SPEAKER_00: all right everybody welcome back to the all in podcast we've got an incredible crew today don't forget to go to our youtube blah blah blah subscribe and make sure you check out freeberg's surprise drop with his hero ray dahlia live on all platforms today how did that come about SPEAKER_03: freeberg little surprise drop just great was talking with ray about his new book which he just published on how countries go broke obviously which country is going broke now for america i think he talks a lot about the historical context of what's gone on with the debt cycles in different SPEAKER_09: countries and basically at the end of the book he has a pretty uh i think important recommendation to try and get the us to roughly three percent of gdp as our net deficit net of all expense including interest expense so that's the recommendation to the administration i think it's pretty timely SPEAKER_10: with the change in administration anyway great topics to talk through and really important book SPEAKER_00: awesome well done and we are super delighted to have in the red throne travis cowan he is the co-founder SPEAKER_11: and ceo of cloud kitchens he also uh worked in the cab business for a little bit co-founder and former ceo of uber and uh yeah we had a great interview at the all-in summit last year and he's back up from his media hiatus he's been in the lab working on cloud kitchens how you doing brother i'm SPEAKER_14: doing really well i i gotta say just like at the summit jason i'm i'm yes it's an honor to be in the SPEAKER_16: presence of such a prominent uber investor absolutely absolutely i mean finally somebody has recognized SPEAKER_18: my contribution the greatness of jacow absolutely i'll mention it three or four times we'll be SPEAKER_19: i'll give you the props you don't have to do it for yourself anymore thank you i appreciate it SPEAKER_38: give everybody a little overview of cloud kitchens and the business and how it's going because people SPEAKER_41: are obviously addicted to ordering food at home and uh it's it's quite a trend yeah i mean the the high SPEAKER_40: level for it the way to think about is it's it's about the future of food what does the future of food look SPEAKER_14: like you go well in a hundred years we'll start way out there in a hundred years you're going to have very high quality food very low cost that's incredibly convenient and they're going to be machines that make it they're going to be machines that get it to you and it's going to be exactly to your dietary preferences your food preferences etc and it just comes to you and it's so inexpensive that it approaches or has surpassed the cost of going to the grocery store that's more of a like a today analogy so you go a hundred years of course that's the thing nobody's going to be making food what about 20 what about 10 and so the company is real estate software and robotics that's all about the future food and if you can get the quality there and you can get that cost down to start approaching the cost of going to the grocery store you do to the kitchen what uber did to the car and that's the thing travis it's like a grind it's like a lot you know bits and atoms in the uber world this is like five times more atoms per bit this is like heavy duty industrial stuff probably more along the lines of like you know where elon goes and some of his companies like they're super interesting tech but you got to grind out those atoms do you see people SPEAKER_46: actually cooking in the future or does it become a centralized service and is it optimized to people's health and what do you think the implications to the food supply are if your vision holds how do you SPEAKER_14: think about all those things look uh people will cook in the future as a hobby i sort of i make a joke at the office i'm like i like horses i love horses but i don't ride a horse to work and it's going to be a little bit like that whereas you can cook it's it's a soulful thing to do it's just very human but you know it's late you know mom gets home late from the office needs to get the kids you know a nutritious meal she doesn't have to cook it now and she doesn't she won't have to cook it and she won't have to go to mcdonald's either it will be high quality and convenient and low cost all at the same time and yes dietary preference everything because it'll be hyper personalized like the way the internet is in content plus plus plus in terms SPEAKER_19: of your specific preferences for what you want i mean you've got these computers rocking oh these SPEAKER_11: robots rocking i think in philly somewhere uh in the lab where they're making balls yeah i mean we're SPEAKER_14: out of the lab at this point we have our machine so we have a machine called a bowl builder that basically makes different cuisine types with bowls so like think of like like sweet greens like what they yeah we're not working with these brands specifically but i'll just sort of it's a good analogy like think of chipotle or cava or sweet green or you get the idea we created test brands that were like those things and built the machine at the same time as we were building an actual restaurant and we built that restaurant to prove that the machine works then we have our customers now touring checking out we're rolling out with five customers in april that are using the machine and the way it will the way it's going to go down is they will come into and we of course we have the real estate so we have kitchens you know tens of thousands of kitchens around the world they will come into one of our kitchens in a facility it's a delivery only restaurant they'll prep the food in the morning and then they will leave and the machine will if people order online door dash uber eats etc they'll order online the way they do build your own bowl exactly as you want and the bowl gets all the ingredients dispensed hot or cold sauce etc gets lidded the bowl goes into a bag the utensils go into the bag the bag is sealed and then it comes out on a conveyor belt and machine gets the bag it goes to the front of the facility gets put into a locker that locker then is sitting there door dash uber eats driver comes waves their waves their phone with an app in front of a camera and it pops open the locker that has the food that you're supposed to that's so cool so like if you're if you're a restaurateur you're the grind of the on-demand meal which is the restaurant world goes away you you basically prep and that's asynchronous from when people order food SPEAKER_61: the machine does the final assembly or what's known as plating essentially like do you think there's a SPEAKER_46: service in the future where my physiology i can share that with you with cloud kitchens and you guys just can always be optimizing my food based on what i know is good or bad for me so first what we do is SPEAKER_14: we serve the restaurants so what happened so chamath you'll be sharing your dietary preferences with uber eats or doordash or sweetgreen or somebody we like our like our customer promise at our company is we serve those who serve others or put another way is infrastructure for better food so we are the either the aws or the nvidia or whatever you want to call it but for food if that makes sense we're behind the scenes we're the infrastructure and so you'll give your preferences it should be a brand SPEAKER_46: like then sweet greens or whomever chipotle that says hey guys share with me like a yes an encrypted hash of your dietary restrictions needs whatever your lipid panel and i and i'll customize this thing and then you enable that yeah it's pretty close to your mouth right you can do that when you SPEAKER_71: authenticate your apple that's really awesome just authenticate apple health when these bowls come off the line and see how i talk it's like an assembly line when these bowls come off the line on the SPEAKER_14: label on the bowl is how many grams of every ingredient is in it plus a picture of what it was before we put the lid in that can be sent to the person while the bowl's on its way via a courier right what do you SPEAKER_63: think travis about this whole maha movement and just the food supply itself so then what how does SPEAKER_46: that change do restaurants embrace more farm-to-table stuff i think look i think what like what we see SPEAKER_14: with supply chains in a bunch of different industries it's just going to get super wired up so right now we're at the point of manufacturing but what happens so you go okay we're doing assembly then you go okay what about prep then you go further upstream and you're like what about supply chain like cisco us foods and then you go further up and you're like well how does how does the mechanization occur on farms and in agriculture and then how does that all get wired up to serve the customer and sort of what they're looking for so like you really can know exactly what kind of wheat was put into that food whether it was organic for real or not like what was the actual field that came from things like this you can imagine like really getting tight about supply chain as it relates to dietary stuff and as it relates to like maha like hell to the yes i mean i ordered a couple different i went to the i went to rfk jr's website and they have like the he has merch he has maha merch i have i have the green maha merch hat i should have worn it today i'm all about it to get the onesie yeah SPEAKER_79: that's amazing the onesie was crazy your bowl builder friedberg you tried to do this right your SPEAKER_82: eats on we had a bowl builder 10 years ago or 2015 yeah 2016. diego saw it he actually visited it when SPEAKER_09: we built it and we designed the system around a canister mechanism so all the food prep was done in a similar sort of like commissary model and then it was loaded in bulk and then put into little canisters and there were 30 slots in the canister yeah spencer and then the canister would move down the device open up and you could assemble bowls with rice and beans and all sorts of stuff the whole thing was automated and we were in the process of building out our first automated store when i actually took a medical leave of absence from itza and ultimately the company did not get it into production but it we had great working demos and it was a very yeah i mean it was just definitely SPEAKER_84: a no-brainer that so you must love this you love this yeah and at the time we were we actually had SPEAKER_85: i'll tell you guys this we actually had a term sheet with chipotle this was nine years ago to SPEAKER_09: actually put this into chipotle stores and then we were in the early conversations with sweetgreen at the time as well and obviously jonathan and team have gone on to develop their own system but you know basically you can reduce so much of like qsr down to this bowl based system and automate it as travis is doing so it's just a no-brainer and it's it's certainly necessary in a time when there's either a labor shortage or labor price inflation that's causing a real issue with the ability and yeah this is the original automats in new york yeah and uh in the early 20th century i love this but yeah they had a commissary behind that wall and they made like plates of food you put in there you put a quarter in you turn the knob and you get your meal out it's the classic that's the classic SPEAKER_14: artificial artificial intelligence right this is like the mechanical turk thing i mean look here's the thing here's the a little nuance that's super interesting about automation in qsr restaurants is that they have an existing brick and mortar that's built a certain way that layout is meant for humans and to for those humans to work in certain processes in exact and very specific way every square inch of that kitchen and that space is is dialed when you go and put a machine like this in it changes the whole thing and so just to get going you've got to like do you've got to like if you're to replace the front line at chipotle you gotta you gotta take out that front line you gotta demo it SPEAKER_91: yeah you gotta put in a new machine that's the challenge that they all had and so now it's like a SPEAKER_14: huge amount of capex my store's down for two to three months and the economics start to not work and by the way i still have to have humans in that brick and mortar and so you know look we have a different take we're in that delivery only model so these are it's true infrastructure for making food behind the scenes for delivery so you don't have these issues and of course our setup our infrastructure SPEAKER_61: these kitchens are designed for these kinds of machines to be in them and vice versa we've designed SPEAKER_82: the machine to be in them when we did this early at itza it was like food delivery was very SPEAKER_09: early we built these itza restaurants that were smaller footprint we had an 800 square foot restaurant that was doing 3 million a year in revenue and it had a handful of people working in it but we were putting about 800 people an hour during the lunch rush through that restaurant SPEAKER_94: ordering custom bowls this was by one market right one market exactly and so by the way did you guys SPEAKER_95: notice that jcal was plugging his product there in the background even though it has absolutely nothing SPEAKER_96: to do with what travis was saying oh welcome back to the show nothing's changed sax is here no one SPEAKER_65: else even noticed that i just heard this voice from above it was the czar of ai and crypto i was SPEAKER_100: like wow descended that's all sit back and listen the czar is back sex any anecdotes you want to share SPEAKER_85: about life in dc how how exciting it's been in the administration the first week it's been