The Man Who Invented Prompt Engineering on AI, AGI & The Future of Humanoids w/ Richard Socher & Salim Ismail | EP #152

28:54And, you know, we consider material scientists heroes in our world. All right, Selim, what do you think about this one? Satya Nadella on Quantum Breakthroughs, quote, we believe this breakthrough will allow us to create a truly meaningful quantum computer, not in decades, but in years. I think this is... I think this is... No, Microsoft. Yeah. Yeah. I think this is beyond huge. I think as we get to this, we have to keep in mind the limitation of quantum computers. They're only good for certain classes of problems. So there's that limitation. But the fact that you can create stable environments is really something huge.

29:32I go back to Helmitz comment that the existence of quantum computing, the heart is in the world of the heart. Yeah, his comment that the exist it gets very kind of metaphysical very quickly because he said the existence of a quantum computer may be proof of a multiverse and your head kind of just breaks right then as I So Richard I love to get your take on this because you're The only way quantum computers can do all of the calculations as rapidly as they do is that they're borrowing resources from a near infinite number of universe, Jason universe. Yeah, we're doing the competition in parallel universes and bringing the answer back.

30:10Love it. Richard point, they're going to be pissed when they found that we're stealing resources. So there's that to think about as well. Hey, Richard, what's your view on all of this? I'm super excited. I think anything you can simulate any domain you can simulate, AI can solve pretty much every problem that domain. It's just the matter of time and whether humans want to put that effort in. So you can simulate, go, you can simulate chess. like so, chess is obviously solvable by an AI, because you can, no, AI can learn through two ways, right? Either imitation or exploration, aka, you know, supervised and fine tuning and supervised training or reinforcement learning.

30:46And so, when you can allow a simulation to just train and try billions and billions of things, it can get smarter over time. What quantum computers will enable us to do once we scale them up is to simulate much more in the physical reality. My favorite science influencers have been a Haustenfelder, put a little bit of a damper on this particular announcement, saying, oh, we'll see if they really can scale it. But I'm very excited. I'm excited that there are different ways of approaching that, like the trapped ions, the neutral atoms. It's interesting. You hear a lot of quantum scientists kind of diss the other approaches and think their approach is the best.

31:25And then comes like this total left field one of these topological qubits that no one had been working on. And I just love the fact that there's this energy. And that in some ways, we have companies that have such a massive monopoly in their space that they have all these extra resources to do 17 years of research before something comes out. Amazing. And it's honestly, thank you to Google and Microsoft for investing in this direction, because there was no immediate return. You know, we saw Hartmut Nevin's latest, remind me what his breakthrough was a few months ago. You know, it announced that the larger the number of qubits, the more stable it became.

32:12And Majorana. Is that pronounced as Mejorana one? I drew on that. Yeah. Yeah. Incredible. It was about 13 years ago I had my two kids, my two boys, and I remember at that moment in time I made a decision to double down on my health. Without question, I wanted to see their kids, their grandkids, and really, you know, during this extraordinary time where the space frontier and AI and crypto is all exploding, it was like the most exciting time ever to be alive. And I made a decision to double down on my health. And I've done that in three key areas. The first is going every year for a found upload.

32:54You know, a found is one of the most advanced diagnostics in therapeutics companies. I go there, upload myself, digitize myself about 200 gigabytes of data that the AI system is able to look at, to catch disease at inception. You know, look for any cardiovascular and cancer or neurodegenerative disease, any metabolic disease. These things are all going on all the time and you can prevent them if you can find them at inception. So super important. So found is one of my keys. I make it available to the CEOs of all my companies, my family members, because I help this in you wealth. But beyond that, we are a collection of 40 trillion human cells and another 100 trillion bacterial cells, fungi, a viarite.

33:40And we don't understand how that impacts us. And so I use a company in a product called Viome. And Viome has a technology called Metatranscriptomics. He was actually developed in New Mexico at the same place where the nuclear bomb was developed as a biodefense weapon. And their technology is able to help you understand what's going on in your body to understand and which bacteria are producing which proteins, and as a consequence of that, what foods are your super foods that are best feed -a -eat? Or what food should you avoid? What's going on in your oral microbiome? So I use their testing to understand my foods, understand my medicines, understand my supplements, and viome really helps me understand from a biological and data standpoint, what's best for me?

