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

Episode Date: April 20, 2023

In this Ask Me Anything session during this year’s Abundance360 summit, Andrew, Emad, Alexandr, and Peter discuss how the world will change post-A.I explosion,  including how to reinvent your busin...ess, your skills, and more.  You will learn about: 03:39 | How Do We Educate On New Technologies In Our Changing World? 15:22 | Is There Any Industry That AI Will Never Disrupt? 28:27 | Will The First Trillionaire Be Born From The Power Of AI? Emad Mostaque is the Founder and CEO of Stability AI, the company behind Stable Diffusion. Alexandr Wang is the world’s youngest self-made billionaire at 24 and is the Founder and CEO of Scale AI. Andrew Ng is the Founder of DeepLearning.AI and the Founder & CEO of Landing AI.  > Try out Stable Diffusion > Visit Scale AI > Learn AI with DeepLearning.AI _____________ I only endorse products and services I personally use. To see what they are,  please support this podcast by checking out our sponsor:  Use my code MOONSHOTS for 25% off your first month's supply of Seed's DS-01® Daily Synbiotic: seed.com/moonshots Levels: Real-time feedback on how diet impacts your health. levels.link/peter  _____________ I send weekly emails with the latest insights and trends on today’s and tomorrow’s exponential technologies. Stay ahead of the curve, and sign up now:  Tech Blog Join me on a 5-Star Platinum Longevity Trip at Abundance Platinum _____________ Connect With Peter: Twitter Instagram Youtube Moonshots and Mindsets Learn more about your ad choices. Visit megaphone.fm/adchoices

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Starting point is 00:00:57 Tennessee sounds perfect. We're all going to have some version of Jarvis, right? An AI that is in your ear, on your body, and so forth. 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 it can analyze information faster than any person. We're just literally starting to explore these. All of us are engaged with governments.
Starting point is 00:01:33 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 it's a contest. School should not be a contest. You will never not be without this AI as you grow up.
Starting point is 00:02:04 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
Starting point is 00:02:24 in which we uplift everybody, which is what this technology has the ability to do. Everybody, this year at Abundance360, 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 Moustak, 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 Ang, the managing partner at AI Fund.
Starting point is 00:03:13 He's co-founder and chairman of Coursera, the founder of Google Brain. I 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?
Starting point is 00:03:35 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
Starting point is 00:04:05 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,
Starting point is 00:04:53 the knowledge, and the reskilling that needs to happen to approach this current world. 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. And 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 to ask. Who wants to take that on? You know, so it's a very important point.
Starting point is 00:05:25 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 I started, co-founded Coursera, which to this day offers a lot of courses,
Starting point is 00:05:43 often works with governments to train up different people. I think that one nice thing is with online education, with digital education, we can speed up the rate at which we help people learn the new technologies and figure out what to do with it as well. And I think media also has a huge important role to play. And eventually, I would love if we can build tools. Like if you look at Google, the UI is really simple.
Starting point is 00:06:07 The background is insanely complicated. You just type what you want and 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 the generative AI tools are headed in that direction.
Starting point is 00:06:22 Yeah, I think it's super natural. I mean, that's why super, space natural. Like, ChatGPT was so successful because you just type and it just came. Stable diffusion, you just type and then have images, right? And so I think making these things more and more usable has led to the explosion
Starting point is 00:06:36 because it kind of comes from the natural understanding of humanity itself. It's trained on these large corpses 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
Starting point is 00:06:51 right now. By the way, the most linear organizations on the planet, if not sublinear. They are. And again, the typical approach to this is regret minimax. Stop it. Ban it. But it's inevitable now. And again, it's kind of a is regret minimax, like stop it, ban it. But it's inevitable now. And again, it's kind of a global phenomenon.
Starting point is 00:07:12 One of the problems as well is that 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.
