[Music] if you were given a couple of billion dollars you’d be able to build a digital super intelligence how quickly I think probably like year and a half to two years Richard soer Richard soer Richard soer often called the father of prompt engineering he is one of the top five most cited researchers in AI former Chief scientist at Salesforce co-founder of the AI powered search engine.com we’re too late to explore the oceans and the world we’re too early to explore maybe different galaxies where we were right on time to explore super intell why haven’t we seen yet a kind of an agentic version of a Jarvis that just watches your tasks programming science research that’s where the next Frontier is for a lot of these amazing olives I cannot believe that we’re alive right now it’s like people should realize how extraordinar lucky we are undeniable now that’s a moonshot ladies and gentlemen everybody Welcome to moonshot
[00:01:00] another episode of WTF just happened Tech this week here with Saleem Ismael I’m Peter D mandis and we have ai royalty with us today uh Richard soer is uh the fourth most cited individual across Ai and Richard what’s the proper way to phrase your your domination and being cited I have uh over 200,000 citations invented one of the most popular word vectors got neural networks into the field of natural language invented prompt engineering that’s right incredible and you know Richard is the founder and CEO of u.com we’ll get into that a little bit later um he uh was acquired by his company uh metamind was acquired by Salesforce and he was the chief scientist in EVP at Salesforce and a lot more Saleem welcome as well buddy good to be here yeah so a lot happening this week in the field of AI and I want to dive into that Richard get your
[00:02:00] uh extraordinary point of view here I want to start with uh with the launch of grock 3 if I had to sort of like tier all of the activities that have just occurred uh and I want to contextualize it on the notion that it wasn’t very long ago that Elon raised $6 billion I was you know full disclosure an early investor in in xai and he announces he’s going to create the largest uh GPT cluster on the planet make it coherent and he does that 122 days and blows people away were you shocked Richard on how fast he built what he did youone executes uh and with $6 billion dollars you know you can do a lot of damage in AI I mean we’ve seen companies like deep seek uh and and that hedge fund uh built amazing models with much less so um in in some sense it’s amazing and it is surprising how quickly they got that far but in some ways you can expect some of these with exponential Technologies like AI
[00:03:00] enough resources you can go hard pretty fast yeah my my standard phrase is don’t bet against Elon I just saw him last week in Miami I was there for the fii summit and uh the guy does execute he’s got an incredible team so I’m curious about how you’re benchmarking grock 3 you know apparently it’s outscoring you know Chachi PT Gemini deep seek how do you how do you rank it a GU an AI engine um so uh we actually yeah have Croc 2 already within you.com too and it’s a popular model though there are others that are even more often chosen by our users uh I think what’s interesting is you know Sam Alman also talked about how the next generation of models are going to be almost the level of a PhD student but what we notice is that not many people are phds and have PhD level questions in their lives so for for more and more people I think we’ve reached a level of informational needs and knowledge needs that is enough for them
[00:04:01] uh so now you kind of push harder on really hard tasks like programming we’ve seen some some exciting announcements today uh anthropics new 3.7 model like I think programming science research that’s where the next fontier is for a lot of these uh amazing models s what have you been hearing on the ground I’m hearing grock 3 is incredible but the outperforming all other AI models seems to be a little bit more hype than reality I think I think it’s coming in as far as I can see when I scan Twitter or x a little bit lower than them but still unbelievable that he’s been able to achieve this in such a short period of time um I’m fascinated uh Richard when you because you guys do like Federated AI because you have access to many models right so I’m really interested in hearing more about your model and what you guys are doing but just on the grock 3 thing I think the for me the biggest thing is the his ability to achieve coherence across such a large cluster that part blew my mind because as far as I could see every AI
[00:05:01] expert said you can’t do it and I Richard I’d love to get your kind of take on that piece of it yeah I think not many people have been set like been able to set up uh a big cluster that quickly um I think in many ways that is a combination of hardware and software and a lot of folks like me are more software people and a lot of AI folks have been spending most of their time in software and so uh I think it kind of speaks to his ability to like work in both Hardware just sort of where he comes from much more of Tesla and uh SpaceX and such uh but now moving into like scaling that up uh and actually getting all the software components at the same time of course there are companies like any scale and and others that are making it easy and easier to deal with massive clusters right any scale allows you to like up scale from like five gpus to 5,000 gpus within a few lines of code uh and so the layers of abstraction are going higher and higher and you know we’re all thanks to
[00:06:00] AI partially uh are operating at higher levels of abstraction I’m curious about uh how people can evaluate these against each other at the end of the day you know I think about human IQ tests as an interesting metric to evaluate them you know I was I was fascinated when when Claude 3 came out at an IQ of 101 and then uh was it gp1 or gp3 came in at a IQ of 120 and I’ve been wondering about when we’ll see you know something coming out at an IQ of 150 uh is that a relevant measure you know IQ has like a lot of different dimensions I think intelligence overall has a lot of different dimensions which we briefly talked at our fii uh conference uh conversation um I I don’t know if it makes sense to just boil it down to this one number uh I think even the Turing test is essentially broken in the sense that the best way to fail the Turing test is to answer questions so much better than a human could like right me an app in 30 seconds and then if it can
[00:07:02] do it it’s an AI if it can’t do it it’s human right so it’s like there are many ways that we measured intelligence that are broken and I’m working on helping the world kind of structure uh that measurement a little bit better by understanding sort of what the dimensions are of intelligence and if there are upper bounds to some or if it can just keep on growing so you know it’s interesting right so you’re providing access to large corporations across most of the AI models how many AI models do you have on u.com like 40 plus yeah 40 plus amazing um if you’re G to if you were going to uh just for people to get a sense of the largest and most powerful models out there uh what’s your list of the top five thereabouts you know like you you can’t ignore opening eye still a lot of folks want to use open Ai and um especially uh 01 and 03 are are quite popular we have a lot of fraud too people trying to create accounts and then like just make us into a free API and then make like 10,000 calls in one hour and you’re like no one