34:35And then finally, feeling good, being intelligent, moving well is critical, but looking good. When you look yourself in the mirror, saying, I feel great about life is so important. And so a product I use every day twice a day is called one skin, developed by four incredible PhD women that found this 10 amino acid peptide that's able to zap senile cells in your skin and really help you stay youthful in your look and appearance. So for me, these are three technologies I love, and I use all the time. I'll have my team link to those in the show notes down below. Please check them out. Anyway, I hope you enjoyed that now back to the episode.

35:19All right, let's go on to our next topic here. So Microsoft dropped some AI data center leases. So, cancelation of US data center leases raised concerns about AI infrastructure, over capacity and shifting partnerships, move sparked industry reactions with European energy stocks. So there's been a lot of build -out. This ties directly to energy as well. I keep on hearing and Richard, I'm curious and it's a mere point of view that there's an open checkbook for building out capacity and building out energy. We're seeing small modular reactors, SMRs, this is fourth generation nuclear setting up next to these.

36:06To these we're seeing, I mean, I don't get to politics here, but Trump is like drill baby drill. You know, it's like we need as much energy as we can in the US to support this industry. Are we are we over building or are we not even close? I believe we're over building. You can't over building. Yeah, I believe we're I tell you why. Because we're you know you look at say deep seek and the massive breakthrough for much smaller cost right the incremental effort to create the next generation is dropping 10x every time we go through this. And therefore, we should get to a point where training can be done very inexpensively, and then you've spent a lot more time on inference.

36:55And therefore, the amount of buildout is exaggerated, because it's aiming at the time, aiming for a model or size of model that was there six months ago when you started the building. And that will not be the case when you finish the building. So that demodidization aspect of it, I don't think is being taken into account, They're building for the capacity. They think they'll need given the projections without realizing that those projections will be wrong That's my that's my general complaint Richard you may have some more specific Mostly disagree. I mostly disagree. I think I've been talking yeah I've been talking for over a year and a lot of other folks have recently picked it up about Jevon's paradox right when we make things more efficient.

37:40We actually will use more of that resource. And I think we're seeing that play out with intelligence. And so we'll just use intelligence in one more places. Everyone will have a personal assistant, a personal health team, a personal tutor, and we'll just use all of that on top of that. There's sort of so many things on the eye and I can talk about that for every but a lot of human problems are related to not enough energy. So even like when people say, oh, there's a shortage of water. There's obviously no shortage of water Just happens to have to more salt in it, which is an energy problem, right?

38:10So all these water fights that are going on is like well if you have more energy just De -salinate ocean water and problem salt, right? You can like there's all these deserts that you can't live in right now because there's not enough water Well enough energy that those problems go away too So my hunch is we're gonna find a lot of uses for that energy now where I do agree with you on that one small bit is When you build a lot of data centers, you also need to have data that actually goes into those data centers. And you don't want to have like a real estate crisis where you build a lot of buildings, but people don't move into them.

38:38And so I do think, you know, I have some ideas on how to fix that, but my hunch is data will increase, energy needs will increase, and intelligence will get cheaper and cheaper, but we'll still just use more of it everywhere. So let me distinguish between energy needs of which I think we need lots of energy, right? And specifically data centers, which apply that energy in a particular way, I think we need less than people think of that, but we definitely will use all the energy we can for desalination of the things. So yeah, we're kind of just generally coming to agreement there. Before we get into thinking machines here in this article from TechCrunch about mirrors and you start up, I am curious.

39:15I mean, over the last year we've seen this constant flow of the leadership of OpenAI out of OpenAI, which is concerning. I mean, I mean, I'm not an investor in OpenAI. If I were, I'd be very concerned. What do you think is going on there? I'm curious. Open question, either of you guys. I think the doors are very open. I think that the basic general thing is if you get to that level and you're suddenly the hottest property executives or deep researchers in OpenAI, you can essentially go follow your passion and go find your MTP and go build something with the mirrors doing what she's doing or any of the other rafter people.

39:58Some may be interested in healthcare and the specific application there. And they can now have the currency to go do that. I think a lot of it has to do with that. And a secondary layer of the speed and move fast and break things, a process Sam has for how to build stuff that is concerning a lot of people. Then you have the third class of people kind of really nervous that we're moving this quickly without adequate wisdom and thought as to what we're building here. And I'd be curious, which would just be where your action is towards the emphasis on those two or three different areas. I think at a very high level, zooming out a little bit, the fact that California has non -compeats and the rest of the US is actually moving towards that, or like doesn't have non -compeats.

