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all right everybody welcome back to the Allin podcast we've got an incredible crew today don't forget to go to our
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YouTube blah blah blah subscribe and make sure you check out freeberg surprise drop with his hero Ray
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Dalia live on all platforms today how did that come about for a b little surprise drop just great was talking
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with Ray about his new book which he just published on how countries go broke obviously which country going broke now
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America I think he talks a lot about the historical context of what's G on with the death Cycles in different
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countries and basically at the end of the book he has a pretty uh I think important
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recommendation to try and get the US to roughly 3% of GDP as our net deficit net
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of all expense including interest expense so that's the recommendation to the administration I think it's pretty
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timely with the change in administration anyway great topics to talk through and
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really important book awesome well done and we are super delighted to have in The Red Throne Travis Ken he is the
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co-founder and CEO of cloud kitchens he also uh worked in the cab business for a
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little bit co-founder and former CEO of uber and uh yeah we had a great interview at the all- in Summit last
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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
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doing really well I I got a say just like at the summit Jason I'm I'm it's an honor to be in the presence of such a
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prominent Uber investor absolutely absolutely I mean finally somebody has recognized my contribution the greatness
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of JAL Absolutely I'll mention it three or four times we'll be all good I'll give you the props you don't have to do
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it for yourself anymore thank you appreciate it appreciate let your winners ride Rainman David
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and instead we open source it to the fans and they've just gone crazy with it love
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Queen give everybody a little overview of cloud kitchens and the business and how it's going because people are
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obviously addicted to ordering food at home and uh it's it's quite a trend yeah I mean the
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the high 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
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like you go well in a hundred years we'll start way out there in a 100 years you're going to have very high quality
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food very low cost that's incredibly convenient and they going to be machines that make it
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they going to be machines that get it to you and it's going to be exactly to your
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dietary preferences your food preferences Etc and it just comes to you and it's so inexpensive that it
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approaches or has surpassed the cost of going to the grocery store that's more of a like a today analog
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so you go 100 Years of course that's the thing nobody's going to be making food what about 20 what about 10 and so the
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company is real estate software and Robotics that's all about the future food and if you can get the quality
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there and you can get that cost down to start approaching the cost of going to the grocery store you do to the kitchen
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what Uber did to the car and that's the thing a grind it's like lot you know bits and
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atams in the Uber world this is like five times more atoms per bit this is like heavyduty industrial stuff
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probably more along the lines of like you know where Elon goes and some of his companies like they're super interesting
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Tech but you got to grind out those atoms do you see people actually cooking in the future or does it become a
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centralized service and is it optimized to People's Health and what do you think
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the implications to the food supply are if your vision holds how do you think about all those things look uh people
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will cook in the future as a hobby I sort I make a joke at the office I'm like I like horses I love horses but I
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don't ride a horse to work right and it's going to be a little bit like that whereas you can cook it's It's A Soulful
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thing to do it's just very human but you know it's late you know Mom gets home late from the office needs
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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
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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
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time and yes dietary preference everything because it'll be hyper personalized like the way the internet
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is in content plus plus plus in terms of your specific preferences for what you want You' got these computers rocking oh
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these robots rocking I think in Philly somewhere uh in the lab where they're making bows yeah I mean we're out of the
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lab at this point we have our machine so we have a machine called a bowl Builder
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that basically makes different Cuisine types with bows so like think of like like sweet greens like what they yeah
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we're not working with these Brands specifically but I'll I'll just sort of it's a good analogy like think of
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Chipotle or Cava or sweet green or you get the idea we created test brands that were like
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those things and built the machine at the same time as we were building an actual
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restaurant and we built that restaurant to prove that the machine works then we have our customers now
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touring checking out we're rolling out with five customers in April that are using the machine and the way it will
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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
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know tens of thousands of kitchens around the world they will come into one of our kitchens in a facility it's a
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delivery only restaurant they'll prep the food in the morning and then they will leave and the
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Machine will if you will order online door dashu breats Etc they'll order online the way they do build your own
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Bowl exactly as you want and the bull gets all the ingredients dispensed hot or cold sauce Etc gets
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sled the bowl goes into a bag the utensils go into the bag the bag is sealed and then it comes out on a
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conveyor belt and machine gets the bag it goes to the front of the facility gets put into
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a locker that Locker then is sitting there door Dash re driver comes waves their waves their phone with an app in
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front of a camera and it pops open the locker that has the food that you're supposed to get that's so cool so like
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if you're if you're a restaurant tour you're the grind of the on man Meal which is the restaurant world goes away
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you you basically prep and that's asynchronous from when people order food the machine does the final assembly or
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what's known as plating essentially like do you think there's a service in the future where my
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physiology I can share that with you with Cloud kitchens and you guys just can always be
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optimizing my food based on what I know is good or bad for me so first what we do is we serve the restaurants so what
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happen so chamat you'll be sharing your dietary preferences with uberit or door Dash or sweet green or
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somebody we like our like our customer promise at our company we serve those who serve others or put in another way
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is infrastructure for better food so we are the either the AWS or the Nvidia or whatever you want to call it but for
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food if that makes sense we're behind the scenes we're the infrastructure and so you'll give your preferences right it
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should be a brand like then sweet greens or whomever Chipotle that says hey guys
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share with me like a yes an encrypted hash of your dietary restrictions needs whatever your lipid panel and I and I'll
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customize this thing and then you enable that on the back it's pretty close jth right you can do authenticate your Apple
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Health just authenticate Apple Health when these bowls come off the line and see how I talk it's like an assembly
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line bows come off the line on the label on the bow is how manys of every ingredient is in it plus a picture of
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what it was before we put the lid in that can be sent to the person while the Bull's on its way via a courier right
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what do you think Travis about this whole Maha movement and just the food supply itself so then what how does that
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change do restaurants Embrace more Farm to Table stuff I think look I think what
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like what we've SE with Supply chains in a bunch of different Industries it's just going to get super wired up so