amazing i SPEAKER_103: mean it's hard to believe it's only been a week right so you're in the white house or that building next to it do you have an office building you mean the treasury building somebody was talking about SPEAKER_97: there's a building next to it or something i have an office in the uh old executive office building otherwise known as the eisenhower building and then i have a pass where i can just walk over to the west wing if i want to walk over to it there's kind of a whole white house complex behind the gates that the west wing's part of it and the eisenhower building and there's a couple other buildings in that complex it's really cool it is really neat to to show up for work at the white SPEAKER_109: house just saying it's awesome it's like being in a movie or something or a tv show it is really cool SPEAKER_39: you know it's awesome any interesting meetings you can talk about and i mean i know we are here today today to talk about deep seek but any interesting meetings or anecdotes from just the vibes and SPEAKER_11: walking around what's the coffee like is there like a commissary you run into anybody interesting SPEAKER_97: there is a commissary actually in the white house called the navy mess and i think they're just opening up for for business now that is one of the cooler things you could do is you can take people to to lunch at the navy mess oh look forward to it jay cal just invited himself i look forward to it i look SPEAKER_119: forward to taking chamath and freeberg there SPEAKER_120: i'll wear my maga hat all right well let's get started you're here because David Friedberg: you uh we have a very specific he's here because the world is ending jason the the western world is okay the western world's ending and david sachs is going to save it but we had a little bit of a SPEAKER_39: freak out the last week regarding this deep seek if you don't know that's a chinese ai startup they released a new language model it's called r1 and it's on par basically with some of the best models in production in the west like open ai's o1 model but they claim and listen you can trust claims coming out of china you know for what it's worth uh they claim to have done this all for six million dollars only 2 000 gpus for a comparison open ai spent reportedly 80 100 million to train gpt4 which you're all using now and uh sam claims they're going to spend a billion dollars training gpt5 and so that's about seven percent of the cost of gpt4 obviously there are export restrictions on nvidia h100s to china so there's a big debate as to if they actually have h1s or not SPEAKER_11: and uh monday was a bloodbath in the stock market nvidia had the worst day in the history SPEAKER_39: of the stock market in terms of total dollar amount of market cap lost it was down 17 which is 600 billion dollars tsmc was down arm was down broadcom was down so i guess everybody's asking the question how did they do this did they do it and then there's a bunch of debate on whether they stole which is kind of rich coming from open ai which got caught red-handed stealing everybody else's content and now they're crying foul that the chinese stole or trained did what's called distillation of their model in order to build theirs sax obviously you are the czar of ai i'm curious what your take on all this is and thanks for coming well i think one of the really cool things SPEAKER_125: about this job is just that when something like this happens i get to kind of talk to everyone and SPEAKER_97: everyone wants to talk and i feel like i've talked to maybe not everyone and like all the top people in ai but it feels like most of them and there's definitely a lot of takes all over the map on deep seek but i feel like i've started to put together a synthesis based on hearing from the top people in the field it was a bit of a freak out i mean it's rare that a model release is going to be a global news story or cause a trillion dollars of market cap decline in in one day and so it is interesting to think about like why was this such a potent news story and i think it's because there's two things about that company that are different one is that obviously it's a chinese company rather than american company and so you have the whole china versus u.s competition and then the other is it's an open source company or at least it open source the the r1 model and so you've kind of got the whole open source versus closed source debate and if you take either one of SPEAKER_128: those things out it probably wouldn't have been such a big story but i think the synthesis of these things got a lot of people's attention a huge part of tick tock's audience for example is international some of them like the idea that that the us may not win the ai race that the us is kind of getting a comeuppance here and i think that fueled some of the early attention on tick tock similarly there's a lot of people who are rooting for open source or they have animosity towards open ai and so they were kind of rooting for this idea that oh there's this open source model that's going to give away what open ai has done at one twentieth the cost so i think all of these things provided fuel for the story now i think the question is okay what should we make of this i mean i think there are things that are true about the story and then things that are not true or should be debunked i think that let's call it true thing here is that if you had said to people a few weeks ago that the second company to release a reasoning model along the lines of o1 would be a chinese company i think people would have been surprised by that so i think there was a surprise and just to kind of back up for people you know there's there's two major kinds of ai models now there's kind of the base llm model like chatty 4o or the deep seek equivalent was v3 which they launched a month ago and that's basically like a smart phd you ask a question gives you an answer then there's the new reasoning models which are based on reinforcement learning sort of a separate process as opposed to pre-training and o1 was the first model released along those lines and you can think of a reasoning model as like a smart phd who doesn't give you a snap answer but actually goes off and does the work you can give it a much more complicated question and it'll break that complicated problem into a subset of of smaller problems and then it'll go step by step to solve the problem and that's that's called chain of thought right and so the new generation of agents that are coming are based on this type of idea of chain of thought that that an ai model can sequentially perform tasks figure out much more complicated problems so open ai was the first to release this type of reasoning model google has a similar model they're working on called gemini 2.0 flash thinking they've released kind of an early prototype of this called deep research 1.5 anthropic has something but i don't think they've released it yet so other companies have similar models to o1 either in the works or in some sort of private beta but deep seek was really the next one after open ai to release you know the full public version of it and moreover they open sourced it and so this created a pretty big splash and i think it was legitimately surprising to people that the next big company to put out a reasoning model like this would be a chinese company and moreover that they would open source it give it away for free and i think the api access is something like 1 20th the cost so all of these things really did drive the the new cycle and i think for good reason because i think that if you had asked most people in the industry a few weeks ago how far behind is china on ai models they would say 6 to 12 months and now i think they might say something more like three to six months right because o1 was released about four months ago and r1 is comparable to that so i think it's definitely moved up people's time frames for how close china is on on ai now let's take the um we should take the claim that they only did this for six million dollars on this one i'm with palmer lucky and brad gerstner and others and i think this has been pretty much corroborated by everyone i've talked to that that that number should be debunked so first of all it's very hard to validate a claim about how much money went into the training of this model it's not something that we can empirically discover but even if you accept it at face value that six million dollars was for the final training run so when the media is hyping up these stories saying that this chinese company did it for six million and these dumb american companies did it for a billion it's not an apples to apples comparison right i mean if you were to make the apples to apples comparison you would need to compare the final training run cost by deep seek to that of open ai or anthropic and what the founder of anthropic said and what i think brad has said being an investor in open ai and having talked to them is that the final training run cost was more in the tens of millions of dollars about nine or ten months ago and so you know it's not six million versus a billion okay it's a billion SPEAKER_39: dollar number might include all the hardware they bought the years of putting into it a holistic SPEAKER_119: number as opposed to the training number yeah it's not just running it it's not fair to compare let's SPEAKER_128: call it a soup to nuts number a fully loaded number by american ai companies to the final training run by SPEAKER_134: the chinese company but real quick sex you've got you've got an open source model and they've the white SPEAKER_14: paper they put out there is very specific about what they did to make it and uh sort of the results they got out of it i don't think they give the training data but you could start to stress test SPEAKER_61: what they've already put out there and see if you can do it cheap essentially like i said i think it is hard to SPEAKER_128: validate the number i think that if let's just assume that we give them credit for the six million number my point is less that they couldn't have done it but just that we need to be comparing likes to likes yeah so if for example you're going to look at the fully loaded cost of what it took deep seek to get to this point then you would need to look at what has been the r d cost to date of all the models and all the experiments and all the training runs they've done right and the compute cluster that they surely have so dylan patel who's leading semiconductor analyst has estimated that deep seek has about 50 000 hoppers and specifically he said they have about 10 000 h 100s they have 10 000 h 800s and 30 000 h20s now the cost of sacks sorry is they deep seek or it's deep seek plus the hedge fund deep seek plus the hedge fund but it's the same founder right and by the way that doesn't mean they did anything illegal right because the h 100s were banned under export controls in 2022 then they did the h 800s in 2023 but this founder was very farsighted he was very ahead of the curve and he was through his hedge fund he was using ai to basically do algorithmic trading so he bought these chips a while ago in any event you add up the the cost of a compute cluster with 50 000 plus hoppers and it's going to be over a billion dollars so this idea that you've got the scrappy company that did it for only six million just not true they have a substantial compute cluster that they use to to train their models and frankly that doesn't count any chips that they might have beyond the 50 000 you know that they might have obtained in violation of export restrictions that obviously they're not going to admit to and we just don't know we don't really know the full extent of of what they have so i just think it's like worth pointing that out that i think that part of the story got overhyped it's hard to SPEAKER_46: know what's fact and what's fiction everybody who's on the outside guessing has their own incentive right like so if you're a semiconductor analyst that effectively is massively bullish nvidia you want it to be true that it wasn't possible to train on six million dollars obviously if you're the person that makes an alternative that's that disruptive you want it to be true that it was trained on six million dollars all of that i think is all speculation the thing that struck me was how different their approach was and tk just mentioned this but if you dig into not just the original white paper of deep seek but they've also published some subsequent papers that have refined some of the details i do think that this is a case in sacks you can tell me if you disagree but this is a case where necessity was the mother of invention so i'll give you two examples where i just read these things and i was like man these guys are like really clever the first is as you said let's let's put in a pin on whether they distilled o1 which we can talk about in a second but at the end of the day these guys were like well how am i going to do this reinforcement learning thing they invented a Chamath Palihapitiya: totally different algorithm there was the the orthodoxy right this thing called ppo that everybody used and they were like no we're going to use something else called i think it's called grpo or something it uses a lot less computer memory and it's highly performant so maybe they work and strain sacks practically speaking by some amount of compute that caused them to find this which you may not have found if you had just a total surplus of compute availability and then the second thing that was crazy is everybody is used to building models and compiling through cuda which is nvidia's proprietary SPEAKER_46: language which i've said for a couple times is their biggest