40:41As in non -compeats are not enforceable in California, is tough for companies very often research cost a lot of money, but once you show the world that something is possible at all, it's much, much cheaper to copy it. And it's also much easier to knowing how you've done in one place, go and take that knowledge without taking any code, but it's stuff in your head, and then go do it cheaper somewhere else. And honestly, it's sort of overall for the ecosystem, it's a positive thing where we're just going to see cheaper, better, faster models. So let's talk about thinking machines. Any clue about what Mira is going to focus on?

41:17So I guess lots of smart people joined her, John Schruelman, who let the ChatcheeBT application of the LMS, you know, that had been available as APIs before. We had already incorporated them before ChatcheeV come out inside you .com in a search engine like Context. And so having some amazing folks that really understand the technology and also have ideas for building products is probably a very positive thing. and I mean, she describes and they describe a lot on their website. My hunches, they're going to try to explore. I hope they don't just build another LM. I think there's so much more stuff out there, but yeah, we'll see.

41:56When I find fascinating and I'm, Suleon, I'm curious about your point of view here is, I think her starting valuation is $30 billion. $10 million. I mean, everything's gone up. Everything's gone up. Yeah, it used to be millions of dollars and not billions of dollars. I don't know how quickly you can just for our amount has this stuff. I think we're headed for a pretty big bubble on as we get to the application side of this. Because when you get to the end user, it's demonetizing so quickly that where's the revenue will be the big question over time. I think putting my investor head at AIX Ventures on for a little bit.

42:38The way we think of this is that it's essentially seed stage risk combined with late stage returns. And so as an investor that affected value just doesn't quite work out, but it doesn't mean that no one will succeed. It's just seed stage risk. Once in a while, every no 5 % or 10 % of seed stage companies actually do something amazing. And like one or two of those in the power laws and investor really blow out and return the entire fun multiple times. And so there are a few such possibilities, but man, yeah, it's really tough and the bar is so high to be able to get enough revenue to eventually be able to justify these high valuations.

43:15So can I just riff off that for a second, Richard, when you're kind of trying to invest in AI startups, right, you've got to figure out, A, does the founder or the team have something really magical. And B, can they get to market and can they find product market fit? And that's a big, big challenge today. How do you guys assess that? Can they do their revenue? Can they get revenue? Yeah. And what do you invest in stuff that has massive breakthrough and has the potential and you'll hope that the potential yields? Where do you put your chips on that? Yeah, so we've been doing really well fund ones already like five X TVPI and it's only like four years old or so.

43:59And so we're looking at the sort of two ways to slice and dice it. One is there's a horizontal new infrastructure layer, right? And in that you have companies like Huggingface, I was very fortunate there are my students when I was a professor at Stanford, invested at a 5 million valuation round, they're going to have billion now. So there's there are a few of those that can break out and really become part of this new stack of building software that is fundamentally different with AI and cursor similar one or investor in combium to the cursor CEO is actually an internal mine and I'm really bummed I didn't get to invest in that one.

44:35And so then there are thousands of application companies vertically that sitting on top of that are sitting on top of this new stack. And so there we look for deep industry insights and DPI expertise, like teams that actually understand my buyer will want this feature and they don't just sort of go off and try a bunch of different things and spend a lot of money on it. Our proprietary data sets, something that you look for, find exciting and all of this. The best companies will have what I call virtues data cycles, at least, if they don't have a direct data access already, they're building a product that as you use the product, you collect more data.

45:11One of the reasons why Tesla is much better suited and why we've seen a lot of self -driving car startups die is that they have to pay for every mile driven by a human to collect data versus if Tesla, we all drive the car and we give the data for free and we actually pay it to drive the car to collect that data. That is a perfect example of a virtuous data cycle. When you see that in very SaaS software, at g .com, people give us feedback of like this was a good answer. This wasn't a good answer. I didn't like this part and so on. And so those are sort of ways where you can Build some kind of advantage over time So I get two out of the two things out of this one Elon owes us money and number two To be really successful in AI be Richards intern at software I love that's right there All right guys that was fun And I think the other side of AI is one of my favorite topics.