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right now we're at the point of manufacturing but what happens so you go okay we're doing assembly then you go
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okay what about prep then you go further upstream and you're like what about supply chain like Cisco US Foods and
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then you go further up and you're like well how does how does the mechanization occur on farms and in agriculture and
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then how does that all get wired up to serve the customer and sort of what they're looking for so like you really
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can know exactly what kind of wheat was put into that food whether it was organic for real or
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not like what was the actual field it came from things like this you could imagine like really getting tied about
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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
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couple different I went to the I went to RFK Junior's website and they have like
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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
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it get the onesie yeah that's amazing the onesie was crazy your bowl Builder Friedberg
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you tried to do this right your and we had a bowl Builder 10 years ago or 2015 yeah
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2016 Diego saw it he actually visited it when we built it and we designed the system around a
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canister mechanism so all the food prep was done in a similar sort of like com AR model and then it was loaded in bulk
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and then put into little canisters and there were 30 slots in the canister dispenser and then the canisters would
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move down the device open up and and you could assemble bowls with rice and beans
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and all sort stuff the whole thing was automated and we were in the process of building out our first automated store
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when I actually took a medical leave of absence from it and ultimately the company did not get it into production
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but it we had great working demos and it was a very yeah I mean it was just definitely a
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no-brainer that this love this you love this yeah and at the time we were we actually had I'll tell you guys this we
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actually had a term sheet with Chipotle this was nine years ago to actually put this into Chipotle stores
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and then we were in the early conversations with sweet green at the time as well and obviously Jonathan and
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team have gone on to develop their own system but you know basically you can reduce so much of like qsr down to this
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bull based system and automated as Travis is doing so it's just a no-brainer and it's it's certainly
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necessary in a time when there's either labor shortage or labor price inflation that's causing a real issue with the
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ability and yeah this is the original automats in in New York yeah in in the early 20th century I love this but yeah
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they had a commissary behind that wall and they made like plates of food you put in there you put a quarter in you
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turn the knob and you get your meal out it's the classic that's the classic artificial artificial intelligence right
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this is like the Mechanical Turk thing I mean look here's the thing here's the a
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little Nuance that's super interesting about Automation in qsr restaurants is that they have an existing brick and
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mortar that's built a certain way that layout is meant for humans and to for those humans to work in certain
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processes an exact and very specific way every square inch of that kitchen and that space is is
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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
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like do you've got to like if you're to replace the front line in Chipotle you got to you got to take out that front
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line you got to demo it yeah you got to put in a new machine that's the challenge that they
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all had and so now it's like a huge amount of capex my storees down for two to three months and the economics start
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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
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take we're in that delivery only model so these are it's true infrastructure for making food behind the scenes for
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delivery so you don't have these issues and of course our setup our infrastructure these kitchens are
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designed for these kinds of machines to be in them and vice versa we've designed
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the machine to be in them when we did this early at ITA it was like food delivery was very early we built these e
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restaurants that were smaller frint we had an 800t restaurant that was doing 3 million a year in revenue and it had a
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handful of people working in it but we were putting about 800 people an hour during the lunch rush through that
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restaurant ordering custom B this was by one market right so one market exactly and so by the way did you guys notice
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that jcal was plugging his product there in the background even though it has absolutely nothing to do with what
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Travis was saying oh welcome back to the show nothing's changed sax is here no one else even
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noticed that I just heard this voice from above it was the Zar of AI and crypto I was like Wow send it that's all
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sit back and listen the Zar is back ZX any anecdotes you want to share about life in DC how how exciting it's been in
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the administration the first week it's been amazing I mean it's hard to believe it's only been a week right so you in
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the white house or that building next to it do you have an office building you mean the treasury building I know
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somebody was talking about there was a building next to it or what something I don't know I have an office in the uh
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old executive office building otherwise known as the Eisenhower Building and then I have a pass where I can just walk
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over to the westwing if I want to walk over to it there's kind of a whole White House complex
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behind the Gates that with the West Wings part of it and the Eisenhower Building and there a couple other
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buildings in that complex it's really cool it is really neat to to show up for work at the White House to say that's
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awesome it's like being in a movie or something or a TV show it is really cool you know it's awesome any interesting
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meetings you can talk about and I mean I know we are here to today to talk about
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deep seek but any interesting meetings or anecdotes from just the Vibes and walking around what's the coffee l is
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there like a commissary you run into anybody interesting there is a commissary actually in the White House called the
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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
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you can take people to to lunch at the Navy mess oh look forward to it J Cal just invited himself look forward to it
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I look forward to taking jamath and freeberg there I'll wear my Maga hat all right
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well let's get started you're here because you uh we have a very specific he's here because the world is ending
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Jason the the Western world is ending okay the Western world is ending and David Sachs is going to save it but we
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had a little bit of a freak out the last week regarding this deep seek if you don't know that's a Chinese AI startup
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they released a new language model it's called R1 and it's on par basically with
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some of the best models in production in the west like open AI 01 model but they
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claim and listen you can trust CLA coming out of China you know for what it's worth uh
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they claim to have done this all for $6 million on only 2,000 gpus for comparison open AI spent reportedly 8
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100 million to train GPT 4 which you're all using now and uh Sam claims they're going to spend a billion dollars
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training GPT 5 and so that's about 7% of the cost of GPT 4 obviously there are export
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restrictions on Nvidia h100s to China so there's a big big debate as to if they actually have H1s or not and uh Monday
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was a blood bath in the stock market Nvidia had the worst day in the history of the stock market in terms of total
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dollar amount of market cap lost it was down 177% which is $600 billion tsmc was
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down arm was down Brom was down so I guess everybody's asking the question how did they do this did they do it and
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then there's a bunch of debate on whether they stole which is kind of Rich coming from open AI which got caught
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red-handed stealing everybody else's content and now they're crying foul that the Chinese stole or
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trained did what's called distillation of their model in order to build theirs Sachs obviously you are the Zar of AI