moat but it's also the biggest threat vector for lock-in and these guys worked totally around cuda and they did something called ptx which Chamath Palihapitiya: goes right to the bare metal and it's controllable and it's effectively like writing assembly now the only reason i'm bringing these up is we meaning the west with all the money that we've had didn't come up SPEAKER_46: with these ideas and i think part of why we didn't come up is not that we're not smart enough to do it Chamath Palihapitiya: but we weren't forced to because the constraints didn't exist and so i just wonder how we make sure we learn this principle meaning when the ai company wakes up and rolls out of bed and some vc gives them SPEAKER_46: 200 million dollars maybe that's not the right answer for a series a or a seed and maybe the right Chamath Palihapitiya: answer is 2 million so that they do these deep seek like innovations constraint makes for great art what SPEAKER_144: do you think uh friedberg when you're looking at this well i think it also enables a new class of SPEAKER_09: investment opportunity given the low cost and the speed it really highlights that maybe the opportunity SPEAKER_147: to create value doesn't really sit at that level in the value chain but further upstream apology made a comment on twitter today that was pretty funny or i think about the right yeah he's like turns out SPEAKER_09: the rapper may be the it's the moat the money it's the moat which is true at the end of the day if model performance continues to improve get cheaper and it's so competitive that it commoditizes much faster than anyone even thought then the value is going to be created somewhere else in the value chain maybe it's not the rapper maybe it's with the user and maybe by the way here's an important point maybe it's further in the economy you know when electricity production took off in the united states it's not like the companies are making a lot of money that are making all the electricity it's the rest of SPEAKER_46: the economy that accrues a lot of the value well you're about to see a big test of this because if openai raises 40 billion at 340 billion that just hit the wire the underwriting logic at 340 billion exactly what you just said freebrook it is the wrapper meaning chat gpt is the next killer app it's getting to a billion plus mao hundreds of millions of dow it's competing for consumer usage SPEAKER_85: that's that's the model that's the model is like consumer usage which puts them on an on a collision SPEAKER_46: course with meta it's the only company that could really impact that because the only company right now that has billions of eyeballs of da use per day and who and by the way zuck said this in his earnings release he's like there's only going to be one company that brings ai to a billion plus people and it will be us some version of that quote is in his earnings release yesterday and then SPEAKER_160: microsoft showed weakness in the cloud and then microsoft's down six percent today and you know i SPEAKER_09: think it's a a window for uh open ai to say we're gonna go up against meta this is it we're gonna be SPEAKER_162: the players what do you and everyone's kind of ignoring google what do you guys think is happening SPEAKER_46: right now between open ai and microsoft because if it's true that this distillation thing actually happened well there's only one place where you could have distilled the o1 model it's on azure so SPEAKER_141: what the hell is going on over there well and there r1 is supported on explain distillation real quick SPEAKER_163: yeah so when you have a big large parameter model the way that you get to a smaller more usable model SPEAKER_46: along the lines of what sax mentioned is through this process called distillation where the big model feeds the little model so the little model is asking questions of the big model and you take the answers and you refine and by the way you can see this nick i sent you a clip you guys can see this i mean it's there's clearly distillation happening nick can you show the clip of the of the deep seek run where it shows the china answer and then deletes it what was winston's job in 1984 right and it sort of starts to go through this whole summary and then the person says are there any actual states that currently do that hold on here it goes it says north korea wait it goes china and then we watch this boom so the reason why this is happening is like you're seeing this chain of thought you're seeing the several layers and then it's catching it after the fact so we know that this is distilled from some other model and my only point there it's the little tongue in cheek is right now when you go and use open ai you're using it sitting in an azure instance somewhere right so this is microsoft's cloud infrastructure that runs it so it begs the question it's not that it's o1's fault or open ai's fault but this distillation happened and i'm not trying to assign blame but typically if this were to SPEAKER_155: happen you'd look to your cloud provider and say how are you letting this happen and i don't think SPEAKER_166: anybody's had a good answer for that well and the cloud provider is hosting r1 now so they're SPEAKER_168: literally undercutting chat gpt and open ai at the same time just to clean that up they're they're SPEAKER_172: hosting their own copy of it right because r1's been when you say they who are you who you're referring SPEAKER_166: to sax microsoft yeah microsoft is hosting their version of r1 which means they are actively subverting their partner open ai and pushing people to a cheaper model well whatever i mean look amazon's David Sacks: going to host their own version of r1 grok has a version of r yeah we have one cerebris just rolled SPEAKER_181: out it's open source now who has r1 on his laptop you know yeah exactly yeah but if it was if it was SPEAKER_182: stolen as um and the ip was stolen as sam is claiming that would be like you'd think he'd be SPEAKER_00: able to call up sate and say hey can you not put the stolen ip on your server and promote it to everybody at a lower cost it just shows microsoft has no loyalty to open ai yeah and they have but SPEAKER_187: you think they would have loyalty but guys what it would take to distill a one like brute force SPEAKER_14: it wouldn't be like oh geez i can't believe it was distilled it would be like such a massive number of calls against an api or against something something that it wouldn't be unnoticed SPEAKER_39: in it well they did actually came out and said they blocked some suspicious activity recently yeah SPEAKER_14: no but they're always doing that they're always that's that's constant you're always doing that SPEAKER_190: that's like you know the old school let me you know go ahead zach let me let me address the SPEAKER_97: distillation point so i i mentioned this a few days ago on on fox news that i thought it was likely or possible that distillation had occurred and there was some evidence for this and it became like a news story and i i didn't even realize that saying that would be news because it's kind of an open secret SPEAKER_172: in silicon valley everyone i talked to they're doing some level of distillation yeah because you SPEAKER_194: need to test your model against theirs anyways yeah and every single person i've talked to SPEAKER_128: basically has agreed that there was some distillation here from open ai now that doesn't mean it was the only thing going on here i mean to be sure the deep seek team is very smart and there were some innovations but also there was some distillation and really this wasn't even a fresh news story i think from the point of view of silicon valley because a month ago we had a press cycle in silicon valley when deep seek's v3 model came out that deep seek v3 was self-identifying as chat gpt when you would ask it who are you like what model are you five out of eight times v3 would tell you that it was chat gpt four and there's lots of videos and examples of this online that have been posted right the point is that we knew a month ago that v3 had been trained on a substantial amount of chat gpt output obviously because v3 was self-identifying as chat gpt and there's two ways that that could have happened so the let's call it innocent explanation is that deep seek had crawled the web and found lots of published output from chat gpt and then trained on that and that wouldn't be a violation of open ai's terms of service or their ip or the other explanation would be that they used the api from open ai and basically you know went to town yeah went to town and there's no way i think based on what we know to prove that one way or another but i know what most people think happened and at the end of the day open ai can probably figure it out and they they've indicated that they think there was SPEAKER_130: some improper distillation here but yeah in the financial times it says open ai says it has found SPEAKER_144: evidence that chinese artificial intelligence startup dc used the us company's proprietary models to train its own open source competitor right that's what i'm referring to so they say they've SPEAKER_46: been very clear about this by the way you have to be sympathetic i think to open ai in this because if you're building a startup you're trying to raise money we've all gone through this cycle guys where it's like there's momentum we celebrate internally the momentum that's what gets you the energy to push your team even further and harder and then all of a sudden it turns out that some portion of that like travis said it well like you're there's probably a chart inside of open ai's offices where you're showing how many times these apis are getting hit right you know how many times these endpoints are getting hit it all looks positive and then you realize that some portion of it was actually bad and trying to undercut your value it's a hard pill to swallow and then you have to Chamath Palihapitiya: course correct very quickly you have to lock down this is one area where security exactly we have not talked about this like you have to lock these models down now you have to lock the endpoints down look in the biden administration if this had happened the first conversation would have been we need to kyc the people that use these models and it's like what are you talking about we don't kyc the cloud if you're trying to use like an ec2 endpoint or an s3 bucket you don't have to all of a sudden prove who you are you just use a credit card and go that's the whole point of why proliferation can happen so quickly but if we take the wrong takeaways from this period there's going to be a bunch of people that'll clamor to like lock these folks down and make innovation go much slower i don't SPEAKER_14: i think that that would be bad here's the other side and totally agree shaman but here's the other side you go through the white paper you see what it is they did what they innovated on yeah the science behind it the thoroughness and you're like these guys are badass it doesn't it does not feel or sound like somebody who took something just when you get through it it could be that it could be that open ai wrote the white paper for them just putting it out there but it's real SPEAKER_88: innovative i agree with that real innovation strong tech you're like this is legit i agree with that SPEAKER_128: but in that paper they're very easy about where the data is coming from and they're they're fairly transparent about everything else they did but they're not really clear about the data and specifically they say that to get from v3 which is the base model to r1 which the reasoning model they had about 800 000 samples of reasoning they were quite unclear about where those reasoning samples came from by the way it is remarkable that you can get from a base model to an r1 with just 800 000 samples but this SPEAKER_46: is the problem like we meaning like the western ai community we've been trudging around on this path where we've been very we had a very orthodoxical approach the only way you can do reinforcement learning Chamath Palihapitiya: is through ppo okay but is that true and it turns out that if you're like a really smart team that has SPEAKER_46: no other choice you move away and you invent your way out of it and so we have to get that example too i think it's technically brilliant some of the things they've done but they also use constraint as a very much a feature not a bug and the the western ai economy has been the opposite so far i think David Friedberg: the best part of this is the fact that sam maltman was supposed to be doing open source he made SPEAKER_39: it a closed source company he stole everybody's data every got caught red-handed he's being sued by the new york times for all that and now the chinese have come and open sourced all the stuff he stole and he's got a real competitor on the original mission of what opening i was supposed to do so i have zero sympathy for him or the team over there i'm glad that this is all going open source it should have been open source and it's better for humanity and the fact that the chinese did it to SPEAKER_146: sam maltman has come up and for him stealing everybody else's content that's my opinion okay SPEAKER_109: but i don't have strong opinions on it it's hilarious does nobody see the irony in this he was supposed to be doing open source for the good of humanity because jacal i will say the models SPEAKER_82: are closed you're right there was there's the lawsuit with scarlett johansson for stealing her SPEAKER_09: voice even when she said no there's a real question and and people have asked new york times and then there's now the question about youtube data being used to train the video