46:05It's humanoid robots I was building robots when I was in junior high school But they didn't do what the robots today do. So I'm gonna share a short video here. This is a robot called clone I contacted the CEO and he's gonna be bringing his robots to the abundant summit next year, but let's check out a little bit of a video here

46:34So what clone is doing is basically creating which that westworld. So these are muscles, they're hydraulic systems, and that video is under representing what it can do in terms of moving the hands. They hope to have it walking in the next few months. They're based in Eastern Europe where they're doing a lot of the work. But talk about an interesting future of robots where, I mean, a lot of the robots today out of the US and China are clunky work walkers, they do walk, but they don't have that human emotional, fluidic movement, but these might. It's interesting that they chose to work in that way.

47:21In a sense, brushless motors have kind of helped us do an amazing amount of cheaper prices and incredible capabilities in robotics. That's my first stop. The second one is, I think the black horse here is similar to Beechseek, is UniTree. UniTree has some insane videos. They look like CGI where you have four -legged robots that also have wheels, which I think is a clever idea. And so super fast, but also jump and climb up stuff and spin the wheels at the same time. That's the second, the third one is, yeah, I'm excited. And now the question is always like, what's the really most amazing use case for humanoid robots like a tractor factory where you just have a bunch of little lasers and thousands of arms and things like that.

48:06You wouldn't want a bunch of humanoid robots walk over a field similar to the dishwasher stuff we talked about earlier. At the same time, it's not a zero -sum game. There's a ton of cool stuff. I would totally buy a humanoid robot to have stuff be done in my house and just kind of clean and they can do it at night. So they don't have to be super fast. And now the fourth comment is I feel like everyone works on the AI version of our body. It's like the original Terminator. No one works on the T1000 and one of my many ideas is actually to build a T1000 like robot and I have a bunch of ideas I recently like gemped on with a really brilliant hardware hacker and he's like you know this could actually work and make sense.

48:44So project number five. Uh oh you heard it here folks. Jim Cameron was right and it's all going to be due to Richard Tarsher. I got to say something here. If you want a musculoskeletan, humanoid robot, you get a man and a woman and you have a baby and you grow the baby. I really struggle with this. We talked earlier, right? If you want a dishwasher, you have a machine that sprays water in particular way and it looks like a box and you have trays to put dishes in whatever. I was saying with a vacuum cleaner. why and to the point that Richard just made, it's so much more powerful to have wheels on the legs, et cetera, et cetera.

49:26Why are we constantly going back to the human form? We've had this hard drive. We've had this hard drive. We have, we've gone about this. You're just wrong. I think driving nuts, you're just wrong. It's wrong. Richard, the argument we've had is I kind of say, if you're going to build a robot, have one with seven arms that can do many more things. Why make it look like a human? Well, and because it's cool. Oh, yeah. So I am an investor in McKinnell apps, too. They built these massive arms, and they can form sheet metal, and they work with SpaceX, and bunch of folks. Whenever you don't want to build an entire factory to make that same large piece of metal millions at times, but you need it 200 times.

50:05They're perfect for. They can literally ship a factory that creates any spare part into the field somewhere, and then just have almost like a blacksmith, but massive and AI. And they're also like, oh, anti -humanoid. Now, again, it's not a zero sum game, right? I think some people want like a beautiful humanoid -like robot in their house, but we can still have dishwashers and factory robots and so on that are very custom purpose and look crazy funky with 20 arms. And you know, that's the excitement for robotics. Doesn't have to be zero sum. All right, we have a lot of robot announcements this week.

50:39So let me continue on here. Next up is Neo's gamma. So, you know, listen, I think this looks pretty damn cool. I mean, this is, you know, in terms of its motions. Now, how stage this is and how practiced. You know, we don't see the 37 ,000 shots that went wrong. But that looks like a pretty friendly home robot. You know, one of the questions I ask everybody is, How many will you own? You know, I when I interviewed Elon and Brett adcock breads the CEO will see him in a minute CEO of a figure and of course Elon overseas Tesla and Tesla bought now called Optimus the projection is as many as 10 billion robots by 2040 and I can imagine that I have no problems imagining I would own You know two or three maybe ten So, Celine, no, not you.