[00:08:00] can read that this is clearly a bot attack uh that happens all the time uh Sonet is still very very popular too Sonet 3.5 and I’m sure this is anthropic yeah yeah anthropics model is probably one of the best models for programming still um so we are we actually we have our own models which we just find June open source models uh and then we also Federate and ask different models depending on where people give the most positive uh feedback given the intent that they have so we classify the intent is it a programming intent uh is this you know a history or a medical intent and then we route uh to different models and it changes actually the most surprising thing maybe is how often it changes and how much mind share deep seek also got in such a short time with not much of a marketing budget right so that was a very popular model for for quite some time everybody Peter here if you’re enjoying this episode please help me get the message of abundance out to the world we’re truly living during the most extraordinary time ever in human history and I want to get this mindset
[00:09:01] out to everyone please subscribe and follow wherever you get your podcasts and turn on notifications so we can let you know when the next episode is being dropped all right back to our episode let me head to the next slide here so grock 3 benchmarks versus the competition uh and here are the numbers so these benchmarks are they relevant and and valuable I I’m I’m curious because everybody wants to know how fast they’re progressing um this is on reasoning and test time compute Richard how do you view this yeah uh I think there are two interesting insights here is indeed like most normal people don’t have crazy hardcore coding science and math questions every day in their life so this is where we push signs forward like I just mentioned earlier uh and that’s where that Frontier is really exciting the other really interesting bit here is that we’re looking at test time compute and so it doesn’t even make sense anymore to think about a single models intelligence because it turn out there’s some fun research that came out
[00:10:01] where you just say wait before you answer this and give it some more thought the same model actually does better and gives you more accurate answers so speed is becoming kind of a uh type dimension of intelligence obviously overlapping with a lot of other kinds of intelligence and the faster you have to be you know the the less intelligent you are the less intelligent your answers are from these models and so what that also means is we may not have to worry about sort of AI running away and open source because you’re going to have to have a lot of compute even at test time if you want to get the smartest possible answers from these models so lots of interesting insights s any any questions Richard I I’m I want I’ve got I’ve got I’ve got a big one which is you know as we move towards AGI I struggle massively when people say AGI and what the hell does that mean even and so I’d love you’re one of the few people that I think could give a coach an answer on how do you define AGI and if we achieve it how will even know and you just put out a you
[00:11:01] just put out a tweet Richard that I found interesting um that said something like if you were given a couple of billion dollars you’d be able to build a digital super intelligence how quickly I think probably like year and a half to two years um was that was that a call for funding like everybody listen give me $2 billion and I’ll give you your digital super intelligence yeah I mean you know I I I miss going on the research side uh going hard um you know when you built the products and you you know make Revenue it’s uh amazing it’s very meaningful but I think uh there’s still there a couple ways that the community is stuck on in terms of research where we can really Push It Forward um I think in terms of AGI uh indeed uh the definitions are so broad right some folks say well it’s 80% of work can be automated and that’s a very pragmatic way of just like you know sort of financially defining uh intelligence um of course I would say that maybe 80% of all digitized work can be automated
[00:12:00] um and then you know maybe 80% of all those workflows and that’s already a huge amount of of GDP uh and that could be a reasonable Financial definition of intelligence but of course if you’re sort of more academically inclined you have to acknowledge that uh there’s certain kinds of intelligence uh and types where you want to um really get uh faster at learning too like humans are able to just with one or two examples learn something so we call the Le efficiency right and if you’re really that intelligent you should be able to learn with much less data along certain dimensions and so uh I think as we want to Define it really properly we’re going to have to go into the different types of intelligence visual intelligence language reasoning mathematical reasoning there’s some type of social intelligence to even among AI like what actions could I take to modify your internal state in order to influence your actions right so there are these different dimensions of intelligence knowledge is a good like dimension to which is quite unbounded right we can
[00:13:01] learn more and more about the universe you end up hitting sort of physics based uh boundaries uh of of how much knowledge you can accumulate um based on the speed of light cone around the different sensors that you may have so the full definition is probably takes too much time here but a financial pragmatic one of just like we automate a lot of digitized work seems reasonable and what’s your view of going to the Physical Realm for example wnc his test is can you make me a cup of coffee and now you’re getting into robotics or the other one I’ve heard is can you put an take an Ikea box and put the piece of furniture together right now you’re getting the physical manipulation which is really is one of the core rationals for intelligence do you go into that world or do you stay in the digital side because it’s just you can boundary it more easily I actually think that physical manipulation is another definition that dimension of intelligence or group of dimensions and at the same time you know a deaf person can be very intelligent a blind person can be very intelligent so of those
[00:14:00] abilities a person as paraplegic can be very intelligent even though they can manipulate matter so I think we have to accept the fact that these are not necessary capabilities to have a super intelligence right you can have a super intelligence that I think is purely digital and it’s just different to our intelligence and I think people who require to say oh you got to have a bunch of fingers and move around they’re just like not they haven’t read enough sci-fi maybe or not like uh uh sort of creative enough in their definitions of intelligence at the same time uh I’m I’m loving uh the uh humanoid robots the tricky bit is that often times we use robots when we can do certain things when we when we want to do certain things many many times very efficiently and very quickly like wash like wash the dishes or or vacuum the carpet exactly which then has like a simple robot Roomba or dishwasher right and then we then we call it a dishwasher and way we call it a vacuum we don’t we give it a specialized name I am you know Sim you and I have had this debate a bunch and I’m I’m curious about your opinion still
[00:15:01] and and Richard’s which is the whole open versus closed AI debate and uh do you feel like open is gaining on closed and is that a definitive future undeniable undeniably open source is gaining when you have this much excitement around something and it is a product and experience that any normal person can appreciate there’s so much energy that goes into open Source uh that it is very hard to compete with that in the long term the more Niche you are the more Technic it is the fewer people can appreciate using that technology like let’s say you do ion thrusters for you know satellites like no one’s going to build an open source model for that for with millions and millions of dollars and that excitement um it’s undeniable of deep seek that it’s been catching up and I I’m hoping we can build one system eventually where almost like Wikipedia people can contribute to it um no one does that I’m I’m going to have to do that at some point I I have I have the same view we