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I'm curious what your take on all this is and thanks for coming well I think one of the really cool things about this
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job is just that when something like this happens I get to kind of talk to everyone and everyone to talk and i' I
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feel like I've talked to maybe not everyone in like all the top people in AI but it feels like most of them and
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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
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synthesis based on hearing from the top people in the field it was a bit of a freakout I mean it's rare that a model
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release is going to be a global news story or cause a trillion dollars of market cap decline in in one day and so
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it is interesting to think about like why was this such a potent news story and I think it's because there's two
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things about that company that that are different one is that obviously it's a Chinese company rather than an American
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company and so you have the whole China versus US competition and then the other is
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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
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versus closed Source debate and if you take either one of those things out it probably wouldn't have been such a a big
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story but I think the synthesis of these things got a lot of people's attention a
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huge part of Tik tok's audience for example is international some of them like the idea that that the US may not
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win the AI race that the US is kind of getting a comeuppance here and I think that fueled some of the early attention
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on Tik Tok similarly there's a lot of people who are rooting for open source or they have animosity towards open
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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
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what open AI has done at 12 cost so I think all of these things provided fuel for the story now I think the question
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is okay what should we make of this I mean I think there are things that are true about the story and then things
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that are not true or should be debunked I think that let's call it true thing here is
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that if you had said to people a few weeks ago that the second company to release a reasoning model along the
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lines of 01 would be a Chinese company I think people would have been surprised by that so I think there was a surprise
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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
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base llm model like Chach D40 or the Deep seek equivalent was V3 which they launched a month ago and that's
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basically like a smart PhD you ask a question gives you an answer then there's the new reasoning models which
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are based on reinforcement learning sort of a separate process as opposed to pre-training and 01 was the first Model
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released along those lines and you can think of a reasoning model as like a smart PhD who doesn't give you a snap
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answer but actually goes off and does the work you can give it a much more complicated question and it'll break
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that complicated problem into a subset of smaller problems and then it'll go step by step to solve the problem and
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that's that's called Chain of Thought right and so the new generation of agents that are coming are based on this
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type of idea of of Chain of Thought that that an AI model can sequentially perform tasks figure out much more
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complicated problems so open AI was the first to release this type of reasoning model Google has a similar model they're
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working on called Gemini 2.0 flash thinking they've released kind of an early prototype of this called Deep
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research 1.5 anthropic has something but I don't think they've released it yet so other
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companies have similar models to 01 either in the works or in some sort of private beta but deep seek was really
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the next one after open AI to release you know the full public version of it and moreover they open sourced it and so
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this created a pretty big splash and I think it was legitimately surprising to people that the next big company to put
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out a reasoning model like this would be a a Chinese company and moreover that they would open source it give it away
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for free and I think the API access is something like 12th the the cost so all of these really did drive the the news
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cycle and I think for good reason because I think that if you had asked most people in the industry a few weeks
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ago how far behind is China on AI models they would say six to 12 months and now
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I think they might say something more like three to six months right because 01 was released about four months ago
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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
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now let's take the um we should take the claim that they only did this for $6 million on this one I'm with Palmer
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lucky and Brad gersner and others and I think this has been pretty much corroborated by everyone I've talked to
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that that that number should be debunked so first of all it's very hard to validate a claim about how much money
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went into the training of this model it's not something that we can imper Ally discover but even if you accept it
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at face value that $6 million was for the final training run so when the media is hyping up these stories saying that
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this Chinese company did it for six million and and these dumb American companies did it for a billion it's not
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an Apples to Apples comparison right I mean if you were to make the Apples to Apples comparison you would need to
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compare the final training run cost by Deep seek to that of open AI or anthropic and what the founder of
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anthropics said and what I think Brad has said being an investor in open Ai and having talked to them is that the
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final training run cost was more in the tens of millions of dollars about nine or 10 months ago and so you know it's
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not six million versus a billion okay it's the billion doll number might include all the hardware they've bought
00:23:20
the years of putting into it a holistic number as opposed to the training number
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yeah it's running it it's not fair to compare let's call it a nuts number a fully loaded number by American AI
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companies to the final training run by the Chinese company but real quick sax you've got you've got an open source
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model and they've the the white paper they put out there is very specific about what they did to make it and uh
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sort of the results they got out of it I don't think they give the training data
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but you could start to stress test what they've already put out there and see if
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you can do it cheap essentially like I said I think it is hard to validate the number I think that
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if let's just assume that we give them credit for the 6 million number my point is less that they couldn't have done it
00:24:08
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
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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
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all the models and all the experiments and all the training runs they've done right and the compute cluster that they
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surely have so Dylan Patel who's leading semiconductor analyst has estimated that
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deep seek has about 50,000 Hoppers and specifically he said they have about 10,000 h100s they have 10,000 H 800s and
00:24:47
30,000 h20s now the cost s sorry is they deep seek or it's deep seek plus the hedge
00:24:53
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
00:24:58
illegal right because the h100s were banned under export controls in 2022 than they did the h800 in 2023 but this
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founder was very farsighted he was very ahead of the curve and he was through his hedge fund he was using AI to
00:25:13
basically do algorithmic trading so he bought these chips a while ago in any event you add up the the cost of a
00:25:22
compute cluster with 50,000 plus Hoppers and it's going to be over a billion dollars so this idea a that you've got
00:25:29
this Scrappy company that did it for only 6 million just not true they have a substantial compute
00:25:35
cluster that they use to to train their models and frankly that doesn't count any chips that they might have beyond
00:25:45
the 50,000 you know that they might have obtained in violation of export restrictions that obviously they're not
00:25:53
going to admit to and we just don't know we don't really know the full extent of
00:25:57
of what they have so I just think it's like worth pointing that out that I think that part
00:26:03
of the story got overhyped it's hard to know what's fact and what's fiction everybody who's on the outside guessing
00:26:11
has their own incentive right like so if you're a semi-conductor analyst that effectively is massively bullish Nvidia
00:26:19
you want it to be true that it wasn't possible to train on $6 million obviously if you're the person that
00:26:26
makes an alternative that's that disrupt you want it to be true that it was trained on $6 million all of that I