51:39You know my struggle with this. I mean, one robot moving very quickly is the same as seven of them. And again, why does it have to look like a human being? It would be much better with wheels and seven arms. You could have the same thing. You could have the same thing. You could have the same thing. You could have the same thing. So, I struggle with that. I think I feel more comfortable having, you know, a humanoid robot walking around the house than some strange looking contraption. I think we're going to end up with the problem in the same way with virtual reality with the uncanny valley, where it's very disconcerting.

52:10I think we're going to have the same thing with humanoid robots. For sure. And like the sci -fi is underrated and showing us sometimes also the positive ways. People will fall in love with their robots and they'll have these androids. Now, I think with short -term, we're going to see a lot of folks just remote controlling a robot, collecting training data that way. And so there's going to be an unpart of the uncanny valley is you may have someone in India or somewhere sitting looking into your entire home being able to navigate everything seeing your kids opening your doors and everything and you kind of have to be okay with that invasion of privacy potentially, right?

52:48And then once you once they got good enough then you're right like they could be faster. I mean they could put on like wheels and like you know shoes with wheels on and you know and attach another arm if we really want them to, they can be more modular that way. So I'm excited for it. All right, so that was NeoGamma from OneX Tech. Let's go to the next robot here. And this is Figure AI. So just for disclosure, I'm an investor in Figure. I don't know if you are Richard. This is Brett Adcox Company, and they just announced their software. Interestingly enough, the figure used to have a software relationship or a Gen -AI relationship with OpenAI, and they shut that down, and they decided to build their own AI team internally and to build Helix.

53:44I think the logic there is, in the same way that Tesla got so much data from autopilot as we're driving it around that allowed them to create these incredible models, that figures AI, I really hope they come up with a separate name for it because calling the company figure and the robot figure gets a little bit confusing. But they're going to get a lot of data and that's going to train the AI in the physical universe. Let's take a look at at their video.

54:33So, Celine, instead of having four arms, you have two robots instead, and they collaborate. It's called collaboration. I think this is going to take a much longer time for people to work out than people realize. But it's fantastic to see the speed at which it's moving forward. Because if 10 years ago when we were first looking at robots, it was really hard to imagine they would get the stock of grandchildren. Yeah. Remember the government? It was so clunky and so I think so. So it's fantastic to see that. But the use cases and the application areas is where I think it'll be. You know, my roomba still cannot clean a room without me moving all the furniture around for it.

55:15So it's working for us hard. Yeah. And like Robotic says, done a phenomenal job if we can constrain the environment a little bit more. And that's why self -driving is also a fairly constrained environment where it's standardized in a lot of places. The highways all look the same. Things like that, road signs are standardizations. houses have very little standardization and you're right, it will be very very hard and the companies that are actually able to get through and get like one use case so nailed that is big enough and important enough for folks will be in a huge advantage but it is harder than most people think it'll be very capital intensive and then the question is can you be a fast follower out of China and just say oh this is how they do it now we reverse engineer it and then you can leap frog skip all the expensive research stage and that's right.

56:00And I'll go to my favorite use case, which is going to be a while before you get one of these human argrobots and say go change the baby's diaper. There's just so many things that can go wrong with that. Yes, I still love the, the, the, walk into the room and the, the robot is holding the, the baby by one foot. The funniest comment I saw on this figure video was this reminds me of two of my buddies being really stone and trying to load the lot that the end. That's perfect. I'm sorry, but I was scared with episodes around this. The doorbell is about to ring. It's my figure robot coming over there.

56:36I don't give you a hug. So answer it and be nice. All right. I can't help doing episode without Bitcoin. Let me begin the question to you, Richard. Are you a believer in Bitcoin? There's a faith component here. I say a believer. Are you a holder in Bitcoin? I have just a tiny bit here and there. I invested in a fund that does a lot of crypto things just to have a little bit of exposure, but I mostly want to focus on AI and find it a bit of a distraction, so I'm not really deep in it. Well, when focusing on AI, I mean, listen, AI's are going to need to have, and agents are going to need to have mechanisms for transacting financial aid.

57:15So, let's take it slightly sideways to cryptocurrencies for AI agents to do business amongst each other. What do you think about that? I mean, it makes sense, but they can also do that with credit cards. We'll have AI kind of made credit card purchases fairly quickly. I was a little bit dismayed when I actually tried to play around with the technology, and then it's just like the gas fees and so on. We're also pretty high. I'm like, wait, this is like a credit card fee almost. It's like already cost a lot of money. I'm like, this doesn't seem right. So I don't know, I feel like they need to really lower the prices so that the transactions themselves are insanely cheap.