Starting point is 00:07:43 Michael, good to see you. You're next, pal. So this is probably a question more to Ahmad, but anybody's perspective is welcome. I have 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 are using English language, we're using prompts, so definition of what you're asking for is a lot more vague. So when it's vague, it may have
Starting point is 00:08:14 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, structurally 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
Starting point is 00:08:50 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
Starting point is 00:09:07 and things like that or GPT-4, it will write the program based on the comments. 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. Again, it's gone so fast. We've got the surface level. We have to explore.
Starting point is 00:09:23 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. Everybody, I want to take a quick break from our episode and tell you about a health product that I love and that I use every day.
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Starting point is 00:10:59 We're going to zoom next. Ned Alsikafi. Ned, where are you on the planet, and what's your question? Hi, guys. Can you hear me okay? Yes, we can hear you great. Perfect. I'm from Chicago. I am in health care, and I love the idea of health care 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
Starting point is 00:11:25 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, you 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
Starting point is 00:12:26 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 just say real quick if you have a concrete idea for what you'd like to do in neurology let me know you know i think teams could help maybe my team could help execute that and one example something ai funded we worked with a fantastic founder allison darcy and now different different CEO, Michael Evers, to support building up Wobot, which is a digital mental health care chatbot. You can actually install it on your phone that, you know, from the data published at the Stanford, seems to be able to take effect relatively quickly in terms of treating symptoms of, for users of symptoms of anxiety and depression.
Starting point is 00:13:23 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, you know, getting to market first is actually an advantage.
Starting point is 00:13:40 You know, certainly other people can copy the idea, but I think, you know, 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. 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 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,
Starting point is 00:14:22 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'll 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.
Starting point is 00:14:35 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'm a medium to small business owner. I'm a physician. I own a diagnostic laboratory.
Starting point is 00:14:47 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 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 and 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
Starting point is 00:15:14 I think is a very concrete, 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 and move your company? Alex, I think you're moving. 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. Um, 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 it into a data set that you can train a new model on top of. Um, you can,
Starting point is 00:16:01 uh, 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. And you find out who that data is viable to, ultimately. We're going to go to Slido. There's a great question here I'm going to send 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?
Starting point is 00:16:33 It's an interesting question, right? It's like the question asked of Bezos. What will change? There's nothing that will never be able to be disrupted because you'll have autonomous robot agents that basically is Blade Runner, right? In the strange world 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
Starting point is 00:17:03 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 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 go into the, I go into Emod's category here, but that's my opinion. You guys are excellent. Andrew? You know, my friends and I, some of my AI tech friends and I, we used to challenge
Starting point is 00:17:46 each other, name an industry that AI will not be able to disrupt. We challenged each other to name that, and I had a hard time coming with them until one day I thought, all right, maybe hairdressing industry. Which industry? Hairdressing. I think that's easy. And I used to say
Starting point is 00:18:02 this on stage until one day, one of my friends who's a robotics professor, she was in the audience when I said that on stage until one day one of my friends was a robotics professor she was in the audience when I said that on stage and Afterward, she stood up she pointed at my head and she said Andrew for most people's hair cells I don't have the bit of robot to cut the hair like that, but your head size That's great, all right, we're gonna go to Kieran and Mike for Oh, that's great. All right, we're going to go to Kieran on mic four.
Starting point is 00:18:29 Do you think with the large language models like GPT, will they ever be able to explain why they generated what they generated or create 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 correlated 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
Starting point is 00:19:07 is that our emotional brain is an elephant and our rational brain 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 it'll come up with something on the spot to try to explain it um you know this is something that amad and i were actually just talking about is like how do you get greater levels of interpretability how do you how do we do research in the direction of like 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 um so um given So, given what has happened to social media, I actually rated the way I feel about AI as
Starting point is 00:19:49 scared shitless. Because you guys, you know, 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 you met about someone calling you and within your mother's voice and selling you stock 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.