models so there's a lot of being on their on their heels a little bit so i definitely i definitely see your point stealing i SPEAKER_218: think yeah i think the the really all the pressure right now i think is on meta because i think meta SPEAKER_46: has to show up with the next iteration of llama that beats and exceeds gemini that exceeds r1 and i think that that is going to be crucial for us to have a counterweight to whatever china is going to put out SPEAKER_221: after this and but i mean jimot it's open source like does it not well so this is so this is my Chamath Palihapitiya: point embrace and extend embrace and extend meta has to embrace and extend everything that these guys have shown meaning like meta's buying tens of thousands of nvidia gpus great but what did this show this shows that actually cuda high-level languages in general i think we've all known that they suck okay and so we've all been going through it thinking that it's like the right thing to do deep seek throws it out the window they use something called ptx what does meta do is critical not to understand they need to embrace this stuff and this is where i think again apologies to the invidiables but it's going to create a more heterogeneous environment and the reason is because there's too much money and risk on the line to go through a single point of failure a chip a high-level framework to get to that chip that's nuts so i think like that kind of like emperor has no clothes SPEAKER_03: moment is upon us well let me ask you another question let's assume that we start the world of SPEAKER_09: ai today so there's no legacy of the last three years and you wake up today and there's this open source model that's 670 billion parameters you can run it on your desktop computer it's completely available everything's completely transparent and i ask you the question forget about all the big companies that are involved in everyone's strategy historically what's the model today to build value here where do you build equity value as a business if you're going to start a company if you're going to invest as a as an investor where do you go the first is you have to build a shim and SPEAKER_46: i think the reason why a shim is really critical is that there's so much entropy at the model level what this should show you is you can't pick any model and the problem is that the people that manipulate these models the machine learning engineers and whatnot they become too oriented to understanding how to get output of high quality using one thing meaning it shouldn't have been the case that we have engineers that can only use sonnet right that's the anthropic model right it shouldn't be the case that people can only use open ai or people can only use llama right now that is kind of what we have you don't have the flexibility to hot swap as models change so if Chamath Palihapitiya: you're starting a company today the first technical problem i would want to solve for is that because tomorrow if it's r2 or alibaba's model or llama i would want to be able to rip it out and put it back in and have everything work and right now we can't do that the answer to your question SPEAKER_39: is the answer to your question is the application layer because this is all going to become storage it's like youtube being built on top of storage or uber being built on top of gps all these innovations are being commoditized and this one is happening faster than all the rest do you want to be in the storage business or you want to be in the youtube business do you want to be in the uber business or do you want to be in the gps chip business i mean they're both decent businesses but gavin baker came on this podcast and said it's the fastest deprecating asset in the world was a large language model he's been proven right they're not worth anything they're all going to be open source they're all going to be commoditized and that's for the best of humanity and now we're going to be on the application level the hardware level with robots and i SPEAKER_09: think that's where the opportunity is travis what do you do what company do you start today if you start a company today given where the world is at given the open source models like what do you do SPEAKER_88: oh i'm getting so excited um look i i think the first the first degree out is it's what you got SPEAKER_14: is there a wrapper company okay so of course maybe those companies already exist and then is there a tools company right so in a funny way even though facebook could be the wrapper they have a tools business that these you know that the that deep seek is basically challenging going full open source and like putting something out there that's really good and what has to happen is meta has to decide like we are going to embrace and extend this we're going to make sure that all the developers come to us that all the cool applications get built here so i think it's like there's a tools business and then there's the wrapper business um and then you know look when ai here's the one thing on the nvidia thing that i would counter with a little bit of what's been said here is like when ai gets cheap you know what's going to happen guys there's going to be a lot more ai right i don't think i think the price elasticity on this one is actually positive so as the price SPEAKER_231: goes down that's the revenue usage everything's going to go up through the roof this is the history of SPEAKER_88: tech forever since like bill gates said i don't know what to do with more than 64 kilobytes of SPEAKER_190: memory like yeah you know the question is did we cheap oil cheap oil in the united states drove the SPEAKER_09: industrial revolution right and like when we started discovering oil suddenly we were able to build factories and make stuff that we never imagined possible and so then you're like okay ai is like SPEAKER_14: you know it's going to get cheap it's going to be oil but it's also going to be specialized for different tasks right like you're going to start getting into nuances of like what is the invest the investor ai look like what does the autonomous car ai look like what is the uh google search i'm trying SPEAKER_238: to figure some lawyer yeah i look like yeah yeah so it could go vertical and siloed siloed air quotes SPEAKER_97: absolutely i'm saying yeah so there's a thing called uh jevons paradox which kind of speaks to SPEAKER_128: this concept satya actually tweeted about it which is the it's a economic concept where as the the cost of a particular use goes down the aggregate demand for all consumption of that thing goes up so the basic idea is that as the price of ai gets cheaper and cheaper we're going to want to use more and more of it so you might actually get more spending on it in the aggregate that's right because more and more applications will become cost economically feasible economically feasible exactly yeah that is i think a powerful argument for why companies are going to want to continue to innovate on frontier models you guys are taking a very strong point of view that open source is definitely going to win that the leading model companies are going to get commoditized and therefore there'll be no return on capital and basically continue to innovate on on the frontier i'm not sure that's true you know for one thing the the r1 model is is basically comparable to o1 which which open ai released four months ago and was training on internally call it nine or ten months ago so open ai is on o3 now its frontier is ahead of where r1 is anthropic and google i think have things in the work and even meta that may be ahead of where r1 is so i think r1 or deep seek's done a good job being a fast follower here it's not clear that this is the frontier and those frontier model companies now having seen what might have happened with distillation have a pretty strong incentive to make sure that doesn't happen again and they're going to be taking countermeasures i mean there's a question of like how much you can do to stop it but i think it's a little premature to conclude that there's no reward for being at the frontier anybody SPEAKER_242: have any other questions for sacks before we drop him off to go back to serving the american people David Sacks: before we drop him off one final point on on the whole open source versus closed source look i'm not SPEAKER_128: going to take sides in that but i i think that it's a mistake to just view what happened here as oh it's this like plucky upstart that's like doing the community a huge service out of the goodness of its heart you know it's basically open sourcing oh they stole it they stole it it it's a chinese come on you still have this huge geopolitical aspect to it right and deep seek is a chinese company and they're trying to catch up and so if you're if you're behind you're trying to catch up then open source is a strategy that actually really makes sense for you and you know they're trying to basically undercut the leading american companies and i i don't think they did it with six million dollars i mean they have massive resources behind them so i think some of the the pro deep seek vibes i think are they're a little bit naive you know in silicon valley it's like that's only the uh people who worked for sam previously and quit who feel that way i think there's a lot of like support for deep seek yeah silicon valley because again people think that they're doing this huge service for the community and i think it's a little bit more self-interested in that than that it could be both SPEAKER_38: right i mean there there is a theory that they're trying to undercut and neuter the lead and at the same SPEAKER_39: time there's a bunch of people who believe in open source and nobody should control this and certainly not sam maltman should be the person who controls it so two things could be true at the same time david thank you so much for coming on we appreciate it and uh thank you for all thank you for coming on your own podcast thank you david i know that this is uh and now we're going to talk SPEAKER_258: about a bunch of other crazy stuff your scholar gentleman david yes thank you all right thanks to SPEAKER_39: david sacks for coming in and uh you know i guess let's open up the aperture here and talk a little bit about relations with china we're obviously in a bit of a cold war with them we have tariffs we have SPEAKER_11: taiwan and then we have uh the sort of trade war going on here with uh exports of h-100s where do we SPEAKER_39: want to start gentlemen and you know travis you've got some a deep you're one of probably five american entrepreneurs who ran an at-scale business with uber and the dd relationship in china so you have SPEAKER_11: a unique position of understanding business in this along with maybe tim cook and elon are the only other two people who've really had an at-scale business there maybe disney they have disneyland SPEAKER_264: there yeah what's your take on the relationship and what's going on here geo how is china going to SPEAKER_09: operate differently than the u.s travis from your experience your point of view tell us a little bit about the culture and business ethics in china particularly as it relates to ai okay so okay so SPEAKER_14: look we i had this thing this is i'm going back almost 10 years here uber day we're running uber china and i mean i cannot there's no way i could express the frenetic intensity of copying that they would do on everything that we would roll out in china and it was so epically intense that i basically had a a massive amount of respect for their ability to copy what we did i i just couldn't believe it we would do real hard work make it we dial it and it would be epic and it would be awesome we'd roll it out and then like two weeks later boom they've got it a week later boom they've got it and of course i use that to drive our team and there's so many great stories i mean we had we had like 400 chinese nationals in silicon valley at our offices in san francisco we had a whole floor for the china growth team and it was primarily chinese nationals we had billboards on the 101 in silicon valley in chinese uber billboards to join our team in chinese to to serve the homeland right um it was like an all-out war it was really epic it was epic and by the way when you went to that floor in our office you were in china like they rolled china style like the desks were literally smaller like the density of the space was it was china okay so but what happens is when you get really really good at copying and that time gets tighter and tighter and tighter and tighter and tighter you eventually run out of things to copy and then it flips to creativity to creativity and innovation now at the beginning you you know it's sort of all over the place like the kind of innovation when it was new was like what you know you're like really but as they exercise that muscle it gets better and better and better so if you want to know about the future of food like online food delivery you don't SPEAKER_250: go to new york city you go to shanghai right what's an example like of like something really innovative SPEAKER_223: there doesn't doesn't meituan do drone delivery and stuff like here's an example if you went to SPEAKER_14: offices like let's say shanghai um beijing any of the major cities hongzhou etc the office buildings have hundreds of lockers around their perimeter so that everything that you get whether it be food or anything else but especially food is just the the couriers drop them off in these lockers in the uh at the office buildings and then there are a whole other set of people that are sort of like inter office runners runners that then bring it to your office as an example like and when you see it you're