57:57Yeah, there's a whole stack of, you know, you've got Bitcoin with very expensive transaction fees and proof of work to proof of stake. And as you get closer to the end use, where you need less security. So if I'm moving, if I'm storing jewelry in a bank vault, then you have a lot of security in, But you don't do that many transactions when it comes to a debit card. You can have much less security. The transactions are limited to like $50 each. And then for you can lower the security in exchange for the volume. I think that's the kind of thing we're going to see in the crypto world as well. How nervous do you get, Celine, when you see the price now at this very moment?

58:33It's... I'm actually... Yeah, so I'm really encouraged by what's happened here. So two things happened over the last few days. One was the bite, the bit bite, whatever bite bit hack, which was the biggest hack ever. And in previous years, this would have caused massive collapse in the crypto world, and it barely even noticed. So I think that's one that variant. And the second was the response from the exchange with the CEO going, we're going to get everybody made whole again very quickly, et cetera. gives me encouragement that there's robustness being built into the ecosystem, which gives people a lot of confidence going forward.

59:12I'm pretty excited about where this will go. The Trump meme coin did not help the crypto world at all. That's really unfortunate, but that's life you get when you ask for. You didn't buy it, did you? No, no, no, no, because you can see it's only going in one direction. So if you don't mind, you mentioned the the the the the buy bit billion dollar hack. Can you unpack it? Yeah. So what's happened was one cold wallet which stored a lot of Ethereum got hacked and suffered a massive withdrawal. Now the challenge here is that you want to if you're if you're the hacker, you want to move this into anonymous places and kind of to wash the transactions because crypto is fairly traceable.

59:59There's appeals to Ethereum, right up to Vitalik to say, can we just roll back the thing before the hack? And it'll just undo the hack, basically. So there's a call for that. But trying to wash all the currency out is going to be very, very tricky to do. And everybody's watching all these wallets where they're going very, very carefully to find out who it is. I don't know how you sustain this. I'll just repeat, I'm really encouraged by the response from Ben Zhao and the Bibet folks saying we're going to just navigate all this. We're going to keep everybody hold on the fact that they had enough backup to do this.

1:00:39In general, what we found in the crypto world is you want to not keep major wealth on centralized exchange for this exact reason. in my box, a lot of people lost a lot of money on early on. So you keep it offline and you do trading on these exchanges, but not storage of value. Yeah, I know, but every time I, you know, I use a treasure or a, what's the allegor, you know, sort of thumb drive wallet, but I pucker up every time I go and plug it into my computer. It's non -trivial, it's very tricky. And you know, this goes to that whole usability idea, right? where we, we, when you remember, you were comment about when a technology goes from deceptive to disruptive, the usability becomes much 10x, 100x better.

1:01:29So Steve Jobs made the smartphone usable and boom it took off. Coinbase made the purchasing of Bitcoin usable and very user friendly in that took off, but the rest equipped was still a hot mess. Anyway, the transg buy an NFT or trade in NFT knows how sticky it is or execute a smart contract. But you have to be like geek level 14 to be able to even touch that stuff. Yeah, I'm using Abra from my major holdings, but I still have again on Coinbase and a number of different places. But it turns out to be a significant amount of capital and you've got to be careful about it. That's right. I think the tricky bit is like, why credit cards work is that you're kind of insured.

1:02:07Like someone steals your credit card and you see a bunch of purchases. You can just tell them like, that was me. And then the bank will give you your money back. And part of the problem of the decentralization here is you decentralize also the risk, the security that you have to have and the liability that each user has for their own wallet. And then people are just not sophisticated enough to be able to deal with all the cyber security threats very often. You know, switching here to micro strategies now called strategy, Richard, Michael Seller was my roommate, Fraternity Brother at MIT, so we go way back.