Starting point is 00:20:32 We bank contentauthenticity.org, which is an 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,
Starting point is 00:20:53 there's an invisible walkmark and 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 live in a world of porous borders, data flows. So Giselle, we're going to have a lot of these
Starting point is 00:21:20 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. 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 the resilience because there's a huge risk on an earthquake as well as like Mount Fuji erosions.
Starting point is 00:22:09 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, this horrible thing to happen to to a region in a country um and you're able to one of the things that um is really unfortunate in any sort of disaster situation is that uh you know seconds really matter you know every second spent that you aren't you know deploying resources to
Starting point is 00:22:42 help resolve one of the you know uh of the people who are in a damaged structure or tackle a certain area is going to result in either lives lost or further damage to the infrastructure. So one of the things that you can do with a combination of satellite imagery plus drone imagery in major cities or major areas that are being impacted
Starting point is 00:23:02 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
Starting point is 00:23:23 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 will be used in that toolkit. Yeah, amazing. All right, to our Zoom audience, we're going to you next, Nico. Nico Dranik, where are you on the planet?
Starting point is 00:23:42 And what is your question? Hi, Peter. I'm calling in from Austria, from Europe. Beautiful. And I have a question regarding the profile of a chief AI officer. So what private profile should this AI officer have to fulfill this for best? Should it be technical? Should it be another profession?
Starting point is 00:24:02 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 well in my case. Thank you. Nico, great question.
Starting point is 00:24:16 Let me preface in a second. 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?
Starting point is 00:24:43 And what would be your, you know, what do you think that person should have as background? 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, but so 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
Starting point is 00:25:12 business-oriented enough to work cross-functionally to figure out what are the valuable business use cases for your specific application. But I have a multi-page article on HPR. 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 eye 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.
Starting point is 00:25:38 Does that sound like a reasonable role in a company? Yeah, I think it would be technical enough to make good judgments and then also to make the, you know, 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
Starting point is 00:25:55 as well as the ability to figure out, understand the business well enough to figure out the use cases. Imad, 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
Starting point is 00:26:09 key, because 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
Starting point is 00:26:25 AI officers here. So they can keep in 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.
Starting point is 00:26:40 And thank you. Some great questions. Katie, I didn't I apologize. I didn't note i apologize i didn't uh note your your your name earlier um actually what is the first step companies can take to evaluate the data they have uh how can we get started extracting uh 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,
Starting point is 00:27:14 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. By the way, it's 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. Well, soon images as well. Soon images, yeah.
Starting point is 00:27:37 Texted images, yeah. One point to cover, it turns out a lot of enterprises have what's called structured data, which means basically giant Excel spreadsheets. So structured data, you know, models like ChatGPT and so on are less directly well suited for, but text and images is getting really good. That's true. Yes.
Starting point is 00:27:56 Right now, general models are still worse at Excel than many of us. But yeah, so these are the data formats. You know, I would basically start the initial process, just 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.
Starting point is 00:28:17 I want to go to Christy's question on Slido here. I'm heading this towards you, Imad. If you had to put all of your money, your family's money, your friend's money, into one of the technologies here or industries, which one would you put it into?
Starting point is 00:28:34 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, and don't get an MBA. Go work.
Starting point is 00:28:51 The thing can get a 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 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
Starting point is 00:29:21 will have an edge over everyone else as i said it's first to market in the stock market itself There are no real investable things here at the moment. Are we gonna see the first trillionaires in this area? Most likely is This where the what grace 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 the GPU and then I had an asset here We're at the GPU era of this technology, but it's real, and we're going to get to ASIC, so it's going to be everywhere,
Starting point is 00:29:48 and it's going to create wealth faster than anything we've ever seen. I call it the dot AI bubble, actually, which is why I'm not joking. Like, you know, if you have funds that are focused on this, it's almost a rising tide where it lifts all boats. You know, even if you have the alpha side, that will come through.