like and it's epically efficient and it's you know they're taking advantage of their economics on labor and things like this it wouldn't exactly work that way here but a lot of the innovation you will see coming out on uber eats or doordash like the stuff that's coming out now is stuff that existed three years ago four years ago in china maybe longer so like eventually you cross that threshold of copying and you are innovating and then you're leading and i think we see that in a in a whole bunch SPEAKER_270: of different places yeah here's a look at these smart lockers that you can see here just available SPEAKER_39: for sale when you go online but yeah these things are crazy and you've experimented with those as SPEAKER_14: well didn't you have like a commissary concept in dtla well look we okay so we got a couple things so we have in every one of our facilities and we've got you know hundreds of them we'll have lockers there so the the courier then waves their phone in front of a camera the right locker pops open they get the food from there and they go the courier pickup is asynchronous from production of food you know you don't have lines anymore there's no more lines which then speeds up delivery shortens the amount of time shortens is it reduces how much money you spend on couriers and we've got a whole other thing this doesn't work and it probably wouldn't work in china because well for a lot of reasons but let me explain what it is it's called picnic where if you are in an office building you order food you go to a website you order whatever it is from a hundred different restaurants those restaurants happen to be in my facilities and there'll be one courier that goes to one of our facilities and picks up 50 orders at a time brings it to an office puts it there's a shelf on every floor you get notified when your food arrives and it arrives the same time every day and you just go to the shelf get it on your floor and dip that right back into your meeting saving people time at the office giving them selection on food especially in food deserts but even going like there's a sweet green right down there in my current in my office right now i could say 20 minutes by just using our own service versus doing that and you get at the same price because the courier economics the courier is bring is delivering 50 orders at a time so courier costs go basically to zero what do we think of the um SPEAKER_11: of the export controls here should we chamath be maybe banning more h-100s or other chipsets going SPEAKER_46: there or is that futile i don't know the answer to that and i think that's i think sax and president make a good decision but here's the curious case of the export controls nick i sent you a couple of tweets if you want to just bring this up so the first thing that people are claiming is that deep seek is getting access to a bunch of nvidia gpus using singapore as a backdoor so essentially you create a singaporean shell company you place an order with nvidia nvidia fulfills that into singapore and then the chips go someplace and so there's a bunch of examples where people are saying that you're talking about up to a quarter of all nvidia revenue goes into singapore and the speculation right now is at 100 of those then go into china which is an enormous claim because that's a huge amount of of nvidia's revenue now the interesting thing is if you actually try to understand well maybe that's not true and maybe it's sitting inside of singapore this is where that kind of unravels so just to be clear like singapore is about 250 or 260 square miles like it's like a small small place also the tick tock headquarters and i tried to find out how many data centers are in singapore and it's about a hundred and so you would think that okay well what does that mean 100 could mean anything but then you look at the energy and they publish that and all of those hundred data centers consume about 876 megawatts so these are small data centers right and the entire industry is like a one and a half two billion dollar revenue business so i do think that sacks and the administration are going to have to dig into this and figure out what their opinion should be but there is clearly a ton of of these chips going into singapore i don't think anybody knows where they end up and the question is what does america think about that and why did we implement these export controls in the first place and if there's a SPEAKER_09: simple back door how do you want to react if the u.s finds a path i mean let's talk about like what happened with sanctions in russia and other prior kind of sanctioning efforts around the world but as you kind of close the the floodgates and close access the buyer or the receiver of those goods or that capital are gonna look elsewhere they're gonna look to create a market somewhere else and so if we do cut off access to nvidia chips we do cut off access to us exports are we not kind of recognizing that the second order effect of that is that china will take ip that they've stolen copies that they've made to travis's point and develop and build out their own fabs and they'll find ways to copy the asml technology and you know at the end of the day there's a lot to put together and i know it's deeply technically complex but if ever there were a group of people in the history of human civilization to pull it off it's probably the modern chinese to be able to say let's go build our own it's worse than that our SPEAKER_63: own infrastructure this is a great point but it's worse than that the models today are capable of SPEAKER_46: designing chips for you that don't rely on the most complicated technologies that asml creates i mean look one of the luckiest things that happened to grok is we designed our chip at 14 nanometer which is effectively in the spectrum of technology like vhs and beta so we chose a simple simple technology stack to build towards the latest cutting edge chips at like two nanometer that use these complicated asml machines it's not clear that the yield is actually that good so why would you spend all that money and if china is forced to engineer its way around it yeah freeberg the answer your question is they'll use these models to design chips that can be manufactured in simple ways and they'll make simple stuff SPEAKER_03: so this is not sure it solves the problem is my point well it doesn't and this is why i think like SPEAKER_46: it doesn't solve the real problem which is how do we incentivize people in america to really out SPEAKER_09: engineer and out innovate competition or ai ushers in an era of extraordinary abundance and that abundance ultimately reduces the the drive for conflict and things are better off or the other Chamath Palihapitiya: version as well is that china could just bear the cost as a central authority of building an SPEAKER_46: incredibly great model right and they will spend all the money and then they will tell the chinese companies you can distill from this model for free because we have a golden vote and a seat on your board anyways which is effectively de facto what happens if you get big enough in china so there's that possibility as well where one central authority bears the capex of creating something that then everybody else can can draft off of and let's talk a little bit about opening eyes uh SPEAKER_00: they're in washington asking for money now is that the uh is that the concept now is that the our SPEAKER_82: government should back the rumor today was they're raising 40 billion at a 340 billion dollar pre-money SPEAKER_09: with masa potentially being the lead i would love travis's read on this because travis has taken large money from from masa in the past and has been through this but how does he think about and make this decision obviously we all know and i mentioned you guys the meeting i had with him last summer where he basically kicked me out of the room because my company is not generative ai like someone said you should go be with masa so i'm like sure i'll sit down with him and start talking and he just like looked at me and he's like uh this is not generative ai i uh only do generative ai i think your company will be very successful you will be very successful goodbye and he just walked out and that was like the end of everything so great yeah well that's all he's doing now so this is the SPEAKER_14: big bet right so okay so i need to i need to bust a myth i did not take money from masa so he begged me to take money for years and we did not take it because he is a he's uh what's the word i'm looking for he's a he's a promiscuous investor so once he once he invests in you you should probably count on him in using your information and investing in all of your competitors at least that's historically what he's done so i didn't go there but then he just kept investing in all my competitors and they kept subsidizing these markets and then i'm like maybe i should have just saturated soaked up the money that was there so the one of the things you should think about like when you look at like oh is open ai taking a lot of money from a masa type situation is it's a little bit of like a double-edged sword is if you don't take that money it goes somewhere else but if you do take that money just know that whatever intelligence they get when they go through the process of giving you the money and maybe hanging around the board or who knows what is going to be used to do other things and that is the nature of the masa machine so you're damned if you do damned if you but you got to pick and if the money's going and it's flowing and and access to capital is a strategic competitive weapon or advantage you must you must play ball now we were able to we we we did stuff with the saudis before even vision fund existed they stroked a three and a half billion dollar check when that was like SPEAKER_295: the biggest thing that ever happened so we were okay with not having the masa money but that masa SPEAKER_09: money then went to all of our competitors door dash and so in this open ai context travis i mean like just knowing what you know about ai is this going to be a competitive advantage for sam to raise 40 billion where does it go when he's up against we don't know what in china SPEAKER_14: microsoft alphabet and meta well look i think this goes to some of the things that chamath is saying which is like if if constraint is the mother of invention or or whatever that that euphemism is the the the aphorism is if that's the case you get into a real weird spot when you get over capitalized over capitalized in the in the uber model like the war was subsidizing rides for market share essentially being the wrapper for transportation and using the parlance we were using earlier to in the in in this discussion so it was necessary you're screwed if you don't the the question is is do you get to this place of over capitalized too big deal too bureaucratic too loose too weak too soft and with when you have an open source model that's very smart and it's a thousand flowers blooming lots of innovation happening everywhere could be an overwhelming force uh now i think there's going to be different sectors treated different ways we're like going full stack in certain industry sectors is going to matter and then in other places having like a very sort of chaotic everybody does a little slice it's going to be okay in other places and i i think we could probably spend days or SPEAKER_134: hundreds of dozens of hours just talking about the nuances there you know well it seems like there's SPEAKER_09: some degree of relationship between the stargate announcement with masa and sam standing up there with larry and then satya showing up in the conversation as well and this raise and the idea that more hardware more infrastructure faster creates a moat and i guess that's the real thing you have to believe which becomes harder to believe in the context of what happened in the last week i personally think that these models are and i've said this for a while it doesn't make sense to have one large do everything model this mixture of experts architecture ultimately you can kind of think about taking a large model making two copies of it and then trying to shrink each model down to whatever the necessary so that you run two models in less frequently meaning that that combination of two models uses less power and takes less time and then you do the same thing again and you shrink it down to four and then 12 and eventually you have lots of smaller models some of which in some cases are experts at one thing like doing mathematics or reading or writing but the reality is we don't know how whether humans have kind of thought about the world the right way that the ai may resolve to having smaller expert models that we don't really understand why that's the expert on something but you have a network of very small kind of things that work together and that ultimately leads to a like commoditization not just in kind of model cost and in development and runtime but also in like what's needed like do you really create much of an advantage by having all these data centers SPEAKER_250: yeah that's the key this is the key point i think freeberg is you're not going to get an advantage by having more h100s at a certain point and the actual advantage is going to be in the ip and owning SPEAKER_11: content and the really smart thing to do data for somebody to go buy reddit quora the new york times SPEAKER_39: the washington post and disney and take all that ip and then not allow other people to use it sue the SPEAKER_88: hell out of them every time they try washington post off that list but yes but i'll say the new SPEAKER_305: york times comes off the list too well whatever i mean all those