1:02:45He is extraordinarily brilliant. And I was just with him in El Salvador. I was there speaking with Carlos Slim, Mike Seller, and Mark Andries and Ben Harwitz. And Mike gave a massively compelling 90 minute presentation to this room full of billionaire family offices. And every time I hear him, I'm like, OK, I mortgage my house, sell everything, buy Bitcoin. The guy is, you know, it's very dangerous to listen to Michael Frinnington. My friends like, yeah. It's compelling. You know, it's interesting though, that when I just point one thing out for those of you who are nervous about this fall, the equivalent is, you know, it's hoddle and buy on the dips, but I have to verify this, something I wonder if you know that if, if you try and buy into an out of, like sell out of and buy into Bitcoin, that's problematic that most of the gains, this is a memory, I wonder if it's true that most of the gains last year were made on like five trading days.

1:03:51Yeah, this is historically accurate. In any given year, Bitcoin accelerates at some point in the year and it's very, very few trading days that make up 80 % of the upside. the problem is you don't know which those five days are, right? And I've managed to spectacularly miss four out of the five of those. And so, and then you buy on the other side of it and it goes horribly wrong. So it's a very tricky thing that what I tell people is just buy as much of it as you can and close your eyes for 10 years. Yeah. If you can. Well, this is, you know, Michael made another move. He acquired another 20 ,000 Bitcoin for about two billion dollars.

1:04:33It's pretty extraordinary moves. I mean, I wish... In our opinion, it has a lot of incentives to give 90 -minute presentations to everyone. Yes. I'm on Bitcoin, yeah. He does, for sure. It's definitely... No, I think there's one other way to look at it. If you wanted to have somebody be the prime evangelist for technology, the articulation he brings that the table is hard to beat. And you could spend a lot of time trying to find a better one. It's incredible. He is amazing. Richard, open forum here. What's been the most amazing events, breakthroughs, technologies, companies that you've seen in the last few months?

1:05:17Oh, boy. We just covered quite a view. And I saw Agent Forrest. I did a podcast with your buddy and mine, Mark Benioff, Mark's amazing Agent Force 2 coming on strong. What do you think about the whole agentic world? I'm a huge fan. I think when you think about what kind, so essentially large language models can be thought of neural sequence models, right? They're very large neural networks. They can be trained on any kind of sequence of things and you can train in both with imitation and with exploration. And so when you think about what are other interesting sequences, you know, in 2019, we started 2018, we started on these large language models for protein sequences.

1:05:59So boom, you got biology. But then the very obvious sequences, the sequence of actions too. And so I'm very excited. We already have over 50 ,000 custom agents built on the U .Com platform by our users. You you can select which LMS you use. Give us examples of the agents that people would use. What are the top two? PTA. So for example, you're in marketing and you say, oh, every time, every two or three weeks, I get a huge PDF file with a bunch of new features and some website that describes a new feature that product engineering have been shipped. And then I'm tasked to write to email marketing campaigns for specific industries, tasked to write three LinkedIn messages.

1:06:41I have to go out in the web and compare these new features to the competition. So I don't say this is super novel. No one has it, even though other people have it. And so on. And what we've done is like we talked to these marketers and they say, oh, well, just describe that. Explain that very well to an agent on u .com. And the next week when a new thing comes in, like you just drag and drop that PDF and it just goes through all those steps. It writes the LinkedIn messages for you. It writes email campaigns for you. And you're just done. And then we have journalists who say, well, I need to like research a new thing.

1:07:15I want, I'm supposed to write an article about prostate cancer, like advances. Then I go to these 50 different sources. I read a bunch of research papers and then I put it together. Perfect use case, you know, this is like the kinds of sources you describe. Like use medical journals only. You can just say that in your prompt. You don't need like a special sort of feature of the switch in the UI UX. You just prompt it differently. You explain that and then it writes like more and more of that for you And then you just need to start comparing so we have journalists and chief editors and writers that Told us that tasks that used to take them multiple days and I'll take them like two three hours and they're done Maybe the last fun one that's relevant for you is we have venture capital firms that say well if I get a new data room I go through ten steps.

1:07:58I look at net dollar retention. I do cack LTV ratios blah blah blah And then you just describe that again and you drag and drop and hold data room into you .com and it just goes through those steps. So whenever it's like knowledge work, you can already automate a ton of it. You create an agent that says go out there and raise me a billion dollars of venture capital and go find the companies that are going to be unicorns and invest in those and then just send me the back account information. That's step two. from my description of a Gen TKI is white color job description. Yeah, they'll be epic.