[00:16:01] saw this in the software world when you had Microsoft running its internet server and then you had open-source web servers and the open source web servers just absolutely took over it’s 99.9% of all web servers are now open source and therefore over time that will always win yeah so my question then is okay we’re going to be heading towards open source got it um we have still a number of Clos Source companies are they eventually going to go open source um are you know is there a win or take all scenario here I think there’s a good chance that if you’re purely foundational model uh a purely foundational model company you’re going to look more and more like a Telco like huge Capa very expensive to build creates a ton of infrastructure that creates value but it’s unclear you can capture all of that value yourself thank you for using that analogy and I think that’s the Perfect Analogy here so we’re commoditizing and demonetizing all of this I mean if you look at the demonetization Curves in
[00:17:01] terms of the cost per you know per transaction it’s like just just this rapid deescalation so how do you rationalize so in the Telo space right folks need to realize we had massive amount of bandwidth being built out in terms of fiber in terms of cable in terms of 3G 4G 5G and all of the value was captured not there but captured on YouTube captured on Netflix captured on apps on top of that and so how do you think about that Richard yeah you can’t build an Uber without internet everywhere you know but Verizon doesn’t get a cut of uber yeah so I think that is why at u.com we haven’t spent a ton of money on training models from scratch and we’ve built a trust layer on top that sort of professionalizes this so that companies can really use that technology and I do think more and more thanks to deep seek of our existing and now new customers are realizing oh yeah we should part partner with someone like you because if a new model comes out in
[00:18:01] two months and I’m stuck on a one-year contract with one of the close those companies now I can’t benefit from that makes it makes a ton of sense because there’s a continuous competitive and everybody’s it’s a race down to the bottom and if they become if you become stuck with a particular model uh you have no guarantee that you’re going to be using the most efficient lowest cost model yeah we call it future proofing organiz so what what does a trust layer mean for u.com a trust layer is highly connected to data um and helping people actually train on how to use the technology so we do certifications so everyone can become a manager of their AIS and of their agents and we incorporate not just public data better than anyone else because we’ve been doing it longer than anyone else but we’re also incorporating company internal data and so then you can actually start to trust it and then when you click on citations on you.com especially in our more advanced research modes you will actually get sent directly to the quote and the browser will scroll down and highlight oh this is where I found this fact so you can very quickly build that trust with them
[00:19:02] we we taught our models to say I don’t know a lot of models if they don’t find the information somewhere on the web they’ll just make up something be like don’t do that so these are a lot of different moving pieces uh to making it more accurate and building that trust you know Sim you and I have talked about when we’re advising companies and investors about investing in AI it’s like investing companies that have uh a great connection with their end customers and with data and then assume that the layer in between is just going to be constantly you know you know flick over replace it get the latest lowest cost model but it’s relationship with the uh with the customer base and uh and the data sets yeah I think this is going to be key into success in in AI platforms right and I think Richard it sounds like you u.com done an amazing job of creating that layer of
[00:20:01] abstraction that protects people from the underlying thing because otherwise one of the huge questions everybody has as we talk both Peter and I yourself we talked to CEOs around the world when do you make your when do you place your chips because the minute you put your chips down on a particular model it’s out a date in three months and so therefore you really need um uh platforms like u.com to help with that and I think it’s fascinating to see what you’ve done that here’s another article for the New York Times the for those listening to the podcast not watching it says open AI uncovers evidence for AI powered Chinese surveillance tools so of course we’ve had this entire you know incredible back and forth with uh Tik Tock and now we potentially have it as well um on deep seek uh what’s your what’s your views here gentlemen I’m not surprised um um how would it not be the case would be my question um that that that you would ask I think all these companies have downloaded you know deep
[00:21:00] seek and put it into their systems uh but it’s not is it are those if you download the model and are utilizing it in isolation is it still reporting back information that you that it’s gathered so you can yeah you can take the open source model and still force it to take stuff uh from a prompt and from a search engine backend so that is possible and you can actually also find tun the model to get rid of all the CCP alignment fascinating all right um our next uh our next story here is and I love this accelerating scientific breakthrough with an AI co- scientist you know I love the fact that we saw uh saw the Noel prize going to Demis and John jumper for the creation of a AI model able to predict the folding of a protein um my expectation Richard and and you’re both deep scientist and a
[00:22:00] deep programmer is that almost all breakthroughs are going to come from AI in the na distant future and we’ll we’ll attach it to a human so a human can get The Nobel Prize but it’s going to be fundamentally uh in the materi in materials in mathematics in science in medicine am I wrong there 100% yeah I’m writing writing a book on this uh sort of in my nights and weekends um on AI for Science and it’s called the Ure machine so the working title and I’m a big believer interesting enough also when you ask a lot of folks all over the world um in areas where they’re scared of AI most folks are scared that it takes their jobs but in terms of science and medicine no one wants more jobs they just want more breakthroughs and cool discoveries so everyone is a lie everyone worldwide is a lie let’s just have ai do a lot of science so there’s a lot of positive momentum behind it and I think we’ll we’ll see more and more discoveries uh first with the of AI and eventually you might you mostly guide it
[00:23:01] right you need to kind of tell the ey this is what we care about the most and then it can go off and do more and more in an automated fashion this is the area that I’m most interested in because I think there’s just so many if you provide it with data set and go formulate 5,000 hypotheses and start testing them it can do virtual testing of all sorts of things and I’m incredibly excited as what’s going to come from this I love this last bullet here it says replicated 10 years of antibiotic resistance studies in just 48 Hours um Dario was at Davos Dario the CEO of anthropic and he said something which I clipped which I love he said listen we’re going to see a century worth of biomedical research in the next 5 to 10 years and one could imagine that during that Century of biomedical research that we would potentially double the human lifespan and so it’s not unlikely it could double the human lifespan in the next within the next decade so I’m always listening for those signals because you know that’s like I’m in it for in it to win it on the on
