI, complementing LLMs, this is where it's going to come from. Let's go to your chairman next. Can we thank Ruth for spinning Sandbox out? Thank you, Ruth. Good job, Ruth. And what a financial success so far. Absolutely.

16:22It's been amazing. I've never seen a company scale revenue as quickly as you have. Thank you. extraordinary. Dr. Eric Schmidt, former CEO and chairman of Google and Alphabet, there's nobody on the planet that I think holds your statue in this field. Thank you for all that you've done. The path to AGI, we talk about AGI, it's this blurry line of what is AGI. So do you have a definition for it? And why is it so exciting? Why is, you know, Sam saying I'll spend $50 billion, whatever will take. Talk about that, please. It's worth understanding what will happen in the next five years. Please. And the work that these guys highlighted and others on the panel will highlight are going to generate savants, that is specialized assistance that will work with you in whatever you do.

17:15An artist's savant, a music's savant, a physics's savant, and so forth. Those savants will work with you to do research, drugs, drug discovery, solve problems, can do many, many things. Why five years? Because today we have all the components necessary. We have planning. We have the ability to do a forward and backward reasoning. We can do stepwise reasoning. We can go against objective functions that are much more complicated than they used to before. And we can generate arbitrary code. In the industry, it is believed that somewhere around five years, no one knows exactly, the systems will begin to be able to write their own code.

17:57That is, they literally will take their code and make it better. And of course, that's recursive. I thought that is essentially a change in slope. If you're going like this, all of a sudden it goes like that. It's reasonable to expect that within six to eight years from now, so 2030, right after that, maybe 2032. under current growth rate, it will be possible to have a single system that is 80 or 90 % of the ability of the expert in every field. So 90 % of the best physicists, 90 % of the best chemists, 90 % of the best artists. When you have such a thing, you have a non -human that is effectively smarter than any human because no human can dominate all of those fields, maybe Leonardo da Vinci could, but certainly not now.

18:44We don't know what happens when such a thing exists, but we know that that race is really important. There are many, many things that this thing, we don't know what to call it except an AGI, could do. For example, it could analyze cyber threats and develop new ones or it could protect against them. You could come up with new biological solutions, good ones or bad ones. So there's both a national security component and a worry, but also a notion of a huge step change in human efficiency and productivity. I will assert that we as humans are not ready for the arrival of this. We're just not ready for it.

19:19I can imagine all future Nobel Prizes and Math, Physics, Chemistry, Medicine coming from AIS. And I should say by the way that if you go to Formula One, you enjoy watching the humans drive around the track. Now it's obvious that automated cars, laymo cars and so forth could drive faster, but we wouldn't find that an interesting sport. So here we are in the land of golf, maybe there will be a robotic golfer that will beat all the lift -hop golfers, but we won't look at the robot, we'll look at the humans. So we poor humans will take pity on ourselves. We're very biased, aren't we? That will be how we choose to entertain ourselves.

19:55Very briefly, but this takes an hour worth of conversation. What do you consider the most dangerous outcome around AGI or artificial superintelligence? There's a huge issue around proliferation and Right now we don't fully understand the rate of proliferation of the mid -tier models and open source models There's a consensus at the moment that models that cost less than a hundred million dollars to train are probably not that dangerous And ones that cost more than a hundred million dollars are more dangerous I have no idea why we believe that but that's the number So what will happen is at some point there will be proliferation of inexpensive tools that can do significant damage the most obvious one is in biology.

20:36Yeah. Thank you. Something you know a lot about. And I do think that we're going to see extension of the human health span because of AI. We live longer but it will be more dangerous in some situations. Hopefully we can moderate that. Did you see the movie Oppenheimer? If you did, did you know that besides building the atomic bomb at Los Alamos National Labs, that they spent billions on bio -defense weapons, the ability to accurately detect viruses and microbes by reading their RNA? Well, a company called Viome exclusively licensed the technology from Los Alamos Labs to build a platform that can measure your microbiome in the RNA in your blood.

21:18Now, Viome has a product that I've personally used for years called full body intelligence, which collects a few drops of your blood, spit and stool, and can tell you so much about your health. They've tested over 700 ,000 individuals and used their AI models to deliver members' critical health guidance, like what foods you should eat, what foods you shouldn't eat, as well as your supplements and probiotics, your biological age, and other deep health insights. And the results of the recommendations are nothing short of stellar. As reported in the American Journal of Lifestyle Medicine after just six months of following Viom's recommendations, members reported the following, a 36 % reduction in depression, a 40 % reduction in anxiety, a 30 % reduction in diabetes, and a 48 % reduction in IBS.