1:08:36And then I think the next level will be they actually start taking actions for you. They start booking flights and things like that. Now the interesting bit is that just like if robotics like we're going to have an uncanny value or like just a trough of this disillusionment potentially because when I saw like this rabid R1 for instance and they in the demo they said, oh I want to book a flight with my four kids to London on these dates. And then boom, boom, boom, now it's done. And I'm like, no way that was real. Because you have so many details, right? Like this hotel, I wanted to be close to these kind of sites.

1:09:07I want to see. And then over time, you change, right? When I was a poor graduate student at Stanford, like on, like, less than minimum wage, I would have been willing to wait 10 hours for a layover in order to save $200. Now I spend thousands of dollars extra just to have a one, the stop like, or zero stop flight and they have a direct flight, right? And so you need to know all these subtleties of like, when are you willing to wait for how long, how much extra do you pay? And then you need to like have much more personalization still to make those agents work too. But for knowledge work, you can already automate a lot.

1:09:42Richard, why haven't we seen yet a kind of an agentic version of a Jarvis that just watches your tasks and says, Hey, last time you booked these, you always did this. So are you sure you don't want to do that again and tracks you and learns from your patterns and therefore that can then represent you more easily. I would have hoped to have seen that by now. Have you seen anything like that? Give it give it permission to listen to your phone calls read your emails, watch you all of that. Yeah, there are two two or three problems of why we haven't seen it yet and sort of lockers. Not nothing impossible to fix But so number one is you're not allowed to record other people without their consent So that puts a damper on a lot of things.

1:10:22A lot of countries will sue you and like California, like in Europe and so on. So that's why you can't have it. The second thing is Microsoft actually tried to like launch this where it just watches everything you do on Windows and people just went crazy. They're like, no way. You're gonna send a screenshot of every one of my things. People do private things sometimes in their browser. They don't wanna share all of that with the world. So that will be a privacy, like it's just a privacy thing. You need to build an insane amount of trust of those companies. Then you have a lot of AI companies that the AI forward, like AI first kind of novel startups, they don't have all the users trust yet and that ability to collect all of the data and so on.

1:11:02But then, you know, I think we will eventually get to it. I think someone will be able to like Apple is very good. They care about privacy and probably more likely you're trusting Apple with, you know, everything you might do on your phone. And then the fourth thing is that eventually we're going to have more AI agents surf the web than people. And that is a massive change for how the internet monetizes because there are basically a few companies that make money actually selling physical goods like Amazon, but even those companies are getting more and more into the second or main bucket, which is advertisement.

1:11:36Turns out your AI assistant doesn't get distracted when it has to just book a quick flight for work to Utah with this Bahamas like ads to like go for your next location. And so Expedia, even Amazon makes a lot of money with ads. If you start gnawing all of those, it changes how the internet monetized. So those companies will try to block all these operators, all these AI agents from just being able to get the work done. And so, you know, these are just like, oh man, you can have the intelligence, but the infrastructure around it will slow things down for adoption. I'm amazing. Richard, who are your main customers at u .com?

1:12:11Who should check out your site and tell us how to check it out. Yeah, so you can just go to u .com, why u .cum. Our biggest customers are cyber security companies, like MIMECAST. We have publishers, a lot of publishers that basically improve internal efficiencies for our journalists, or allow you just ask questions on your website and then get citations only on articles from your own network. So you can keep users longer. I want every journalistic outlet eventually to have their own GPT version, where it just answers questions about an article, you can eventually even think of these articles having very personalized follow -up questions like let's say you never understood why the Hootdoos and Tootsies were fighting each other and you read a new article and the outlet knows is the first time you read about this particular human conflict.

1:12:57Maybe they show you like some more explanations and background stories and stuff. We can are building that for for media and publishing companies. We have universities with like 30 ,000 students going live on U .Com where all the students can use it and the professors. Jeff thing will push those universities and all their professors to realize wait my students can just drag and drop this assignment in here and just give them the perfect answer I need to think in my assignments like we think all of that so we're excited about those And then there's a whole host of like consumer companies that want both the search APIs that power sort of the plumbing of the LM's as well as the answers Be done for them and have some API customers that are ramping up massively and revenues increasing lots been really great It's been a pleasure to get to know you and build our friendship.

1:13:44Seleme, as always, thank you for making time. I think I used to feel like I had a grip on what just happened. Now it's at an insane rate. I can't imagine next year. But yeah, incredible week in technology this week. Richard, Seleme, thank you guys. Stop. Give me.

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