Starting point is 00:30:02 Like, a trillion dollars will go into this. this like 20 billion went into delivery startups last year I told I think probably of six billions gone into this sector today a Hundred billions going to self-driving cars a trillion went into 5g. Yep. Just amazing anything here. That's investable You know far as I'm next I want to add one thing to what Iman said about jumping in. I think sometimes people think, am I too late? And the answer is you're not.
Starting point is 00:30:29 You're actually very early still. AI on, you know, don't have as exponential as some very rapid growth, but if you jump in now, I
Starting point is 00:30:36 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
Starting point is 00:30:42 it's still growing so rapidly. It's Bitcoin. It's literally $6 billion. 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? This episode is brought to you by Levels. One of the most important things that I do to try and maintain my peak vitality and longevity
Starting point is 00:30:56 is to monitor my blood glucose. More importantly, the foods that I eat and how they peak the glucose levels in my blood. Now, glucose is the fuel that powers your brain. It's really important. High prolonged levels of glucose, what's called hyperglycemia, leads to everything from heart disease to Alzheimer's to sexual dysfunction to diabetes and it's not good. The challenge is all of us are different. All of us respond to different foods in different ways. Like for me, if I eat bananas, it spikes my blood glucose. If I eat grapes, it doesn't. If I eat bread by itself, I get this prolonged spike in my blood glucose levels. But if I dip that bread in olive oil,
Starting point is 00:31:38 it blunts it. And these are things that I've learned from wearing a continuous glucose monitor and using the levels app so levels is a company that helps you in analyzing what's going on in your body it's continuous monitoring 24 7. i wear it all the time really helps me to stay on top of the food i eat remain conscious of the food that i eat and to understand which foods affect me based upon my physiology and my genetics. You know, on this podcast, I only recommend products and services that I use, that I use not only for myself, but my friends and my family, that I think are high quality and safe and really impact a person's life. So check it out, levels.link.com.
Starting point is 00:32:22 I'll give you two additional months of membership and it's something that I think everyone should be doing. Eventually this stuff is going to be in your body, on your body, part of our future of medicine today. It's a product that I think I'm going to be using for the years ahead and hope you'll consider as well. I've been sitting here and really blown away with all the great technology 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 I need to do. But what I'm, what I'm actually brought me up to, to the... How many folks are in real estate here? Raise your hand, please. Just get a sense. So you're not alone. Okay, thank you. But my main question 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?
Starting point is 00:33:17 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're here around the world. All right, we got your question. How do we save humanity?
Starting point is 00:33:55 That's an easy one, right? Thank you. Seriously. I mean, I mean, I'm odd. Please dive in because this is something you care deeply about. These are universal translators. Go to chat GPT, 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 a libertarian, and it'll do that.
Starting point is 00:34:13 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,
Starting point is 00:34:41 you're not going to want to throw your life away. A more peaceful world for us is a world in which you 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.
Starting point is 00:35:04 So again, this is the hope now 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 world view i'm going to ask a question and jump in here open ai's approach right now uh and you know and Elon 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?
Starting point is 00:35:45 Not tweeting this out? Well, I think one thing, I'll just speak for everyone. I think we all have to admire what OpenAI has done. You know, 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
Starting point is 00:36:09 large models if not for open ai and you know i think so far they've been very responsible in their deployment of the technology i think they've been very thoughtful they've they've invested a lot into research to to make sure that these models are deployed safely. And I think 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. I feel like the easy answer would be to say, oh, we need to be super concerned about ethics and 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 Imad released his model, which is fantastic, love what he did. I think that Imad 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 EMOD created massively more value than
Starting point is 00:37:05 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, you know, that 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 you know as alexander said amazing technology and it's been really a breakthrough that allows my humans to scale and they've been at the core of it um like i have disagreements with even ai uh my core one is just a case of now it's got to the
Starting point is 00:37:40 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 mid journey 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
Starting point is 00:38:18 could be existential and we will treat it as such we believe this technology i was surprised when i read that as well so 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.