archives are definitely going to SPEAKER_304: be what would be great about those is you could then like a patent troll then tell anybody else who's absorbed new york times stories historically or disney and you could just sue the hell out of SPEAKER_126: them and then you've got the best most proprietary one and you're just you're describing text so SPEAKER_160: you're describing text content which is a fraction of where also this is important so video i think you SPEAKER_85: can recognize that google's youtube content library is probably 100 to 200 times larger than the rest of the internet combined but they don't have the right to do it well they do actually so jason you're such SPEAKER_190: an old-school copyright guy you're such an old-school media guy by the way sorry i believe in artists SPEAKER_94: and their right to content yeah we've had a series of conversations that i i feel very confident to tell SPEAKER_85: you that they do have the right in a good chunk of that content not in a lot of the copyrighted content that the big media companies have given them but a lot of user generated content they do have the right and they are using it and they're legally doing it and then there's the separate kind of body of content which i think comes for example from tesla tesla has an extraordinary advantage that they were really pressured to put cameras on everything years ago and that gives them this ability to build models that do self-driving so i think that there's a lot more data advantage that arises in certain industry segments than others and that's where the moat will lie and that moat will SPEAKER_09: allow you to actually build better products that get you a more persistent advantage in gathering more data that's ultimately where i think this resolves to it may not necessarily be about who's got the biggest data center SPEAKER_14: network yeah i mean here's the thing guys at some point the amount of data becomes the long pole in the tent at some point the quality of the algorithms becomes a long pole in the tent and more compute is not going to change that we i don't think we're there yet that's the one thing that counters the cheap ai means more ai is is there enough data and or algorithms to make the more ai to make it work and i do agree with the the siloing it and getting expert and getting better in these ways um but i think this is an interesting sort of trade-off between some of these these variables SPEAKER_00: i got just got offered 2500 bucks to put angel my book into chris harper collins did a a deal with uh microsoft and so i'm doing 500 per year i think it's for three years is the license and they just did this blanket license for every book they didn't look at yourself they didn't look at how desirable it was it was just like a blanket deal everybody gets 2500 bucks per book for three years and i think i'm going to just do it just to support proper licensing so that people can start going down uh this path but let's get into doge it's been a i think we're in 10 days into this administration and um SPEAKER_11: trump formally established doge the department of government efficiency in an executive order SPEAKER_39: apparently elon's been spending a lot of time at the offices bunch of wins doge is claiming on the interwebs to be saving american taxpayers around a billion dollars a day that's three dollars for every american every day about a thousand dollars a year in savings for each us citizen and they claim they can triple this and so for family five that'd be about what fifteen thousand dollars a year maybe sixty thousand dollars during trump's second term we got 36 trillion dollars in debt have fun with some numbers there if you like but the key announcement was a very similar to the twitter execution the ability SPEAKER_11: for people to resign done in a very kind way eight months of severance ish is being offered to federal SPEAKER_39: workers they expect five to ten percent of federal workers to take this buyout and it's um i mean this could be something like a hundred billion dollars in savings eight months of severance um is not SPEAKER_11: actually a legal concept that you can do so these are some sort of buyouts and there's obviously some hand-wringing about it but i think they're off to a good start they've also been canceling leases SPEAKER_39: as we talked about you know pre-election there is so much space not being used that the federal government is terminating a ton of stuff they own and going to sell it and consolidating folks and at the same time all of this is happening everybody has to return to office who wants to go first here with uh you know the sort of first 10 days of doge i see some eggplant emojis in the group chat first 10 days how excited chat what's that about i'm adding yeah how are you not in the group chat SPEAKER_328: literally every time one of these hits the group chat it's just hilarious eggplants people are like SPEAKER_330: oh my god we're not earning tax money dollars and the eggplant always comes with freeberg first SPEAKER_101: i'm outing him as an egg planter i'm a i'm a i'm a big doge eggplant guy oh so much eggplant SPEAKER_39: so freeberg tell us about how much eggplant you love this there's nothing that i would say is SPEAKER_09: particularly surprising in the first week a lot of this was kind of talked about leading up to the inauguration vivek and elon published their piece in the wall street journal a couple weeks ago they talked about the mechanisms of action that they could utilize to kind of drive reduction in cost one of which was come back to the office another one of which is you know giving people a buyout offer and by the way the buyout offer is not new bill clinton did the same thing during his presidency yeah if you guys remember when he tried to balance the budget get to a surplus which he did successfully and his intention was to actually reduce us death to zero by the year 2013 and he had a very specific economic and fiscal plan for doing that which he put into place incredible era i think we're seeing them take the actions that they said they would do they said they would demand to employees federal employees come back to the office and they assumed some degree of attrition from that and now the buyout offer and we'll see how far things go with the courts with respect to their ability to stop a legislative or statutorily mandated spending there's a big question mark here on how much authority the executive branch has in stopping spending and how much they're not allowed to stop because it's demanded by law it's demanded by congress in acts or laws that have passed and so that's going to be the big test here over the next couple of months a lot of lawsuits will fly the courts will ultimately adjudicate and we'll see how far the doge intention can take things and then there's a separate set of efforts around legislative action here there's about a two trillion dollar annual deficit right now in the united states um federal government two trillion a year and if you look at the the dalio book on why countries go broke you know there's a pretty simple kind of arithmetic in there which is not complicated it's just at the end of the day the u.s needs to get our federal deficit down below three percent of gdp which means we've got to cut about a trillion trillion one of spending if we can do that then we're in kind of a more economically sound place by the way a really important point which is in the dalio interview as you cut spending interest rates will come down because right now there's a pretty significant sell-off in treasuries and a lot of risk associated with the u.s's ability to deliver its debt obligations over the next 30 years which is why 30-year treasuries are at five percent right now even though the federal reserve is cutting rates the rate on treasuries is going up people are still selling off treasuries SPEAKER_337: that was also inflationary it's also inflationary dave that's right for sure and so as we cut SPEAKER_09: spending we also will see that the intent that the there will be less inflation and the u.s ability to pay back their debt obligations over the next 30 years goes up so the rates will come down and so there's actually a really nice kind of cyclical effect as these cuts start to come SPEAKER_85: into play the rate at which you can make the cuts actually affects the number the amount of cuts you have to make the faster you make the cuts the less you have to cut and that's a really key kind of principle going into this which i think we should expect a big whirlwind of cutting in the next couple of months or an attempt to the courts will adjudicate what needs to be legislated and then they're going to go to congress and start to try and get some of these cuts in but i will tell you once again after our visit in dc last week there was not a single member of congress that i spoke with SPEAKER_09: who views cutting to be a mandate for them in the laws that they're trying to pass they all SPEAKER_14: have a very different kind of agenda than doge right look this is this is really one of those interesting things where it's like the difference between legislature and executive branch is like doge is really bringing it to life is like what powers and controls does the executive branch have to spend and not to spend and especially to not spend when it's been legislated to spend this is where the action is like there's no law that says you know you can give a bunch of folks eight months of severance and they're gone and you don't replace them there's no law that says that the executive branch and again i don't know that all the the laws sort of the rules or laws about whether you know how they go about doing it but let's say presumably they're doing this and there's some legal backing behind it like they just go and do it and now they're not spending money if it was really hard to hire people and they could even make it harder to hire people do they do they fight bureaucracy with bureaucracy that it's harder to spend hard to hire people harder to procure certain things that you're supposed to spend money on you can reduce this spend through a lot of very SPEAKER_194: interesting nuanced friction rules that they're in control of yeah some friction could slow SPEAKER_39: things down they're talking about putting competency tests in they're talking about giving people reviews and maybe they have to hit some standards and the gentleman's riff i mean when you force people to come back to the office you're going to lose five ten percent of people and ten percent SPEAKER_189: take the buyout and now all of a sudden we're saving things i mean it'll be interesting to see SPEAKER_14: if it's five or ten percent on rto i mean that yeah it could be a lot more i mean what i'm hearing about these buildings is that they are super super empty like next level empty and uh let's just say SPEAKER_134: i'm really glad i don't hold it like i'm an owner that has a bunch of leases yeah to the to the SPEAKER_39: the federal government right now yeah oh the government and you know what the interesting thing about those leases i was talking to the team at density which does people counting in buildings so they obviously um you know are very interested in that the government is such a reliable yeah client that they're all on one-year leases so people don't you know do what they do at startups we just force them to do five or ten years because they know hey this company could go out of business they're just like yeah yeah we're just on a rolling year-over-year lease so you can actually just cut these it's gonna flood the market chamont your thoughts on also the stopping of uh because they're obviously going for it they stopped all payments which is a a part of the playbook i saw on twitter up close and personal which is hey let's let's turn off subscriptions and see you know if anybody's using these subscriptions basically obviously a judge got involved in that but aid going to other countries you know we're just starting to look at what are we actually sending to other countries and for what purpose and then there's a naming and shaming and maybe appealing to the public through social media and saying hey do you want this money going here when hey we have tragedies in our own country that need to be solved we have health care we have houses burned down we have infrastructure and so maybe you could talk a little bit about hearts and minds and winning those and SPEAKER_63: what your general take is so far i think that we have to remember that we're only nine or ten days into doge so the fact that we're already at a billion dollars a day is really incredible and there has SPEAKER_46: really been no discernible impact there has been a lot of fissures of fake news and misinformation but the real impacts have been negligible to none since they started making those cuts i think that doge is a three layer onion so layer one is the people we have now given a pretty generous offer to folks and i think elon said it it was like basically the maximum allowed by these contracts but they tried to do a very good thing there the second as you guys just said the second layer of the onion is going to be the infrastructure all the buildings all the physical plants that the government owns and operates that may be empty that may be idle and getting them back and into private hands so that they be they can be repurposed that's going to save a ton of money but both of them will pale in comparison to the third layer of this onion which is the it and the services and the spend and what i mean by that is when you read how the department is set up at the center and nucleus of every single one of these doge teams is an engineer and i