[00:24:01] the doubling the human lifespan um and then we’ll negotiate we’ll negotiate where we go from there uh we saw uh Larry Ellison uh when he was on stage on Stargate uh announcing the idea that we’re going to have you know personalized mRNA vaccines against your cancer should you have it and so for me this is like one of the most extraordinary areas of Reinventing medicine curing cancer uh curing uh viral infections curing death perhaps who knows yeah I think a lot of people who now say oh like Brian Johnson and Longevity folks are just like that’s a bad idea I think one most of those people are healthy and aren’t currently battling anything uh and two they’re just like people before the baby pill came out right they’re like oh that’s not natural I’m like yeah you know like there’s a lot of bad stuff that’s natural like murder and no laws are natural like there’s just animal right stuff and so there’s like all kinds of
[00:25:01] bad natural things and Humanity has been pretty good at improving uh from that Natural State and uh I think it lacks a certain creativity when people think we can’t ever solve aging and health spans and things like that so you know we in 2018 started uh the largest project for a large language model for proteins and we actually uh published that paper when we I still at Salesforce um and we’ve had uh incredible success in fact we we believed in so much worked with wet labs and actually synthesized those proteins and they were 40% different to naturally occurring proteins and just to put that into perspective Francis Arnold about four years ago won a Nobel priz for what you call directed Evolution which was random permutations with a lot of experimental like Signs in the in the in the loop and then saying oh this random pentation improved this particular property so let’s keep this and then keep iterating by the end of her very long process those proteins were 3% different to naturally occurring proteins and hours were 40% and what
[00:26:02] taught us that we actually captured the syntax the grammar of these proteins was that they folded properly and they had the properties we predicted them to have and we wanted them to have and so there’s a lot more work that comes from this bunch of startups have already started and once you understand the language of proteins all the medicine will will follow this goes back to Saleem your point about AI interfacing with the physical Universe right so um another friend uh Alex zankov the CEO of ENC silicone medicine uh one of the things that he’s done and he was he was very early in generative Ai and uh and Drug Discovery but he’s built a massive robotic laboratory where he can basically have the AI come up with experiments uh and run those experiments you know a 100 times faster than humans get the data iterate the experiment run the experiment and so you literally create a theoretical world and a
[00:27:01] physical world uh and I find that extraordinary yeah I think we’re see I think we’re going to see hundreds of examples like this where people now if the only limit is our imagination and how fast we can apply some of these because the speed of the technology is now at a level where we can pretty much go down any Avenue we want me personally I’m looking for how do you reconcile quantum mechanics with with relativity as a as a physics major that’s my thing and I think AI will be able to figure it out yeah I’m I cannot believe that we’re alive right now it’s like people should realize how extraordinarily lucky we are this I don’t think this is you know every every generation feels like they’re alive during the most extraordinary time whether it was you know at the beginning of flight and electricity and the internet and so forth but I think it’s I think we’re I think we’re to explore the we’re too late to explore the ocean and the world we’re too early to explore maybe
[00:28:00] different galaxies but we’re right on time to explore super intelligence yeah for sure you know the other area besides medicine is Material Sciences so we just saw matter gen out of Microsoft right talk about prompt engineering my friend your prompt engineering has now gone into a completely different like please build me design me a material that is super conducting that includes these elements that is this cost uh that can be manufactured you know it’s like crazy it’s like if we had like a room temperature normal pressure superconductor from that it would be world changing and I’m very excited for that yeah yeah the nice thing about chemistry is that unlike biology you can iterate even faster right there’s no living tissue or there you don’t have to run FDA trials and so on you can just iterate even quicker in that Loop yeah and uh you know s you I always said Material Science is is at the foundation of everything else and you know we consider material scientists heroes in our world all right selem uh what do you think about this one Satia
[00:29:01] Adela on Quantum breakthroughs quote we believe this breakthrough will allow us to create a truly meaningful quantum computer not in decades but in years um so Google Now Microsoft yeah I think this is beyond huge I think as we get to this we have to keep in mind the limitation that quantum computers are only good for certain classes of problems so there’s that limitation but the fact that you can create stable environments is is really something huge I go back to helmet’s comment that the existence ofum heart yeah um his his comment that the exist it’s 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 so Richard I’d love to get your take on this because you’re go step further right he says the only way quantum computer can do all of the calculations as rapidly as they do is that they’re
[00:30:02] borrowing resources from a near infinite number of universe ad jent univers yeah we’re doing the computation in parallel universes and bringing the answer back I love it at which point they’re going to be pissed when they find out we’re stealing their resources so there’s that to think about as well hey Richard what’s your view on all of this uh I’m super excited I think uh anything you can simulate uh any domain you can simulate AI can solve pretty much every problem that domain uh it’s just a matter of time and with 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 it can know AI can learn through two ways right either imitation or exploration AKA you know supervis and fine-tuning and and supervised training or uh reinforcement learning and so when you can allow a simulation to just train and try billions and billions of things it can get smarter over time what uh quantum computers will enable us to do once we scale them up is to ulate much more in the physical reality um uh my
[00:31:01] favorite science influencer Sabina hosen Felder put a little bit of a damper on on this particular announcement saying oh you know we’ll see if they really can scale it um but but I’m very excited I’m excited that there are different ways of approaching that you know like the trapped ions the neutral atoms it’s it’s interesting you hear a lot of uh Quantum uh scientists kind of diss the other approaches and think their approach is the best and then comes like this total left field one of these topological cubits that no one had been working on and I I just love the fact that there’s this energy and that you know 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 in one before something comes out amazing and it’s and honestly thank you to Google and Microsoft for investing in this direction because there’s there was no immediate return you know we saw uh hartmut NE uh latest um remind me what his