22:07Listen, I've been using Viom for three years. I know that my oral and gut health is one of my highest priorities. Best of all, Viome is affordable, which is part of my mission to democratize health. If you want to join me on this journey, go to Viome .com slash Peter. I've asked Naveen Jane, a friend of mine, who's the founder and CEO of Viome to give my listeners a special discount. You'll find it at Viome .com slash Peter. Ruth, a pleasure. Ruth is a present and CIO of alphabet and Google, you're a matter. this morning, I want to quote this and then ask you about it. We've all witnessed companies making grand AI for good pronouncements, for sure.

22:50But when push comes to shove and financial performance dictates decision -making, often less lofty ideals are what shareholders provide demand. So how do you think, you know, I think the world of Google, I think Google has transformed the world in extraordinary ways. How do you think of AI for good versus AI for financial gain in the position you're in and Google as a company? I think of it as a false choice because the upside from AI is absolutely extraordinary. But if we don't invest to protect on the downside, we'll never have the opportunity to actually invest to capture the upside. And that upside down side point is two sides of the same So when you think about the upside, it's around accelerating science.

23:39It's around social issues, solving things in education, health care, as we've been talking about. It's the economic upside. But if there's not a responsible foundation, if we're not doing the heavy work, we don't have a right to have a seat at that table. And that means engaging with regulators constructively. It means investing in our systems internally so that you're protecting from the downside. If you don't protect on the downside, you're going to find resistance, whether it's from the regulatory world or from everybody else. And so they go hand in hand and to assume that you can pursue one without the guardrails that are critical.

24:12I don't think it's long term sustainable. And so we view them as two interlinked approaches to really maximizing the upside of this extraordinary technology. You've managed through a multitude of ups and downs in the economy, including the 2008 financial crisis. is what's important for business leaders here to know about leading their teams through the incredible changes we're about to see. And do you think people realize how much change we're about to see in business and industries and society over the next five years? I think the most important point to take away from all these conversations is that the art of the possible is fundamentally changed.

24:54This is a generational opportunity like we haven't seen before. And I spoke about some of the key proof points in the earlier discussion this morning, probably one really important one is in life science and so proud of our colleagues on the Nobel Prize for this with Alpha Fold credited with being the most important contribution to drug discovery. Relevant to your question, Demis Asabba, is the founder of DeepMind, one who went on this journey to create Alpha Fold. when he embarked on it, he said, many people said, how is this possible? And his answer was, why not? And so we kept going. And I think the other really important point when you think about this, that I talked about some of the language translation work we're doing.

25:38We now translate in 260 languages. The important point is that we added 110 languages in the last six months. I'm doing 500 million. 500 million people on the planet. So it's a vertical lift. What that says is you better not delay. You better move right away. It's already been set on this panel. I 100 % agree and the economic upside is profound. So I would say the two most important, you know, there are many important messages, but one of them is the time is now. You have to reimagine what is possible because it really is. And we're seeing it already today. We're seeing it in the manufacturing sector.

26:11We're seeing it in education. We're seeing it in so many different areas. In fact, very importantly, on this point about language translation. I was recently with the Minister of Digital Transformation, a country in West Africa who said more than 50 % of their population is under the age of 19. They knew that the most important thing they could do, we've already heard comments about education today, the most important thing to do is education. How can you have a country with more than 50 % under the age of 19 and not solve that, but they didn't have the teachers to do so. And what's exciting with AI is they can now actually provide education, quality education, to the entire population.

26:51And very importantly, in many countries, as in this one, in many of our countries, multiple languages are spoken. And before AI translate, you had to learn French or English in order to get the math books. Now you can learn it in your language. And so to me, when you think about the impact on humanity, it is incredibly inspiring. My dad always said when I was growing up, education is your passport for freedom, it is your passport for life. This is transformative. So one, get on the program right away, and the second really important point is what Demis said, which is, why not? You have to radically reimagine what is possible, how you interact with customers, every element of process, risk management, the way to solve healthcare issues, education issues, climate change issues, but the time is now.

27:38It's an, and it's near infinite opportunity, isn't it? Every industry will be transformed. Re -imagined the impossible, re -imagined the possible. Thank you. Thank you. Ben Harowitz, co -founder and general partner of A16z. Man, well, man, you guys have been on fire in the AI universe. So I'd love to hear your thinking as a leading thought investor. Where is the value going to accrue in this incredible value chain from chips and power and real estate and large models and applications? are they all equally important to invest in? Yeah, so I think as people have been saying, it's such a gigantic market.