00:26:33
think is all speculation the thing that struck me was how different their approach was and
00:26:41
TK just mentioned this but if you dig into not just the original white paper of deep seek but they've also published
00:26:47
some subsequent papers that have refined some of the details I do think that this is a case
00:26:53
and Sak you can tell me if you disagree but this is a case where necessity was the mother of invention so I'll give you
00:26:59
two examples where I just read these things and I was like man these guys are like really clever the first is as you
00:27:05
said let's let's put in a pin on whether they distilled 01 which we can talk about in a second but at the end of the
00:27:12
day these guys were like well how am I going to do this reinforcement learning thing they invented a totally different
00:27:17
algorithm there was the the Orthodoxy right this thing called po that everybody used and they were like no
00:27:24
we're going to use something else called I think it's called grpo or something it
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uses a lot less computer memory and it's highly performant so maybe they were con strain
00:27:35
sacks practically speaking by some amount of compute that caused them to find this which you may not have found
00:27:41
if you had just a total surplus of compute availability and then the second thing that was crazy is everybody is
00:27:48
used to building models and compiling through Cuda which is nvidia's proprietary language which I've said for
00:27:55
a couple times is their biggest moat but it's also the biggest threat factor for lockin and
00:28:01
these guys worked totally around Cuda and they did something called PTX which goes right to the bare metal and it's
00:28:07
controllable and it's effectively like writing assembly now the only reason I'm bringing these up is we meaning the West
00:28:14
with all the money that we've had didn't come up with these ideas and I think part of why we didn't
00:28:20
come up is not that we're not smart enough to do it but we weren't forced to because the constraints didn't exist and
00:28:27
so I just wonder how we make sure we learn this principle meaning when the AI company wakes up and
00:28:33
rolls out of bed and some VC gives them $200 million maybe that's not the right answer for a series A or a seed and
00:28:42
maybe the right answer is 2 million so that they do these deep seek like Innovations constraint makes for great
00:28:49
art what do you think uh freedberg when you're looking at this well I think it also enables a new class of investment
00:28:56
opportunity given the low cost and the speed it really highlights that maybe the
00:29:03
opportunity to create value doesn't really sit at that level in the value chain but further Upstream apology made
00:29:09
a comment on Twitter today that was pretty funny or I think ref this about the ra he's like turns out the rapper
00:29:15
may be the the mo the the mo which is true at the end of the day if model performance continues to improve get
00:29:23
cheaper and it's so competitive that it commoditized much faster than anyone even
00:29:28
thought then the value is going to be created somewhere else in the value chain maybe it's not the rapper maybe
00:29:35
it's the user and maybe by the way here's an important point maybe it's further in the economy you know when
00:29:40
electricity production took off in the United States it's not like the companies are making a lot of money that
00:29:45
are making all the electricity it's the rest of the economy that Acres a lot of the value well you're about to see a big
00:29:49
test of this because if open AI raises 40 billion at 340 billion that just hit the wire the underwriting IC at 340
00:29:59
billion exactly what you just said freeberg it is the rapper meaning chat GPT is the next killer app it's getting
00:30:05
to a billion plus ma hundreds of millions of da it's competing for Consumer usage that's that's the model
00:30:12
that's the model is like consumer usage which puts them on a on a collision course with meta it's the only company
00:30:19
that could really impact that because the only company right now that has billions of eyeballs of daus per day and
00:30:27
who and by the way Zuck said this in his earnings release he's like there's only
00:30:30
going to be one company that brings AI to a billion plus people and it will be us some version of that quote in his
00:30:38
earnings released yesterday and Microsoft showed weakness in the in their cloud and then Microsoft's down
00:30:43
six% today and you know I think it's a a window for open AI to say we're going to
00:30:50
go up against meta this is it we're going to be the players what you everyone's kind of ignoring Google at
00:30:55
what do you guys think is happening right now between open Ai and Microsoft cuz if it's true that this distillation
00:31:00
thing actually happened well there's only one place where you could have distilled the o1 model it's on aure so
00:31:06
what the hell is going on over there well and there R1 is supported on explain distillation real quick yeah so
00:31:13
when you have a big large parameter model the way that you get to a smaller more usable model along the lines of
00:31:20
what saaks mentioned is through this process called distillation where the big model feeds the little model so the
00:31:26
little model is asking questions of the big model and you take the answers and you refine and by the way you can see
00:31:33
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
00:31:38
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
00:31:45
1984 right and it sort of starts to go through this whole summary and then the person says are
00:31:51
there any actual states that currently do that hold on here it goes it says North
00:31:57
Korea wait goes China and then wait watch this boom so the reason why this is happening is like you're seeing this
00:32:03
Chain of Thought you're seeing the several layers and then it's catching it after the fact so we know that this is
00:32:08
distilled from some other model and my only point there it's a little tongue and cheek is right now
00:32:15
when you go and use open AI you're using it sitting in an Azure instance somewhere right so this is Microsoft's
00:32:22
Cloud infrastructure that runs it so it begs the question it's not that it's 's fault
00:32:28
open ai's fault that this distillation happened and I'm not trying to assign blame but typically if this were to
00:32:33
happen you'd look to your cloud provider and say how are you letting this happen
00:32:37
and I don't think anybody's had a good answer for that well and the cloud provider is hosting R1 now so they're
00:32:44
literally undercutting chat GPT and open AI at the same time just to clean that up they're
00:32:49
they're hosting their own copy of it right because r1's been open when you say they who are you who are you
00:32:55
referring to saxs Microsoft yeah Microsoft is hosting their version of R1 which means they are actively subverting
00:33:02
their partner open Ai and pushing people to a cheaper model well whatever I mean
00:33:08
look Amazon's going to host their own version of R1 grock has a version of R1 just red out it's open source now
00:33:16
have who has R1 on his laptop you know yeah exactly yeah but if it was if it was stolen as um and the IP was stolen
00:33:22
as Sam is claiming that would be like You' think he'd be able to call up S and say hey can you not put the stolen IP on
00:33:29
your server and promote it to everybody at a lower cost it just shows Microsoft has no loyalty to open AI yeah and they
00:33:35
have but you think they would have loyalty they have loyalty what it would take to distill
00:33:40
01 like brute force it wouldn't be like oh geez I can't believe it was distilled it would
00:33:48
be like such a massive number of calls against an API or against something something that you it wouldn't be
00:33:56
unnoticed and oh they did actually came out and said they blocked some suspicious activity recently yeah no but
00:34:02
they're always doing that they're always that's that's constant you're always doing that that's like you know the old
00:34:08
school you know go go ahead s let me let me address the distillation point so I I
00:34:12
mentioned this a few days ago on on Fox news that I thought it was likely or possible that desolation had occurred
00:34:20
and there was some evidence for this and it became like a news story and I I didn't even realize that saying that
00:34:25
would be news because it's kind of an Open Secret Silicon Valley everyone I talked to they're doing some level of
00:34:31
distillation because you need to test your model against theirs anyways yeah and every single person I've talked to
00:34:37
basically has agreed that there was some distillation here from open AI now that doesn't mean it was the only
00:34:45
thing going on here I mean to be sure the Deep seek team is very smart and there were some Innovations but also
00:34:51
there was some distillation and really this wasn't even a fresh news story I think from the point of view of Silicon
00:34:58
Valley because a month ago we had a press cycle in Silicon Valley when deep seeks V3 model came out that deep seek
00:35:08
V3 was self-identifying as chat GPT when you would ask it who are you like what model are you five out of eight
00:35:16
times V3 would tell you that it was Chachi T4 and there's lots of videos and examples of this online that have been
00:35:23
posted right the point is that we knew a month ago that V3 had been framed on a substantial amount of chat GPT output
00:35:30
obviously because V3 was self-identifying as chat GPT and there's two ways that that could have happened
00:35:36
so the let's call it innocent explanation is that deep seek had crawled the web and found lots of
00:35:43
published output from chat GPT and then trained on that and that wouldn't be a violation of open AI terms of service or
00:35:51
their IP or the other explanation would be that they used the API from open Ai and basically you know went to town yeah
00:36:01
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
00:36:08
people think happened and at the end of the day open AI can probably figure it out and they they've indicated that they
00:36:14
think there was some improper distillation here in the financial times it says opening eye says
00:36:21
it has found evidence that Chinese artificial intelligence startup DC used the US company's proprietary models to
00:36:26
train its own open source compan right that's what I'm referring to so they say they've been very clear about this by
00:36:31
the way you have to be sympathetic I think to open AI in this because if you're building a startup you're trying
00:36:36
to raise money we've all gone through this cycle guys where it's like there's momentum we celebrate internally the
00:36:42
momentum that's what gets you the energy to push your team even further and harder and then all of a sudden it turns
00:36:49
out that some portion of that like it Travis said it well like you're there's probably a chart inside of open ai's
00:36:55
offices where you're showing how many times these apis are getting hit right you know how many times these end points
00:37:00
are getting hit it all looks positive and then you realize that some portion of it was actually bad and trying to
00:37:06
undercut your value it's a hard pill to swallow and then you have to course correct very
00:37:12
quickly you have to lock down this is one area where security exactly we have not talked about this like you have to
00:37:18
lock these models down now you have to lock the endpoints down look in the Biden Administration if this had
00:37:24
happened the first conversation would have been we need need to kyc the people that use these models and it's like what