[00:32:00] breakthrough was a few months ago you know it announced that the larger the number of cubits the more stable it became right um uh and majorana is that how you pronounce it majara one majana yeah yeah um incredible it 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 uh 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 fountain upload you know Fountain is one of the most advanced Diagnostics and Therapeutics compan companies I go there upload myself digitize myself about 200
[00:33:02] gbt of data that the AI system is able to look at to catch disease at Inception you know look for any cardiovascular any cancer any neurod degenerative 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 Fountain is one of my keys I make that available to the CEOs of all my companies my family members cuz you know health is in New Wealth uh but beyond that uh we are a collection of 40 trillion human cells and about another 100 trillion bacterial cells fungi V and we you know don’t understand how that impacts us and so I use a company and a product called viome and viome uh has a technology called metatranscriptomics it was actually developed uh in New Mexico the same place where the nuclear bomb was developed as a biod defense weapon and
[00:34:01] their technology is able to help you understand what’s going on in your body to understand which bacteria are producing which proteins and as a consequence of that what foods are your superfoods that are best for you to eat or what food should you avoid right 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 and then finally you know feeling good being intelligent moving well is critical but looking good when you look yourself in the mirror saying you know I feel great about life is so important right 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 pepti TI it’s able to zap scile cells in your skin and really help
[00:35:03] you stay youthful in your look and appearance so for me these are three Technologies I love and I use all the time uh I’ll have my team link to those in the show notes down below please check them out anyway hope you enjoyed that now back to the episode all right let’s go on to our next uh topic here so Microsoft dropped some AI data center leases so cancellation of us data center leases raised concerns about AI infrastructure overc capacity and shifting Partnerships move sparked industry reactions with European energy stocks so there’s been a lot of buildout um you know this ties directly to energy as well um you know I keep on hearing and Richard I’m I’m curious in your point of view that there’s an open checkbook for building out capacity and building out energy we’re seeing
[00:36:00] small modular reactors smrs this is fourth generation nuclear setting up next to these uh to these we’re seeing um I mean you know I’m I don’t get into po 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 this industry uh are we are we overbuilding uh or are we not even close I believe we’re overbuilding you think we overing yeah I believe we’re I’ll tell you why um U 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 and therefore the amount of buildout is is exaggerated because it’s aiming at a
[00:37:00] time aiming for a model or size of model that was uh there six months ago when you started the building uh and that will not be the case when you finish the building so that demonetization aspect of it I don’t think is being taken into account they’re building for the capacity they think they’ll need given what’s the projections without realizing that those projections will be wrong that’s my comp that’s my general complaint Richard you may have some more specific I uh I I mostly disagree I mostly disagree I thinkc I’ve 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 jeevan’s Paradox right when we make uh things more efficient we actually uh 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 more and 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 and I can talk about that forever but a lot of human
[00:38:00] 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 or water just happens to have too much salt in it which is an energy problem right so all these water fights that are going on it’s like well if you have more energy just desalinate ocean water and problems solved right you can like there’s all these deserts that you can’t live in right now because there’s not enough water well if enough energy that those problems go away too so my hunch is we’re going to find a lot of uses for that energy now where I do agree with you on 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 um where you build a lot of buildings but people don’t move into them and 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’ll need less than people think of
[00:39:01] that but we definitely will use all the energy we can for desalinization other things so yeah I think we’re kind of generally coming to agreement there before we get into thinking machines here in this article from Tech runch about miring you startup I am curious I mean over the last year we’ve seen this constant flow of the leadership of open AI out of open AI um which is concerning I mean um I’m not an investor in open AI uh if I were I’d be very concerned what do you think’s going on there I’m I’m curious open question either of you guys um I think the doors are very open I think the the the basic General thing is if you get to that level and you’re suddenly the hottest property Executives or or deep researchers in open a you can essentially go follow your passion and go find your MTP and go build something whe whether Mira is doing what she’s doing or any of the other After People some may be interested in healthc care
[00:40:00] 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 of the speed and move fast and break things approach that Sam has for how to build stuff that is concerning a lot of people then you got 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 Richard as to where your reaction as to where’s the emphasis on those three two or three different areas I think I think at a very high level zooming out a little bit uh the fact that California has non-competes and the rest of the US is actually moving towards that um or like doesn’t you know doesn’t have non-competes as in like non-competes are not enforcable in California uh is tough for companies uh very often research costs a lot of money but once you show the world that something is possible at all it’s much much cheaper to copy it uh and it’s also much easier to knowing how we you’ve done it in one place go and take that knowledge without taking any code but
[00:41:01] it’s that’s you know stuff’s 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 just going to see cheaper better faster models so let’s talk about uh thinking machines uh any any clue about what Mira is going to focus on so I guess uh lots of smart people joined her John Schulman who who L the chat gbt application of the LMS you know that had been available as apis before we had already Incorporated them before chv came out inside you.com in a search engine like context and so uh having some amazing folks that really understand the technology and uh also have ideas for for Building Products um is uh is probably a very positive thing and I mean she describes and they describe a lot uh on their on their website um my hunches they’re going to try to explore uh I hope they don’t just build another llm um I think there’s so much more stuff out there uh but yeah we’ll see yeah what I find fascinating and SEL I’m curious about your point of
[00:42:00] view here is I think her her starting valuation is $30 billion um I mean it’s everything’s gone up everything’s gone up yeah it used to be millions of dollars and now it’s billions of dollars I don’t know how quickly you can justify monetize this stuff I think we’re we’re headed for a pretty big bubble on as we as we get to the application side of this because when you get to the user is demonetizing so quickly that that where’s the revenue will be the big question over time I think uh putting my investor had at a ventures on for for a little bit um the way we think of this is that it’s essentially seed stage risk combined with late stage returns and so as an investor that expected value just doesn’t quite work out but it doesn’t mean that no one will succeed right it’s just seed stage risk once in a while every know 5 10% of seed stage companies actually do something amazing and like one or two of those in the power law as an investor really blow out and return