Starting point is 00:38:36 Hey everybody, this is Peter. A quick break from the episode. I'm a firm believer that science and technology and how 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
Starting point is 00:38:52 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 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.
Starting point is 00:39:23 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 demandist.com backslash blog and learn more now 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.
Starting point is 00:39:55 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 ChatGPT 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.
Starting point is 00:40:22 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 ChatGP is amazing. I play with it, building multiple businesses using it. I have to admit, I'm not letting ChatGP tell me where to invest at this moment in time.
Starting point is 00:40:39 Maybe it gets much smarter. Well, I won't mind. Maybe it'll replace me and I'll retire, but not yet there. Maybe the reality is making an investment decision or a decision to build a business is so complex and so multifaceted. I don't know if we have the mechanisms to 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'll still take a while to get through the very complex multi-step reasoning that
Starting point is 00:41:09 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 years 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.
Starting point is 00:41:32 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.
Starting point is 00:41:54 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? You mind? You want to start? Yeah, you'll be able to use stable LLM and stable chat soon. Right now, probably it's going to be GPT-Neo, JNX on that side of things.
Starting point is 00:42:14 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. Is Clot available yet? PAUL LEWISOHNSKY- Privately available. IMAI LABOUREAUX- Privately available, yeah. So 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-NeoX and Plan T5, precisely.
Starting point is 00:42:37 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 GPT-4 chat service as well that you can fine-tune on. Yeah, Lama as well. I'd mention Lama, although... It's non-commercial, that's the problem.
Starting point is 00:42:57 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.
Starting point is 00:43:25 So I think you probably need to take one of these open source models of which Ahmad named a bunch, Lama's a new one from Meta, and a host of others, and train them up. While choosing the right LLM language model is important, I feel like one of the things that AI Fund would recommend to different companies, what language model to start building on top of. So these trade-offs between model size and cost,
Starting point is 00:43:46 and do you want to fine-tune, or do you do prompting, or do you consider 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. Hey, Peter. What's your question, buddy?
Starting point is 00:44:05 So I'm a kid, so I still go to school. over there. Hi, Bear. Hey, Peter. 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
Starting point is 00:44:19 and do their math. And I guess my question is, one, how do you think 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, that's a big question of question of transparency is a great question. Thank you for that. I feel like if you use chat GPT 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.
Starting point is 00:44:57 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, i can't tell you about it that's that's what doesn't feel very good and kind of these schools are struggling um the debate is people will be to use these tools in the future so we train them to use it or is it a crutch that will limit right a person's growth i have a controversial opinion so i have a four-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 add
Starting point is 00:45:29 with her own brain one of the challenges of chat gpt is you know most students using it are in an age where parents and teachers don't have an ability really to easily stop as used 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 child GV and educational system is something I see a lot of schools struggling with. I wish I had an answer. Cheating implies it's a contest.
Starting point is 00:46:00 Schools should not be a contest. Got it. So I think most schools are basically childcare systems mixed with status games. a contest. Schools should not be a contest. Got it. So I think most schools are basically childcare systems mixed with status games. I think schools should embrace this technology and they should really think, how can we impart knowledge into individuals?
Starting point is 00:46:16 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.
Starting point is 00:46:35 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.
Starting point is 00:46:59 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.
Starting point is 00:47:14 Take your question, answer it what you want. Yes to Python, yes to college. Yes to Python, yes to college. Okay. Creation of music and art. Music has had its stable diffusion moment. Audio LLM and others. You will have perfect music models by the end of the year.
Starting point is 00:47:32 Ellen's question again. Privacy in terms of healthcare. All right. I think this is 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?
Starting point is 00:47:54 I think it's a really big societal topic that we're all going to wrestle with over the next few years. And I encourage everyone to get involved if you have an opinion. I think also AI for healthcare has to be auditable and 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.
Starting point is 00:48:18 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. 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 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 U.S. versus China in our very next session.
Starting point is 00:48:44 I'm going to try and keep us on time. Let's give it up for these incredible individuals.

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