think the reason is that they can get into these systems of record and start to trace where the money is going and i think when you start to uncover through forensic analysis where these dollars are going and how it's spent that's probably how you're going to close the gap from a trillion to i and i suspect to be honest it could be more than two trillion dollars when it's all said and done that is an enormous amount of waste and it's unproductive so i'm very SPEAKER_45: excited for what happens over this next little while just the the transparency is going to be incredible SPEAKER_14: guys just for kicks check this out right 2009 if we took if we took 2019 spend right the year before cove and put it up against 2024 revenues 500 billion dollar surplus wow that's versus versus the one and a half trillion dollar deficit so it took two trillion dollar swing on like uh four years yeah on a four trillion dollar budget that's all waste well a lot of it's great remember we've got a trillion dollars a year of interest payments now i mean this is guys this is the thing like there's two deflationary things that we need one is doge and two is where ai is going to take us if it really does its thing and that will keep us in an okay spot economically but like we gotta this spend has to go SPEAKER_231: or we're in we're in sort of like we're in greek greek territory if that makes sense yeah and i think SPEAKER_55: this is um the popular support for this is pretty incredible i'll just go through a couple of numbers SPEAKER_39: with you you know looking at what people agree with that trump's doing early on and what they disagree with you know obviously we talked about it last week chamath pardoning the january 6 protesters and you know ending requirements for government employees to report gifts that's sort of like the supreme court thing these are tremendously unpopular and then if you go and you look at downsizing the federal government and uh imposing a hiring freeze and requiring all federal employees to return to an office these are incredibly popular and elon tweeted these uh these graphs out as well so right now you have trump at the apex of his political popularity and you have these issues specifically in a very polarized time as incredibly popular he's also done an incredible job with the border that's another consensus-based issue so trump now has downsizing the government and controlling immigration and getting rid of violent immigrants as incredibly popular parts of his mandate and that's the big win for him if you look at his popularity trump is massively more popular than he was the first time around he's at 49 compared to last time 44. he's still the historically least popular president ever so my point in all of this is when you see trump doing things like his meme coin or you know taking on pete buddha judge today all that kind of trump 1.0 negativity grifting that's the stuff that's going to derail this but the stuff that's not going to derail it is focusing on the trump 2.0 agenda and that is as somebody who was a never trumper as you all know in the audience and now somebody who is supporting him relentlessly that margin that extra 10 percent of people who support him right now is me and other folks who are looking at the people who put around him he has to stay with the 2.0 agenda as hard as it is and stay away from the steve bannon agenda and the grifting those are the things that will take this all apart so that's my appeal to them i told everybody i'd give a letter grade i give him a b so far could do better but pretty good less of the meme coin less of the drug you know we have to make sure SPEAKER_00: that we're not dragging dishwashers and teachers and people who've been here 20 years out of the country and it's going to be a very deaf important um approach here if this is going to be sustained and i think it's a coin toss if he will be able to maintain his popularity and what he did today with this like i don't know if you saw the pete booty judge he was attacking him over this tragedy that's SPEAKER_126: the kind of stuff people don't want less of that please more of the doge that's my little rant can SPEAKER_85: we talk to travis about waymo now travis can i ask have you taken a production waymo yes what do SPEAKER_147: you think about it and do you think that's the future of transportation and how does uber play into the uh self-driving car business now i mean look it's funny because as you guys know back in the SPEAKER_14: back in the day 2015 16 17 we had our own autonomous vehicles out there and i remember the first one of ours that i took and i got in the back and all i had was a stop button a big red stop button that i could push if things got weird and i remember it was in pittsburgh where we had our robotics division and autonomy division at uber and i got out of that car and literally it's like i got off a roller coaster ride like my legs were i could not stand straight like i was like a little wobbly because i was so freaked out and the adrenaline was pumping you get in a waymo today and it's like you're not even thinking twice you're just like it's all good you just get in you get out now part of it's just the normalization it's like it's just working and it that normalizing matters in terms of the psychology around it is it we're just there so it just works now is it a optimized experience for ride sharing no like the cyber cab is sort of the ultra sort of destination for what it means to get transported across the city in a vehicle that is not meant for a human to drive no steering wheel you know folks potentially been facing each other you know just a whole bunch of different formats the the technology works we know that there are different ways to get to the technology i think that the probably the most interesting thing that we should be or one of the most interesting things to be thinking about maybe there's a few first is a cheap ai makes cheap autonomy okay so if as as cheap ai gets out there and proliferates and gets broadly distributed we should expect autonomy gets easier and easier and easier and you see some of the stuff that's happening with tesla and fsd their new models are like i think in a three month period he they went up like 10x in terms of performance meaning in number of miles per per human intervention like they're seeing you know that's the thing that elon's seeing right now because cheap ai cheap good ai makes cheap good autonomy and that's a thing we need to connect the dots on i think the thing then you go one level past that you're like okay there's the possibility literally that autonomy just gets easy and commoditized similar to what's happening to ai the next part is okay you get the hardware you're like okay manufacturing's hard that's interesting that could be a long pull in the tent i think that that could be a place where tesla of course has huge advantage you then look at who are waymos partners are they getting set up to do the right kind of manufacturing and get scale of cars out there but then there's like this dark horse that nobody's talking about which is it's called electricity it's called power and all these vehicles are electric vehicles and if you said yeah i just did some like quick back of the envelope calcs if all of the miles in california went ev ride sharing you would need to double the energy capacity of california right let's not even talk about what it would take to double the energy capacity in the grid and things like that in california like let's not even go there even getting 20 more 10 more is going to be a gargantuan five to ten year exercise you know look i live in you know i live in la it's a nice area in la and we have power outages all the freaking time because the grid is effed up and they're sort of upgrading it as things break that's literally where we're at in la one of the most affluent neighborhoods in la that's just where we are so i think the the sort of the dark horse kind of hot take is combustion engine avs because i i don't know how you can go fast getting av out there really really really massive SPEAKER_38: with the electric grid as it is what do you think about regulation in this regard because obviously SPEAKER_39: there was the cruise you know a person got hit by a regular car they dragged it the whole thing imploded we had uh at uber the um the tragedy in arizona where somebody was playing candy crush when they were a safety driver you know what what is your outlook on this stuff rolls out and somebody gets hurt and then that you know tens of thousands of cities that you brought uber to how receptive SPEAKER_38: are they going to be towards this and what do you think the regulatory framework will be like SPEAKER_231: you know i think similar to how you get normalized it's like you're used to getting in a car it's SPEAKER_14: normalized psychologically and in the sort of public sphere the public mindset you get used to it so like we're getting to a place where these vehicles are provably safer than human driven vehicles so yes there are mistakes but they're just provably safer and people are just getting used to it and that's a big part of the cycle so i think we're getting out of the hysteria and we're getting into like yeah it's just great like talk to people who are using it and they feel safer from uh of course like i i feel like we're going to get in less accidents but also i feel safer because there's like there's less chance of like an interpersonal problem that does happen especially you know late at night you know when people are out partying and things like this there's just like there is a level of safety on many different aspects to these vehicles yeah for the drive yeah there's like there's there's safety SPEAKER_38: aspects across the board sure right what do you think about byd and like you sort of mentioned everybody getting to autonomy at the same time obviously waymo's got the biggest lead tesla's SPEAKER_39: behind them byd and about 10 other providers are out there doing this does does you know do 10 players get there at the same time and then it's just who can incorporate these into their network and what do you think of the strategy that uber is doing of hey we've got these eight partners we'll take everybody into the network and we'll manage people vomiting the back of cars cleaning them and charging SPEAKER_14: them so look i think the big issue you have with anything chinese is will you be allowed to bring it in the us just period like you maybe kind of can now what happens with tariffs will there be blocks and bringing this kind of technology into the us what happens there i think that's a whole thing the bet that uber makes is that whether consciously or subconsciously that's like will ai will cheap democratized ai happen and if so does that make cheap democratized autonomy then you've got to line up your physical sort of hardware partners the car manufacturers then you've got to say okay is the electricity where it's at and are there other bets to make to make sure that i can charge my cars so like there is a huge real estate play here and fleet management play of like how do i electrify these plots of land known as parking lots and also set them up so that robots can clean cars in sort of a very very efficient way there's like a whole when you talk about that's super interesting travis SPEAKER_85: that's like it's almost like the idea that we all talk about today is data centers and data centers SPEAKER_09: need their own power substation yeah in order to meet the power demands but if if we do see a world of robotics automation generally and we've got these kind of moving robotic systems in our world they need to have a similar sort of like power demand met that probably looks like hey they all go into SPEAKER_85: their their recharge building and they get recharged whether they're a car or a humanoid robot or a food delivery robot on the sidewalk or whatever you know and they just kind of get recharged huh robots need SPEAKER_46: actuators do you know what you need for an actuator or permanent magnet you know what you need for SPEAKER_380: permanent magnet rare earths who's the rare earth king x china greenland let's go so so guys i think SPEAKER_14: there is a there's a there's a couple interesting things one of them is going to be how are these companies thinking about real estate electrifying that real estate in urban environments and roboticizing that real estate so that they can do the servicing maintenance etc look i guess it could be manual SPEAKER_45: for a while can i can i put you on the spot just go one level above it because merge the last two concepts together you talked about we talked about the federal government doge etc isn't there the SPEAKER_46: potential for just a complete surplus of physical inventory that exists in america oh yeah okay so big Chamath Palihapitiya: time so what does that mean for commercial real like how do you like navigate around that because you SPEAKER_14: got to evade the falling knives first so okay so let's just go down ride sharing lane so autonomous ride sharing lane you go down that lane car ownership which is already dropping drops like a knife all the way down and there's this thing in cities which takes up 20 to 30 percent of all the land it's called parking it's no longer necessary because cars are getting utilized the cars that exist on the roads are getting you utilized 15x more than they were before per car so you need hypothetically 115 the number of cars maybe you could say one-fifth or one-tenth because you want to be able to surge to like rush hour and things like that it depends on what kind of carpooling and things like this that are going on let's just call it 10x fewer cars one-tenth