[00:43:01] the entire fund multiple times and so there are a few such possibilities but man it’s really tough and the bar is so high uh to be able to get enough Revenue to eventually uh be able to justify these high valuations so 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 um 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 points can they get Revenue yeah and or do you invest in stuff that has massive breakthrough and has the potential and you’ll hope that the potential yields where where do you put your chips on that yeah so we’ve been we’ve been doing really well fund one’s already like five uh 5x tvpi and it’s uh only like four years old or so and so um we’re looking uh there there’s sort of
[00:44:02] two ways to slice and dice it one is there’s a horizontal uh new infrastructure layer right and in that you have companies like hugging face I was very fortunate uh there were my students when I was a professor at Stanford invested at a 5 million valuation round um they’re worth four and a half billion now so there’s there are 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 a similar one we’re investor in to the cursor Co was actually an intern of mine I was really bummed I didn’t get to invest in in that one um and so uh then there are thousands of application companies vertically that’s sitting on top of that are sitting on top of this new stack uh and so there we look for deep industry insights and deep AI 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 our proprietary data sets something that you look for or find exciting in all of this the best
[00:45:01] companies uh will have what I call virtues data cycled at least uh 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 you know one of the reasons why uh Tesla is much better suited and why we’ve seen a lot of uh self-driving car startups die is that they had to pay for every mile driven by a human to collect data versus uh of Tesla we all drive the car and we give the data from for free and we actually paid to drive the car to collect that data right and so that that is a perfect example of a virtuous data cycle and you see that in VAR SAS softwares like you.com we get people 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 uh some kind of advantage over time so I get two out of two things out of this one Elon owes us money and number two um to be really successful in AI be Richard intern at some point I love that that’s right there all right
[00:46:01] guys that was fun and I think the other side of AI is one of my favorite topics it’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 um uh I’m going to share a short video here uh this is a robot uh called clone uh I contacted the CEO and he’s going to be bringing his robots to the abundant Summit next year but let’s check out a little bit of a video here so uh what clone is doing is basically uh creating uh what’s that Westworld uh so these are these are muscles um they’re hydraulic systems and that video is under representing what it can do in terms of moving the hands uh they hope to have it walking in the next few months uh they’re based in Eastern Europe where they’re doing a lot of work uh but talk about an interesting future
[00:47:01] of robots where I mean a lot of the robots today out of the US and China are clunky work Walkers they they do walk but they don’t have that that human emotional cheaper prices uh and incredible capabilities in robotics that’s my first stop the second one is I think the the black horse here similar to uh to deep seek is unit tree unit tree 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 um that’s the second th the third one is yeah I’m excited and now the question is always like what’s the what’s the the really most amazing use case for humanoid robots versus you
[00:48:01] know like a tractor Factory where you just have a bunch of little lasers and thousands of arms and things like that you 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 some game there’s a ton of cool stuff I would totally buy a humanoid robot to have like stuff be done in my house and just kind of clean and they can do it at night right so they don’t have to be super fast and uh now the fourth comment is I feel like everyone works on AI version of Robotics it’s like the original Terminator no one works on a 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 jammed on with a really brilliant Hardware hacker and he’s like you know this could actually work and make sense so project number five um if I have some oh you heard it here folks Jim Cameron was right and it’s all going to be due to Richard choser um I gotta I gotta say something here um you know if you want a muscular skeleton humanoid robot you get
[00:49:00] a man and a woman and you have a baby and you grow the baby I mean I I don’t I I I really struggle with this like if you know we talked earlier right if you want a dishwasher you have a machine that that sprays water in a particular way and it looks like a box and you have trays to put dishes in whatever oh same 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 etc etc why are we constantly going back to the human form which is frankly we we have we about this drives me nuts you’re just wrong it’s I’m 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 much many more things like why make it look like a human well any move on so I so I am an investor in mackina Labs too they build these massive arms and they can form sheet m and they work with SpaceX and a bunch of folks whenever you don’t want to build an
[00:50:00] entire Factory to make that same large piece of metal millions of times but you needed like 200 times they’re perfect for they can literally ship a factory that creates any spare part into the field somewhere and then they just have like almost like a blacksmith but massive uh and and Ai and they’re also like oh anti- humanoid now again it’s not a zero some 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 and you know that that’s the excitement for robotics doesn’t have to be zero some all right we have a lot of a lot of robot announcements uh this week so let me 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 uh uh you know in terms of its motions now how stage this is and uh how practiced you know we don’t see the
[00:51:01] 37,000 shots that went wrong but uh 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 Brett’s the CEO we’ll see him in a minute CEO of of figure and of course Elon overseas Tesla and Tesla bot now called Optimus the projection is as many as 10 billion robots by 20 240 and I can imagine that I have no problems imagining I would own uh you know two or three maybe 10 Sim no not you you you know my struggle with this I mean one robot moving very quickly is 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 uh you making coffee at so so I strugg I think I think we I think I feel more comfortable having you know a humanoid robot walking around the house than some