00:37:30
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
00:37:36
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
00:37:41
proliferation can happen so quickly but if we take the wrong takeaways from this
00:37:46
period there's going to be a bunch of people that'll clamor to like lock these folks down and make Innovation go much
00:37:52
slower I don't I think that that would be bad here's the other side and totally agree Chim but here's the other side you
00:37:57
go through the white paper you see what it is they did what they innovated on yeah the science behind it the
00:38:05
thoroughness and you're like these guys are badass it doesn't it does not feel or sound like somebody who took
00:38:13
something just when you get through it it could be that it could be that open AI wrote the white paper for them just
00:38:19
putting it out there but it's real Innovative I agree with that real Innovation strong Tech you're like this
00:38:26
is legit I agree with that but in that paper they're very hazy about where the data is coming from and they're they're
00:38:35
fairly transparent about everything else they did but they're not really clear about the data and specifically they say
00:38:41
that to get from V3 which is the base model to R1 which the reasoning model they had about 800,000 samples of
00:38:51
reasoning they were quite unclear about where those reasoning samples came from from by the way it is remarkable that
00:38:59
you can get from a base model to an R1 with just 800,000 samples but this is a problem like we meaning like the Western
00:39:05
AI Community we've been trudging around on this path where we've been very we had a very Orthodox approach the only
00:39:14
way you can do reinforcement learning is through po okay but is that true and it
00:39:19
turns out that if you're like a really smart team that has no other choice you move away and you invent your way out of
00:39:26
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
00:39:32
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
00:39:40
think the best part of this is the fact that Sam mman was supposed to be doing open source he made it a Clos Source
00:39:45
company he stole everybody's data every got caught red-handed he's being sued by
00:39:50
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
00:39:56
real competitor on the original Mission of what opening ey was supposed to do so
00:40:00
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
00:40:05
open source and it's better for Humanity and the fact that the Chinese did it to
00:40:08
Sam wman has come up and for him stealing everybody else's content that's my okay there you have it but I don't
00:40:15
have strong opinions on it it's hilarious does nobody see the irony in this he was supposed to be doing open
00:40:23
source because Jal I will say the models are closed you're right yeah there was there's the lawsuit with Scarlet
00:40:29
Johansson for stealing her voice even when she said no there's a real question and and people have asked New York Times
00:40:35
and then there's now the question about YouTube data being used to train the video models so there's a lot of being
00:40:40
on their on their heels a little bit so I definitely I definitely see your point
00:40:44
stealing I think yeah I think the the really all the pressure right now I think is on meta because I think meta
00:40:52
has to show up with the next iteration of llama that beats and exceeds Gemini that exceeds R1 and I think that
00:41:03
that is going to be crucial for us to have a counterweight to whatever China's going to put out after this and but I
00:41:09
mean jamat it's open source like does it not so this so this is my point Embrace
00:41:13
and extend Embrace and extend meta has to embrace and extend everything that these guys have shown meaning like meta
00:41:20
is buying tens of thousands of Nvidia gpus great but what did this show this shows that actually Cuda high level
00:41:29
languages in general I think we've all known that they suck okay and so we've all been going through it thinking that
00:41:35
it's like the right thing to do deep seek throws it out the window they use something called PTX what does meta do
00:41:41
is critical now to understand they need to embrace this stuff and this is where I think again apologies to the Invidia
00:41:48
bles but it's going to create a more heterogeneous environment and the reason is because there's too much money and
00:41:56
risk on the line to go through a single point of failure a chip a highle framework to get to that chip that's
00:42:03
nuts so I think like that kind of like Emperor has no close moment is upon us well let me ask you another question
00:42:09
let's assume that we start the world of AI today so there's no Legacy of the last three years and you wake up today
00:42:16
and there's this open- Source model that's 670 billion parameters you can run it on your desktop computer it's
00:42:22
completely available everything's completely transparent and I ask you the question forget about all the big
00:42:28
companies that are involved in everyone's strategy historically what's the model today to build value here
00:42:34
where do you build equity value as a business if you're going to start a company if
00:42:40
you're going to invest as a as an investor where do you go the first is you have to build a shim and I think the
00:42:45
reason why a shim is really critical is that there's so much entropy at the model level what this should show you is
00:42:51
you can't pick any model and the problem is that the people that manipulate these
00:42:55
models the machine learning engine and whatnot they become too oriented to understanding how to get output of high
00:43:01
quality using one thing meaning it shouldn't have been the case that we have Engineers that can only use sonin
00:43:08
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
00:43:14
llama right now that is kind of what we have you don't have the flexibility to hot swap as models change so if you're
00:43:21
starting a company today the first technical problem I would want to solve for is that because tomorrow if it's R2
00:43:29
or alibaba's model or llama I would want to be able to rip it out and put it back
00:43:34
in and have everything work and right now we can't do that the answer to your question fre is the answer your question
00:43:40
hold on the answer to your question is the application layer because this is all going to become storage it's like
00:43:45
YouTube being built on top of storage or Uber being built on top of GPS all these
00:43:50
Innovations are being commoditized and this one is happening faster than all the rest do you want to be in the
00:43:54
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
00:43:58
be in the GPS chip business I mean they're both decent businesses but Gavin Baker came on this podcast and said this
00:44:04
the fastest deprecating asset in the world was a large language model he's been proven right they're not worth
00:44:09
anything they're all going to be open sourced they're all going to be commoditized and that's for the best of
00:44:12
humanity and now we're going to be on the application Level the hardware level with robots and I think that's where the
00:44:17
opportunity is Travis what do you do what company do you start today if you start a company today given where the
00:44:23
world is at given the open- source models like what do you do oh I'm getting so excited um look I I think the
00:44:31
first the first degree out is it's what you got is there a rapper company okay so of course maybe those companies
00:44:41
already exist and then is there a tools company right so in a funny way even though Facebook could be the rapper they
00:44:48
have a tools business that these you know that the that deep seek is basically challenging
00:44:56
going full open source and like putting something out there that's really good and what has to happen is fa meta has to
00:45:02
decide like we are going to embrace and extend this we're going to make sure that all the developers come to us that
00:45:08
all the cool applications get built here so I think it's like there's a tools business and then there's the rapper
00:45:14
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
00:45:21
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
00:45:26
more I right I don't think I think the price elasticity on this one is actually positive so as the price goes down
00:45:34
that's right the revenue usage everything's going to go up we through the RO this is a history of tech forever
00:45:40
since like Bill Gates said I don't know what to do with more than 64 kilobytes of memory like you know the question is
00:45:47
did we cheap oil cheap oil in the United States drove the Industrial Revolution right and like when we started
00:45:53
discovering oil suddenly we were able to build factories and make stuff that we never imagin possible and so then you're
00:45:58
like okay AI is like you know it's going to get cheap it's going to be oil but it's also going to be specialized for
00:46:06
different tasks like you're going to start getting into nuances of like what is the invest the investor AI look like
00:46:14
what does the autonomous car AI look like what does the uh Google search I'm trying to figure
00:46:21
some like yeah so you could go vertical and Silo siloed air quotes understand what I'm saying abolutely yeah so
00:46:28
there's a a thing called Jin's Paradox which kind of speaks to this concept SAA actually tweeted about it which is the
00:46:35
it's an economic concept where as the the cost of a particular use goes down the aggregate demand for all consumption
00:46:44
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
00:46:51
more and more of it so you might actually get more spending on it in the aggregate that's right because more and
00:46:56
more applications will become cost feas economically feasible exactly that is I think a powerful argument for why
00:47:04
companies are going to want to continue to innovate on Frontier models you guys are taking a very strong point of view
00:47:12
that open source is definitely going to win that the leading model companies are
00:47:15
all going to get commoditized and therefore there'll be no return on Capital and basically continue to
00:47:20
innovate on on the frontier I'm I'm not sure that's true you for one thing the the R1 model
00:47:27
is is basic comp to 01 which which open AI released four months ago and was training on internally call
00:47:35
it N9 or 10 months ago so open AI is on 03 now its Frontier is ahead of where R1
00:47:43
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
00:47:53
R1 or deep seeks done a good job being a fast follower here is it's not clear that this is the frontier and those
00:48:00
Frontier Model companies now having seen what might have happened with distillation have a pretty strong
00:48:06
incentive to make sure that doesn't happen again and they're going to be taking countermeasures I mean there's a
00:48:11
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
00:48:17
reward for being at the frontier anybody uh have any other questions for Sachs before we drop him off to go back to
00:48:24
serving the American people before we drop him off one final point on on the whole open source verus closed Source
00:48:30
look I I'm not going to take sides in that but I I think that it's a mistake to just view what happened here as oh
00:48:39
it's this like Plucky upstart that's like doing the community huge service out of the goodness of its heart you
00:48:45
know it's basically open sourcing all oh they stole it they stole it it's a Chinese come on you still have this huge
00:48:52
geopolitical aspect to it right and deep seek is a Chinese company they trying to
00:48:57