the land necessary for parking at least one-tenth like maybe it's less than that okay so now you're opening up you're opening up 20 of the land in a SPEAKER_62: city that just goes fallow but what should we do with that and is there a demand for that land SPEAKER_46: well look i mean maybe it's the should it be housing you know like and then don't we have to reevaluate all of the city planning today because city planning today to your point works backwards from all these yeah constraints that are 1.0 constraints like yeah here's the traffic flow here are the traffic SPEAKER_45: patterns those don't exist theoretically anymore or they would exist in a totally different way right SPEAKER_14: yeah i mean we've got it there's like a massive amount of creativity to say what can i do with that land and with a high roi right like some people are like you're gonna have farms you know uh hydroponic SPEAKER_63: farms in urban environments i'm like uh you know that's not a bad idea you don't have farm to table healthy food it's literally farm to table it's like a mile away from yeah so there's some interesting SPEAKER_14: ideas the land price has to really come crashing down and there's interesting ramifications if it SPEAKER_391: were to do that you could imagine that's what that's what i wanted you to say not to try to get Chamath Palihapitiya: you there but that seems like well that seems like the crazy thing that nobody is thinking about which SPEAKER_46: is in this push this physical built inventory has so much value built up in the 401ks of individuals to SPEAKER_155: the balance sheets of huge pension funds but that value is could be very different right but the SPEAKER_14: crazy part is is it could just be electricity production and electric capacity on the grid SPEAKER_231: could be the gating factor that makes it a slow burn potentially i'm just riffing here guys right SPEAKER_39: makes total sense and if you want to see what happens when you have like unlimited land if you live in austin and you see the distance between san antonio houston and dallas and austin in that triangle you know you get 30 minutes outside of the city centers there's just unlimited land and there's less regulation and you know what's happened housing prices and rents have come down two or three years in a row so this could happen in other major cities and if doge has less regulation you can build SPEAKER_00: more it could be amazing for americans to actually be able to afford homes again and maybe SPEAKER_238: convert some of this space you go energy storage electric grid upgrades sort of modular energy SPEAKER_14: capacity upgrades like and production these are this is going to be very very important right now if you want to when we do this all the time we have of course facilities all over every major city in the u.s and really around the world utility upgrades is the long pull in the tent in in construction development in a lot of our cities not all cities but in a lot of our cities the fed held rates they're SPEAKER_39: getting close to the goal of two percent i guess we're at 2.4 2.9 percent in terms of inflation any thoughts on uh where we're at with the fed deciding to not cut and just uh you put it on the docket SPEAKER_45: here chamath any any wider thoughts there i would just say that the long end of the yield curve is SPEAKER_46: basically telling us that there's a still a chance for inflation so i think that the the question is these next 30 or 60 days from the administration i think are basically they're critical and i think if if doge gets to the 3 billion a day number quicker than people thought there's going to be a lot of room for i think the president to make a very valid argument that rates are too high for where they are and that we're going to be able to have a lot more cost control in the expenses which means that there'll be less need to spend it doesn't solve the problem that yellen created yellen and biden on the way out the door the biggest problem was that they put america in this very difficult position because they issued so much short-term paper that is extremely expensive and as all of that rolls off we have to go and finance a ton of this debt at now five percent so it's still nearly 30 percent of SPEAKER_84: of uh the debt is going to get refinanced this year and then it's like what are these auctions SPEAKER_190: going to look like guys this is the thing we we all got a blast auction barely had 2x coverage SPEAKER_66: and i think that that could take a lot of the energy out of the market watch the dalio interview SPEAKER_09: because this this is exactly the topic he covers you know as we end up needing to refinance this debt the rates climb the appetite isn't there and it becomes a spiral that's why we have to cut fast in terms of the deficit to basically attract the market now you know the markets moved a little bit right so on january 13th the 30-year treasury peaked at exactly five percent and it's come down today it's at 4.77 so a little bit of relief uh since that that peak is as kind of the administration's gone into office and actually taken action but as more of this action is realized if people do appreciate and doge is successful and the court's adjudication does allow reduction in spending which i think is the intention i think we could see this rate drop from 478 much more significantly than where it SPEAKER_406: is and that'll create a great deal of relief and dave it's like it either does that or it really really doesn't or it does like the exact super nasty really bad that's right i got a text from someone who SPEAKER_09: is pretty senior in capital markets thinks this is going to go to five and a half percent before it goes down so they think that there's going to be a little bit more of a turbulent run ahead but it's SPEAKER_14: like but the thing is it's like that whole thing of like it's going to get to five and a half before it comes down it's like by the way it spirals on itself it's like you got to print money to then get to that place and then the printing drives it for you know you get to that spiral the problem is if SPEAKER_46: we go to five and a half percent that's not 80 basis points what you really need to think about is the total tonnage of actual dollars that need to get repaid back and if you look backwards that's effectively like 10 rates from 2000 could you imagine what the economy that's right would have done if you had brought rates to 10 11 20 years ago it would have crippled the economy so we don't have a lot of room here where you can walk rates up to five and a half six percent without a lot of things starting to break this is why i actually think doge will be successful because as people internalize all of these things where every single congressperson freeberg that may have wanted their own benefit for their community they'll have to take a step back because the broader optimization for america just needs to take priority but shamath it just doesn't work like that man SPEAKER_14: like my thing is like i like i agree with the notion but i just don't believe that any individual congressperson will take responsibility in this way they won't they won't but the question is can they block it yeah but or put another way again the executive branch can slow roll spend in a lot of SPEAKER_09: different ways except you cannot with medicare and social security discretionary spending is like 20 the mandatory spending social security medicare medicaid these are the the larger outlay and uh this where where we come back to the fact that this will never i hear you get addressed until it has to be because of the political suicide that arises i just think there's this is where i think elon's SPEAKER_46: fame can be helpful and i mean very specifically this following idea you know that famous sputnik comment where nasa spent millions of dollars trying to engineer a pen that could write upside down and it turned out that in sputnik the russians just took a pencil that is what we need to do to the u.s government because i suspect even though there's a lot of mandated spend the real question that nobody knows the answer to is is that spend useful so even though it's appropriated by congress there has to be a feedback loop that says you can just use a pencil you don't need the upside down writing pen and i think that if there's anybody that can broadcast that to the world it's him and this is where i think trump gets enormous leverage by having elon in the west wing but David Friedberg: nobody else could give him the rest of us would just be chirping into the darkness yeah this is SPEAKER_38: the naming and shaming of government waste that's actually going to work in the doge account on twitter is doing it they're basically saying hey we're giving foreign aid for this project for that SPEAKER_39: project is it going to be perfect every time no but you show an empty office space you show people not coming to work you show people well yeah if that's even real you know there's going to be a bunch of you know back and forth here but overall if you keep naming and shaming each of these projects and then you know they were talking about blockchain whatever and supposed to report elon is at like the government building working on leases at the moment like this stuff is going to be extraordinary popular because you can just take the number of 330 million americans and whatever you just save SPEAKER_00: you can just divide it by that number and tell every american how much they just paid less in taxes or how much they just saved individually the naming shaming and doing the back of the envelope math for every american is going to work do we want to wrap maybe a little bit on this tragedy SPEAKER_41: in dc okay what are your thoughts uh we were talking with our friend sky dayton who is very involved in aviation and um he's got a lot of blog posts he's done recently and he's got a company he SPEAKER_46: invested in to do uh pilot training i'll share two things one is anonymous it's from a friend of mine gave it to me and said i could share it there's a commercial pilot and he and i posted this i'll just read it honestly dca is the sketchiest airport we fly into i feel like the controllers there play fast and loose hence the periodic runway incursions i've said to every first officer in my threat briefings that we both need to be on red alert at all times there dca calls out helo traffic helicopter traffic and vice versa all the time but it's borderline impossible to see them when you're bombing along at 150 miles per hour i mean that's from a pilot that is i don't think he has any incentive to sugarcoat things and then i just wanted to read a message from brian yutko who's the ceo of whisk who's building a lot of these autonomous systems he said first auto traffic collision avoidance systems do exist right now these aircraft will not take control from the pilot to save the aircraft even if software and systems on the aircraft know that it's going to collide that's the bit flip that needs to happen in aviation automation can actually kick in and take over even in piloted aircraft to prevent a crash that's the minimum of where we need to go some fighter jets have something called automatic ground collision avoidance systems that do exactly this when fighter pilots pass out and it's possible for commercial and then the second he said is we need to have better atc air traffic control software and automation right now we use vhf radio communications for safety and for critical instructions and that's kind of insane we should be using data links etc the whole atc system runs on 1960s technology they deserve better software and automation in the control towers it's totally ripe for change the problem is that attempts at reform have failed so i just wanted you guys to have that one from this commercial pilot and then two from brian yuko who i think understands this issue really well there's so much opportunity here to make this better this should have never happened our other friend sky dayton has been pushing really hard for the u.s government to do advanced pilot training one of the things that he says constantly is just that a lot of the pushback is just union rhetoric around what they perceive the right thing for their constituency is and hopefully this starts this conversation because i think guys like sky guys like brian are working on this next level of autonomous solution that can just make flying totally totally safe beyond what it was the crazy SPEAKER_212: stat is that we haven't had a commercial airline disaster in the united states in almost 25 years SPEAKER_39: isn't that it was 15 yeah it's looking like pilot error here and it's there also seems to be some question of why these apaches are flying around this really crowded airspace and it seems like they're SPEAKER_00: shuttling you you know politicians around and maybe that's not the best idea in this really dense area SPEAKER_146: as your pilot friend was referring to chamath so god thoughts and prayers and all that stuff for the um for the families of the people who died it's just terrible tragedy terrible tragedy yeah it's just it's really just this is an area to invest money and use the private sector and all this incredible SPEAKER_39: innovation that's available to upgrade these systems and infrastructure this has been another amazing episode of the all in podcast thanks travis for joining us thank you tk that was a lot of fun SPEAKER_295: guys first time this is my first time on a podcast ever yes you were great anytime you were great man SPEAKER_429: you were great appreciate it appreciate it very based it's gonna like it tell us what you think SPEAKER_448: and we'll see you all next time love you boys