[00:52:01] 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 I think we’re going to have the same thing with human art robots for sure and like there sci-fi kind of uh is is underrated and showing us sometimes also the like the positive ways like um you know people will fall in love with their robots and they have these Androids now I think with short term uh we’re going to have to we’re going to see a lot of folks just uh remote controlling a robot collecting training data that way and so there’s going to be an part of The Uncanny Valley is you may have someone in uh India or somewhere sitting looking into your entire home being able to navigate everything seeing your kids opening your doors and everything uh and you kind of have to be okay with that invasion of privacy potentially right um and then once you once they get 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 then you know and attach another arm if you really want them to uh you know they can be more modular that way so I’m I’m
[00:53:03] excited for it all right so that was Neo GMA from 1X Tech uh let’s go to the next robot here and uh and this is figure AI so just for uh for disclosure I’m an investor in figure I don’t know if you are Richard um this is Brett atcx company and they just announced their software interestingly enough uh figure used to have a software relationship or a geni relationship with open aai uh and they have uh they shut that down and they decided to build their own AI team internally and to build uh Helix and I think the logic there is in the same way that Tesla got so much data uh from autopilot as you were driving it around that allowed them to create these incredible models that figures AI I really hope they come up with a separate
[00:54:00] name for it because calling the company figure and the robot figure it gets a little bit confusing but they’re going to get a lot of data uh and that’s going to train the AI in the physical Universe uh let’s take a look at uh at their at their video so s instead of having four arms you have two robots instead and they collaborate it’s called collaboration I just I I think this is going to take a much longer time for people for it to work out than than people realize but you know it’s it’s fantastic to see the speed at which it’s moving forward because 10 years ago when we were first looking at robots it was was really hard to imagine they would get this this remember the so clunky and
[00:55:02] so I thing so it’s fantastic to see that um 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 so hard yeah and like I think robotics has done a phenomenal job if we can constrain the environment a little bit more that’s why self-driving is also a fairly constrained environment standardized in a lot of places the highways all look the same things like that road signs or 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 uh out of China and just say oh this is how they do it now we reverse engineer it and then can leap frog skip all the expensive research stage and and and and and I’ll
[00:56:02] go to my favorite use case which is going to be a while before you get one of these human robots 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 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 uh this reminds me of two of my buddies being really stoned and trying to unload uh the LA that’s perfect have a field with episodes around this the doorbell is about to ring it’s my it’s my figure robot coming over there to give you a hug so answer it and be nice um okay all right I I can’t help do an episode without Bitcoin um let me begin the question to you Richard are you a believer in Bitcoin there’s a faith component here when I say believer are you a holder in Bitcoin I have just a tiny bit here and there um uh invested in a fund that that does a lot of uh crypto things uh just to have
[00:57:01] 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 AIS are going to need to have and agents are going to need to have mechanisms for transacting financially so uh you know let’s take it slightly sideways to uh cryptocurrencies for for AI agents to do business amongst each other uh what do you think about that I mean it makes sense but they can also like do that with credit cards right like we’ll have ai kind of make credit card purchases fairly quickly um I was a little bit dismay when I actually try to play around with the technology and then it’s just like the gas fees and so on were also pretty high and I’m like wait this is like a credit card fee almost is like already costs a lot of money I’m like this doesn’t seem right um so I don’t know I feel like they need to really lower the prices so that the transactions themselves are insanely cheap yeah there’s a whole stack of you know you’ve got Bitcoin with very
[00:58:00] 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 uh so if I’m moving if I’m storing jewelry in a bank vault then you have a lot of security and 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 uh and then for you can lower the security for the 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 SEL when you see the price now you know at this very moment it’s a uh 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 the the bite um the bit bite whatever bite bit um 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 right so I think that’s one the very and the second was the the response from the exchange with the CEO going
[00:59:02] we’re going to get everybody made whole again very quickly Etc gives me encouragement that there’s robustness being built into the ecosystem which U gives people a lot of confidence going for it so I’m pretty excited about where that could um where this will go uh the the Trump uh meme coin did not help the crypto world at all and so that’s really unfortunate but that’s life you get what you ask for it did you no no not no no no because you can see it’s it’s only going One Direction so if you don’t mind you mentioned the uh uh the the the bybit uh billion doll hack can you unpack it us 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 watch the transactions because crypto is fairly traceable there’s appeals to um uh
[01:00:02] ethereum right up to vitalic to say can we just roll back the the the thing before the hack and it’ll just undo the hack basically so there’s a call for that uh uh 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 um I don’t know how you Su sustain this I’m just I’ll just repeat I’m really encouraged by the response from benia and the and the and the byit folks saying we’re going to just not navigate all this uh we’re going to keep everybody whole and the fact that they had enough backup to do this in general what we’ve found in the crypto world is you want to not keep ma major wealth on a on a centralized exchange for this exact reason mount gaau 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 stor of value yeah I know but every time I you know I
[01:01:00] use a a treasure or a um uh what’s the a ledger you know sort of thumb drive wallet but I Puck her up every time I go and 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 I remember you comment about when a technology goes from uh deceptive to disruptive uh the usability becomes much 10x 100x better so Steve Jobs made the smartphone usable and boom it took off coinbase made the purchasing of Bitcoin usable and very user friendly and that took off but the rest of crypto is still a hot mess uh anybody that tries to buy an nft or trade an nft knows how sticky it is or execute a smart contract you have to be like geek level 14 to be able to even touch that stuff yeah I’m using Abra Abra from my major Holdings but I still have again on coinbase and a number of different places but uh it it turns out to be significant amount of capital and
[01:02:01] 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 like if someone steals your credit card and you see a bunch of purchases you can just tell them like that wasn’t 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 now has for their own wallet and then you know people are just not sophisticated enough to be able to deal with all the cyber security threats very often uh you know switching here to micro strategies now called strategy uh Richard uh Michael sailor was my roommate uh fraternity brother at MIT so we go way back uh he is extraordinarily brilliant and I was just with him in Al Salvador uh I was there speaking with Carlos Slim Mike sailor and Mark andrees and Ben harwitz and Mike gave a massively compelling 90minut