catch up and so if you're if you're behind and you're trying to catch up then open source is a strategy that
00:49:02
actually really makes sense for you and you know they're trying to basically undercut the leading American companies
00:49:09
and I I don't think they did it with $6 million I mean they have massive resources behind them so I think some of
00:49:16
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
00:49:24
uh people who worked for Sam previously and quit who feel that way I think there's a lot of like support
00:49:30
for deep sea Valley because again people think that they're doing this huge service for
00:49:36
the community and I think it's a little bit more self-interested that than that it could be both right I mean there
00:49:41
there is a theory that they're trying to undercut and neuter the lead and at the
00:49:45
same time there's a b bunch of people who believe in open source and nobody should control this and certainly not
00:49:49
Sam wman should be the person who controls it so two things could be true at the same time David thank you so much
00:49:55
for coming on we appreciate it and uh thank you for all coming on your podcast David we appr David I know that this is
00:50:02
and now we're going to talk about a bunch of other crazy stuff gentleman David yes thank you all right thanks to
00:50:07
David Sachs for coming in and uh you know I guess let's open up the aperture here and talk a little bit about
00:50:15
relations with China we're obviously in a bit of a cold war with them we have tariffs we have
00:50:22
Taiwan and then we have uh the sort of trade war going on here with uh exports of h100s where do we want to start
00:50:30
gentlemen and you know Travis you've got some uh deep you're one of probably five
00:50:35
American entrepreneurs who ran an at scale business with Uber and the DD relationship in China so you have a
00:50:41
unique position of understanding business in this along with maybe Tim Cook and Elon are the only other two
00:50:47
people who've really had an at scale business there maybe Disney they have Disneyland there
00:50:51
yeah what's your take on the relationship and what's going here GE China how's China going to operate
00:50:57
differently than the US Travis from your experience your point of view tell us a
00:51:00
little bit about the culture and business ethics in China particularly as it relates to AI okay so okay so look we
00:51:08
I had this thing this is I'm going back almost 10 years here Uber day we're running Uber
00:51:14
China and I mean I cannot there's no way I could express the frenetic intensity of
00:51:25
copying the that they would do on everything that we would roll out in China and it was so
00:51:34
epically intense that I basically had a a massive amount of respect for their ability to copy what we did I I just
00:51:46
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
00:51:52
we'd roll it out and then like two weeks later boom they've got it a week later boom they've
00:51:59
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
00:52:08
400 Chinese Nationals in Silicon Valley at our offices in San Francisco we had a whole
00:52:15
floor for the China growth team and it was primarily Chinese Nationals we had Billboards on the 101 in Silicon Valley
00:52:24
in Chinese Uber Billboards to join our team in Chinese to to serve the Homeland right
00:52:34
um it was like an allout War it was really epic it was epic and by the way when you went to that floor in our
00:52:40
office you were in China like they red China style like the desks were literally smaller like the density of
00:52:49
the space was it was China okay so but what happens is when you get really really good at coping and that
00:52:58
time gets Tighter and Tighter and Tighter and Tighter and Tighter you eventually run out of things to
00:53:03
copy and then it flips to creativity to creativity and Innovation now at the beginning you you know it's sort of all
00:53:12
over the place like the kind of innovation when it was new was like what you know you're like really but as they
00:53:19
exercise that muscle it gets better and better and better so if you want to know
00:53:24
about the future of food like online food delivery you don't go to New York City you go to
00:53:31
Shanghai right what's an example like of like something really Innovative their doesn't doesn't mwan do drone delivery
00:53:37
and stuff like here's an example if you went to offices like let's say shanhai um Beijing any of the major cities hongo
00:53:46
Etc the office buildings have hundreds of lockers around their perimeter so that everything that you
00:53:56
get whether be food or anything else but especially food it's just the the couriers drop them off in these Lockers
00:54:02
in the at the office buildings and then there are a whole other set of people that are sort of like inter office
00:54:11
Runners Runners that then bring it to your office as an example like and when you
00:54:17
see it you're like and it's epically efficient and it's you know they're taking advantage of their economics on
00:54:23
labor and things like this it wouldn't exactly work that way here but a lot of the Innovation you will see coming out
00:54:31
on Uber Eats or door Dash like the stuff that's coming out now is stuff that existed three years
00:54:38
ago four years ago in China maybe longer so like eventually you cross that threshold of coping and you you're
00:54:45
innovating and then you're leading and I think we see that in a in in a whole bunch of different places yeah here's a
00:54:52
look at these smart lockers that you can see you're just available for sale when
00:54:56
when you go online but yeah these things are crazy and you've experimented with those as well didn't you have like a
00:55:01
commissary Concept in DTLA well look we okay so we got a couple things so we have in every one of our facilities and
00:55:08
we've got you know hundreds of them we'll have lockers there so the The Courier then waves their phone in front
00:55:15
of a camera the right Locker pops open they get the food from there and they go The Courier pickup is asynchronous from
00:55:22
production of food you never you don't have lines anymore there's no more lines which then speeds up delivery shortens
00:55:28
the amount of time shortens is reduces how much money you spend on couriers and we've got a whole other
00:55:37
thing this doesn't work in it probably wouldn't work in China because well for a lot of reasons but let me explain what
00:55:43
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
00:55:53
it is from a 100 different restaurants those restaurants happen to be in my facilities
00:55:57
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
00:56:03
puts it there's a shelf on every floor you get notified when your food arrives and it arrives the same T time every day
00:56:10
and you just go to the Shelf get it on your floor and dip it right back into your meeting saving people time at the
00:56:17
office giving them selection on food especially in food deserts but even going like there's a sweet green right
00:56:23
down there in my current in my office right now I could save 20 minutes by just using our own service versus doing
00:56:30
that and you get at the same price because the Courier economics The Courier is bring is delivering 50 orders
00:56:35
at a time so Courier costs go basically to zero what do we think of the um of the export controls here should we chth
00:56:43
be maybe Banning more h100s or other chip sets going there or is that futile I don't know the answer to that and I
00:56:50
think that's I think saxs and president Trump will make a good decision but here here's the Curious
00:56:57
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
00:57:05
that people are claiming is that deep seek is getting access to a bunch of Nvidia gpus using Singapore as a back
00:57:14
door so essentially you create a Singaporean shell company you place an order with Nvidia Nvidia fulfills that
00:57:21
into Singapore and then the chips go someplace uhoh and so there's a bunch of examples where people are saying that
00:57:29
you're talking about up to a quarter of all Nvidia Revenue goes into Singapore and the speculation right now
00:57:39
is that 100% of those then go into China which is an enormous claim because that's a huge amount of of nvidia's
00:57:47
Revenue now the interesting thing is if you actually try to understand well maybe that's not true and maybe it's
00:57:53
sitting inside of Singapore this is where that kind of unravels so just to be clear like Singapore is about 250 or
00:58:01
260 square miles like it's like a small small place also the Tik Tok headquarters
00:58:08
and I tried to find out how many data centers are in Singapore and it's about a 100 and so you would think that okay
00:58:14
well what does that mean 100 could mean anything but then you look at the energy
00:58:19
and they publish that and all of those 100 data centers consume about 876 megaw so these are are small data centers
00:58:28
right and the entire industry is like a one and a half2 billion doll Revenue business so I do think that saaks and
00:58:36
the administration are going to have to dig into this and figure out what their opinion should be but there is
00:58:42
clearly a ton of of these chips going into Singapore I don't think anybody knows
00:58:48
where they end up and the question is what does America think about that and why did we Implement these export
00:58:55
controls in the first place and if there's a simple back door how do you want to react if the US finds a path I
00:59:00
mean let's talk about like what happened with sanctions in Russia and other prior
00:59:05
kind of sanctioning efforts around the world but as you kind of close the the floodgates and close access the
00:59:14
buyer or the receiver of those goods or that Capital are going to look elsewhere
00:59:19
they're going to look to create a market somewhere else and so if we do cut off access to Nvidia ch we do cut off access
00:59:27
to US exports are we not kind of recognizing that the second order effect of that is that China will take IP that
00:59:35
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
00:59:41
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
00:59:47
technically complex but if ever there were a group of people in the history of human civilization to pull it off it's
00:59:53
probably the modern Chinese to be able B to say let's go build our own it's worse
00:59:58
than that our own infrastructure this is a great point but it's worse than that the models today are capable of
01:00:03
Designing chips for you that don't rely on the most complicated technologies that asml creates I mean look one of the
01:00:12
luckiest things that happened to Gro was we designed our chip at 14 nanometer which is effectively in the spectrum of
01:00:19
Technology like VHS and beta so we chose a simple simple technology stack to build to
01:00:27
the latest cuttingedge chips at like 2 nanometer that use these complicated asml machines it's not clear that the
01:00:33
yield is actually that good so why would you spend all that money and if China is
01:00:38
forced to engineer its way around it yeah freeberg the answer to your question is they'll use these models to
01:00:44
design chips that can be manufactured in simple ways and they'll make simple stuff so this I'm just not sure it
01:00:51
solves the problem is my point well it doesn't and this is why I think like it doesn't solve the real problem which is
01:00:57
how do we incentivize people in America to really out engineer and out innovate competition or AI I sure's in an era of
01:01:05
extraordinary abundance and that abundance ultimately reduces the the drive for conflict and things are better
01:01:11
off or the other version as well is that China could just bear the cost as a central authority of building an
01:01:19
incredibly great model right and they will spend all the money and then they will tell the Chinese companies you can
01:01:26
distill from this model for free because we have a golden vote and a seat on your
01:01:30
board anyways which is effectively de facto what happens if you get big enough in China so there's that possibility as
01:01:36
well where one Central Authority Bears the capex of creating something that then everybody else can can draft off of
01:01:43
and let's talk a little bit about open AI uh they're in Washington asking for money now is that the uh is that the
01:01:49
concept now is that the our government should back the rumor today was they're raising 40 billion at a 340 billion doll
01:01:56
preone with MSA potentially being the lead I would love Travis's read on this because Travis has taken large money
01:02:03
from from Masa in the past and has been through this but how does he think about
01:02:08
make this decision obviously we all know and I mentioned you guys the meeting I had with him last summer where he
01:02:12
basically kicked me out of the room because my company's not generative AI like someone said you should go meet
01:02:17
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
01:02:22
is not generative AI I only do generative AI I think you're company will be very successful you will be very
01:02:27
successful goodbye and he was walked out and that was like the end of everything
01:02:31
so great yeah that's all he's doing now so this is the big BET right so okay so I need to I need to bust a myth I did
01:02:38
not take money from Masa so he begged me to take money for years and we did not take it because he is
01:02:47
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
01:02:57
should probably count on him in using your information and investing in all of your competitors at least that's
01:03:02
historically what he's done so I didn't go there but then he just kept investing
01:03:06
in all my competitors and they kept subsidizing these markets and then I'm like maybe I should have just saturated
01:03:13
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
01:03:18
open AI taking a lot of money from aasa type situation is it's a little bit of like a double-edged sword is if you
01:03:25
don't take that money it goes somewhere else but if you do take that money just know that whatever intelligence they get
01:03:32
when they go through the process of giving you the money and maybe hanging around the board or who knows what is
01:03:37
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
01:03:44
you're don't but you got to pick and if the money's going and it's flowing and and access to Capital is a strategic
01:03:50
competitive weapon or Advantage you must you must play ball now we were able to we we we did stuff with the Saudis
01:03:58
before even Vision fund existed they stroked a three and half billion dollar check when that was like the biggest
01:04:04
thing that ever happened so we were okay with not having the M of money but that M of money then
01:04:10
went to all of our competitors door Dash and so in this open AI context Travis I mean like just
01:04:16
knowing what you know about AI is this going to be a competitive Advantage for Sam to raise 40 billion where does it go
01:04:24
when he's up against we don't know what in China Microsoft alphabet and meta well look I think this
01:04:32
goes to some of the things that shath is saying which is like if if constraint is
01:04:38
the mother of invention or or whatever that that euphemism is the the the aphorism is if if that's the case you
01:04:45
get into a real weird spot when you get over capitalized over capitalized in the
01:04:52
in the Uber model like the war was subsidizing rides for market share essentially being the rapper for
01:05:00
transportation and using the parlons we were using earlier to in the in in this discussion so it was necessary you're
01:05:07
screwed if you don't the the question is do you get to this place of over capitalized too big you know too
01:05:15
bureaucratic too loose too weak too soft and with when you have an open source model that's very smart and it's a
01:05:24
thousand flowers blooming lots of innovation happening everywhere could be an overwhelming
01:05:30
force uh now I think there's going to be different sectors treat it different ways where like going full stack in
01:05:36
certain industry sectors is going to matter and then in other places having like a very sort of chaotic everybody
01:05:42
does a little slice is going to be okay in other places and I think we could probably spend days or hundreds of
01:05:50
dozens of hours just talking about the nuances there you know well it seems like there's some degree of relationship
01:05:57
between the Stargate announcement with Masa and Sam standing up there with Larry and then Sacha showing up in the
01:06:03
conversation as well and this raise and the idea that more Hardware more infrastructure faster creates emote and
01:06:13
I guess that's the real thing you have to believe which becomes harder to believe in the context of what happened
01:06:18
in the last week I personally think that these models are and I've said this for
01:06:24
a while it doesn't make sense to one large do everything model this mixture oferts architecture ultimately you can
01:06:32
kind think about taking a large model making two copies of it and then trying to shrink each model down to whatever
01:06:39
the necessary so that you run two models in less frequently meaning that that combination of two models uses less
01:06:46
power and takes less time and then you do the same thing again and you shrink it down to four and then 12 and
01:06:52
eventually you have lots of smaller models some of which in some cases are experts at one thing like doing
01:06:58
mathematics or reading or writing but the reality is we don't know how whether humans have kind of thought about the
01:07:03
world the right way that the AI May resolve to having smaller expert models that we don't really understand why
01:07:08
that's the expert on something but you have a network of very small kind of things that work together and that
01:07:13
ultimately leads to a like commoditization not just in kind of model cost and in development and
01:07:19
runtime but also in like what's needed like do you really create much of an advantage by having all these dat c key
01:07:27
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
01:07:32
and the actual Advantage is going to be in the IP and owning content and the really smart thing to do would be for
01:07:38
somebody to go buy Reddit Kora the New York Times The Washington Post and Disney and take all that IP and then not
01:07:45
allow other people to use it sue the hell out of them every time they try I take Washington Post off that list but
01:07:50
yes but I'll say New York Times comes off the list too well whatever I mean all those
01:07:56
are definitely going to be what would be great about those is you could then like
01:08:01
a patent troll then tell anybody else who's absorbed New York Times stories historically or Disney and you could
01:08:07
just sue the hell out of them and then you've got the best most proprietary one you're describing you're describing text
01:08:14
so you're describing text content which is a fraction of where this is important
01:08:18
so video I think you can recognize that Google's YouTube Content Library is probably 100 to 200 times larger than
01:08:25
the rest of the internet combined to do it well actually Jas you're such an old school copyright guy
01:08:33
you're such an old school Med guy by way sorry I believe in artists and their right to content yeah we've had a series
01:08:39
of conversations that I I feel very confident to tell you that they do have the right in in a good chunk of that
01:08:44
content not in a lot of the copyrighted content that the big media companies have given them but a lot of user
01:08:48
generated content they do have the right and they are using it and they're legally doing it and then there's the
01:08:54
separate kind of body of content which I think comes for example from Tesla Tesla
01:08:58
has an extraordinary advantage that they were really pressed to put cameras on everything years ago and that gives them
01:09:03
this ability to build models that do self-driving so I think that there's a lot more data advantage that arises in
01:09:10
certain industry segments than others and that's where the moat will lie and that moat will allow you to actually
01:09:15
build better products that get you a more persistent advantage in gathering more data that's ultimately where I
01:09:19
think this resolves to it may not necessarily be about who's got the biggest data center Network yeah I mean
01:09:25
here the thing guys at some point the amount of data becomes the long pole in the tent at some point the quality of
01:09:33
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
01:09:40
there yet that's the one thing that counters the cheap AI means more AI is is there enough data and or algorithms
01:09:50
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
01:09:57
these ways um but I think this is an interesting sort of trade-off between some of these these variables I got just
01:10:03
got offered 2500 bucks to put Angel my book into because Harper Collins did a a deal with uh Microsoft and so I'm
01:10:11
thinking 500 per year I think it's for three years is the license and they just did this blanket license for every book
01:10:17
they didn't look at your sales they didn't look at how desirable it was it was just like a blanket deal everybody
01:10:21
gets 2500 bucks per book for 3 years and I think I'm going to just do it just to
01:10:26
support proper licensing so that people can start going down uh this path but let's get into Doge it's been a uh I
01:10:32
think we're in 10 days into this Administration and um Trump formally established Doge the department of
01:10:40
government efficiency in an executive order apparently elon's been spending a lot of time at the offices bunch of wins
01:10:49
doge is claiming on the interwebs to be saving American taxpayers around a billion dollars a day $3 for every
01:10:56
American every day about $1,000 a year in savings for each US citizen and they claim they can triple this and so for a
01:11:02
family five that would be about what $155,000 a year maybe $60,000 during Trump's uh second term we got $36
01:11:09
trillion in debt have fun with some numbers there if you like but the key announcement was a very
01:11:16
similar to the Twitter execution the ability for people to resign done in a very kind way eight months of severance
01:11:24
is is being offered to federal workers they expect 5 to 10% of federal workers to take this buyout
01:11:32
and it's um I mean this could be something like a hundred billion dollar in savings eight
01:11:39
months of severance um is not actually a legal concept that you can do so these are some sort of
01:11:46
buyouts and there's obviously some hand ringing about it but I think they're off
01:11:50
to a good start they've also been canceling leases as we talked about you know pre-election
01:11:55
there is so much space not being used that uh the federal government is terminating a ton of stuff they own and
01:12:04
going to sell it and consolidating folks and at the same time all of this is happening everybody
01:12:13
has to return to office who wants to go first here with uh you know the sort of first 10 days of
01:12:21
Doge I see some eggplant emojis in the group chat first 10 days how do group chat what's that about I'm adding you
01:12:29
right now how are you not in the group chat I'm adding you right now I'm literally every time one of these hits
01:12:34
the group chat it's just hilarious eggplants people are like oh my God we're not burning
01:12:42