[01:03:01] presentation to this room full of billionaire family offices and every time I hear them I’m like okay I I mortgage my house sell everything buy Bitcoin the guy is you know it’s very dangerous to listen to Michael FR mik it’s it’s compelling you know it’s interesting though that I want to just point one thing out for those of you who are nervous about this this fall the equivalent is you know it’s hoddle and buy on the dips but uh I I have to verify this SEL I wonder if you know that if uh if you try and buy into and out of like sell out of and buy into Bitcoin uh that’s problematic that most of the gains I this as a memory I wonder if it’s true that most of the gains last year were made on like five trading days yeah this is historically accurate uh in any given year Bitcoin accelerates at some point in the year and it’s very very few trading days that make up 80%
[01:04:01] 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 um and so and then you buy on the other side of it and then 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 uh you know Michael made another move move uh he acquired another 20,000 Bitcoin for about $2 billion uh you know you know it’s pretty extraordinary moves I mean yeah I wish has a lot of incentives to give 90-minute presentations to everyone buy more Bitcoin yeah he does uh for sure it’s uh it’s definitely um we we know you I look there’s one other way I look at it is if you wanted to have somebody be the prime evangelist for a technology the articulation he brings to the table is hard to beat and you you could spend
[01:05:00] a lot of time trying to find a better one it’s incredible he is amazing um Richard uh open Forum here what’s been the most amazing uh events breakthroughs Technologies companies that you’ve seen the last few months oh boy uh we just covered uh covered quite a few um and you know I saw agent Forest I did a podcast with your buddy and mine Mark Ben off marks amazing agent force 2 coming on strong um what do you think about the whole agentic world I’m a huge fan I think you know 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 them both with imitation and with exploration and so uh when you think about what are other interesting sequences you know in 2019 we we started 201819 we started on these large language models for protein sequences so boom you got biology but then the very
[01:06:02] obvious uh sequence is a sequence of actions too uh and so I’m very excited uh we already have over 50,000 custom agents built on the u.com platform by our users you can select which LMS you use give us give us examples of the agents like that people would use what are the top so for example you’re in marketing you say oh every time like every two three weeks I get a a huge uh PDF file with a bunch of new features and some like like website that describes a new feature uh that uh product engineering uh have been shipped and then I’m tasked to write two email marketing campaigns for specific Industries tasked to write three LinkedIn messages I 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 uh we talk to these marketers and they say oh well just describe that explain that very well to an agent on you.com and the next week
[01:07:01] 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 the 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 I 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 uh switch on in the uiux 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 uh told us that tasks that used to take them multiple days now take them like two three hours and they’re done maybe the last fun one uh that’s relevant for you is we have venture capital firms that say well if I get a new data room I go through 10 steps I look at net dollar retention I do CAC LTV ratios blah blah
[01:08:02] blah uh and then you just describe that again and you drag and drop uh an whole 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 can 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 bank account information at the end that’s step two from my my my description of a gentic AI is white color job description yeah that’ll be epic and 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 with robotics like we’re going to have an uncanny valley or like just a trough of dis disillusionment potentially because when when I saw like this rabbit 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 stes and then boom boom boom now it’s done and I’m like no way that was
[01:09:01] real cuz you have so many details right like this hotel I wanted to be close to these kind of sites I want to see uh 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 uh stop like or zero stop flight and 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 you need to like have much more personalization still um to make those agents work too but for knowledge work you can already automate a lot Richard 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 then can then represent you
[01:10:00] 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 there’re two two three problems of why we haven’t seen it yet and sort of blockers uh 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 a lot of countries will sue you and like California like and Europe up and and so on so 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 going to send a screenshot of every one of my things people do private things sometimes in their browser they don’t want to share all of that with the world so that that will be a privacy like it’s just a privacy thing you need to build an insane amount of trust with those companies then you have a lot of AI companies that the the AI forward like AI first T of novel startups they don’t have all the users trust yet and that ability to collect all of the data and
[01:11:01] so on um but 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 uh 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 uh 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 turns 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 on your next vacation and so Expedia even Amazon makes a lot of money with ads if you start ignoring 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
[01:12:00] work done and so you know these are just like oh man you can have the intelligence but the infrastructure around it will will slow things down for adoption amazing got Richard who are your main customers at u.com who should check out your site and tell us how to check it out yeah you can just go to u.com y.com uh our biggest customers are cyber security companies like minecast uh we have Publishers a lot of Publishers that basically improve internal efficiencies for a journalist 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 hutus and tosis were fighting each other and you read a new article and the outlet knows is the first time read about this particular human conflict maybe they show you like some more explanations and background
[01:13:00] 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 which I think will push those universities and all their professors to realize wait my students can just drag and drop this assignment in here and it just gives them the perfect answer I need to think in my assignments like rethink all of that so we’re excited about those um 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 LMS as well as the answers uh be done for them and have some API customers that are ramping up massively and uh revenue is increasing a lot it’s been really great amazing it’s been uh it’s been a pleasure to get to know you and and and build our friendship S as always thank you for making time um it’s uh I think you know 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 um yep incredible week in in
[01:14:01] technology this week Richard uh Saleem thank you guys having me [Music]