tax and and the eggplant always comes from free bird first I'm outing him as an egg I'm I'm a I'm a big Doge eggplant
01:12:50
guy oh so much eggplant oh so freeberg tell us about how much eggplant you love this there's
01:12:57
nothing that I would say is particularly surprising in the first week a lot of this was kind of talked about leading up
01:13:03
to the inauguration VI and Elon published their piece in the Wall Street Journal a
01:13:08
couple weeks ago they talked about the mechanisms of action that they could utilize to kind of Drive reduction in
01:13:16
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
01:13:23
way the buyout offer is not new Bill Clinton did the same thing during his presidency yeah if you guys remember
01:13:29
when he tried to balance the budget get to a surplus which he did successfully and his intention was to actually reduce
01:13:35
us Death To Zero by the year 2013 and he had a very specific economic and fiscal
01:13:40
plan for doing that which he put into place incredible era I think we're seeing them take the actions that they
01:13:46
said they would do they said they would demand to employees federal employees come back to the office and they assumed
01:13:52
some degree of attrition from that and now the bi offer and we'll see how far things go with the courts with respect
01:13:59
to their ability to stop a legislative or statutorily mandated spending there's a big question mark here on how much
01:14:07
Authority the executive branch has in stopping spending and how much they're not allowed to stop because it's
01:14:15
demanded by law it's demanded by Congress and Acts or laws that have passed and so that's going to be the big
01:14:21
test here over the next couple of months a lot of lawsuits will fly but courts will ultimately adjudicate and we'll see
01:14:28
how far the Doge intention can take things and then there's a separate set of efforts around legislative action
01:14:34
here there's about a $2 trillion annual deficit right now in the United States um federal government 2 trillion a year
01:14:40
and if you look at the the doo book on why countries go broke you know there's a pretty simple kind of arithmetic in
01:14:46
there which is not complicated it's just at the end of the day the US needs to get our federal deficit down below 3% of
01:14:54
GDP which means we've got to cut about a trillion trillion one of spending if we
01:14:59
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
01:15:04
doo interview as you cut spending interest rates will come down because right now there's a pretty significant
01:15:11
selloff in treasuries and a lot of risk associated with the US's ability to deliver um its debt obligations over the
01:15:17
next 30 Years which is why 30-year treasuries are at 5% right now even though the Federal Reserve is cutting
01:15:22
rates the rate on treasuries is going people are still selling off treasuries that also inflationary it's also
01:15:29
inflationary Dave yeah for sure and so as we cut spending we also will see that the intent that the there will be less
01:15:36
inflation and the US ability to pay back their debt obligations over the next 30
01:15:41
Years goes up so the rates will come down and so there's actually a really nice kind of cyclical effect as these
01:15:46
Cuts start to come into play the rate at which you can make the cuts actually affects the the amount of cuts you have
01:15:51
to make the faster you make the cuts the less you have to cut and that's a key kind of principle going into this which
01:15:56
I think we should expect a big Whirlwind of cutting in the next couple of months
01:16:00
or an attempt to the courts will adjudicate what needs to be legislated and then they're going to go to Congress
01:16:05
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
01:16:10
was not a single member of Congress that I spoke with who views cutting to be a mandate for them in the laws that
01:16:15
they're trying to pass they all have a very different kind of agenda than D well look this is this is really one of
01:16:21
those interesting things where it's like the difference between legislature and executive branch is like doge is really
01:16:30
bringing it to life is like what powers and controls does the executive branch have to spend and not to spend and
01:16:39
especially to not spend when it's been legislated to spend this is where the action is like there's no law that says
01:16:47
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
01:16:53
no law that says that the executive branch and again I don't know the all the the laws sort of the rules or laws
01:16:59
about whether you know how they go about doing it but let's say presumably they're doing this and there's some
01:17:05
legal backing behind it like they just go and do it and now they're not spending money if it was really hard to
01:17:12
hire people and they could even make it harder to hire people do they do they fight bureaucracy with bureaucracy that
01:17:18
it's harder to spend harder to hire people harder to procure certain things that you're supposed to spend money on
01:17:26
you can reduce the spend through a lot of very interesting nuanced friction rules that they're in control of yeah
01:17:33
some friction could slow things down they're talking about putting competency tests in they're talking about giving
01:17:38
people reviews and maybe they have to hit some standards and the gentleman's riff I mean when you force people to
01:17:43
come back to the office you're going to lose 5 10% of people and 10% take the buyout and now all of a sudden we're
01:17:49
saving things I mean it'll be interesting to see if it's 5 or 10% on RTO I mean that it could be a lot more I
01:17:55
mean what I'm hearing about these buildings is that they are super super empty like next level empty and
01:18:03
uh let's just say I'm really glad I don't hold like I'm an owner that has a bunch of leases yeah to the to the the
01:18:12
federal government right now yeah oh the government and you know what the interesting thing about those leases I
01:18:16
was talking to the DM at density which does people counting and buildings so they obviously um you know very
01:18:21
interested in that the government is such a reliable yeah client that they're all on one-year
01:18:27
leases so people don't you know do what they do with startups we just force them
01:18:31
to do five or 10 years because they know hey this company could go out of business they're just like yeah yeah
01:18:35
we're just on a rolling year-over-year lease so you can actually just cut these it's going to flood the market Shaman
01:18:40
your thoughts on also the stopping of uh because they're obviously going for it they stopped all payments which is a
01:18:49
part of the Playbook I saw a Twitter up close and personal which is hey let's let's turn off subscriptions and see you
01:18:55
know if anybody's using these subscriptions basically obviously a judge got involved
01:18:59
in that but Aid going to other countries you know we're just starting to look at
01:19:04
what are we actually sending to other countries and for what purpose and then there's a naming and shaming and maybe
01:19:10
appealing to the public through social media and saying hey do you want this money going here when hey we have
01:19:16
tragedies in our own country that need to be solved we have healthare we have houses burned down we have
01:19:21
infrastructure and so maybe you could talk a little bit about heart and minds and winning those and what your general
01:19:26
take is so far I think that we have to remember that we're only n or 10 days into Doge so the fact that we're already
01:19:32
at a billion dollars a day is really incredible and there has really been no discernable impact there has been a lot
01:19:41
of fissures of fake news and misinformation but the real impacts have been negligible To None since they
01:19:47
started making those cuts I think that doge is a three layer onion so layer one is the people
01:19:55
we have now given a pretty generous offer to folks and I think Elon said it it was
01:20:03
like basically the maximum allowed by these contracts but they tried to do a very good thing there the second as you
01:20:08
guys just said the second layer of the onion is going to be the infrastructure all the buildings all the
01:20:14
physical plants that the government owns and operates that may be empty that may
01:20:19
be idle and getting them back in into private hands so that they be they can be repurposed that's going to save a ton
01:20:25
of money but both of them will pale in comparison to the third layer of this onion which is the it and the services
01:20:34
and the spend and what I mean by that is when you read how the department is set
01:20:39
up at the center and nucleus of every single one of these Doge teams is an engineer and I think the reason is that
01:20:48
they can get into these systems of record and start to trace where the money is going and I think when you
01:20:54
start to on cover Through forensic analysis where these dollars are going and how it's spent that's probably how
01:21:04
you're going to close the gap from a a trillion to and I suspect to be honest it could be more than two trillion
01:21:10
dollars when it's all said and done that is an enormous amount of waste and it's
01:21:16
unproductive so I'm very excited for what happens over this next little while just the the transparency is going to be
01:21:22
incredible guys Just for kicks check the out right 2009 if we took if we took 2019 spend right the year before Co and
01:21:33
put it up against 2024 revenues $500 billion Surplus wow there go that's crazy versus versus the1 A5 trillion
01:21:42
dollar deficit so a two2 trillion swing on like a four four yeah on a$ four4 trillion doll budget that's all
01:21:52
waste well a lot of we've got a trillion dollars a year of interest payments now
01:21:57
I mean this is guys this is the thing like there's two deflationary things that we need one is Doge and two is
01:22:06
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
01:22:13
we gota this spend has to go or we're in we're in sort of like we're in Greek Greek territory if that makes
01:22:20
sense yeah and I think this is um the popular support for this this is pretty incredible I'll just go through a couple
01:22:27
of numbers with you you know looking at what people agree with that Trump's doing early on and what they disagree
01:22:35
with you know obviously we talked about it last week chamath pardoning the January 6 protesters and you know ending
01:22:43
requirements for government employees to report gifts that's sort of like the Supreme Court thing these are
01:22:48
tremendously unpopular and then if you go and you look at downsizing the federal
01:22:53
government and imposing a hiring freeze and requiring all federal employees to return to an office these are incredibly
01:23:00
popular and Elon tweeted these uh these graphs out as well so right now you have
01:23:06
Trump at the Apex of his political popularity and you have these issues specifically in a very
01:23:13
polarized time as incredibly popular he's also done an incredible job with the Border that's another
01:23:21
consensus-based issue so Trump now has downsizing the government and controlling immigration and getting rid
01:23:27
of violent immigrants as incredibly popular parts of his mandate and that's the big win for him if you look at his
01:23:35
popularity Trump is massively more popular than he was the first time round he's at 49% compared to last time 44
01:23:42
he's still the historically least popular president ever so my point in all of this is when you see Trump doing
01:23:49
things like his meme coin or you know taking on Pete Bud Jed today all that kind of trump 1.0 negativity grifting
01:23:58
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
01:24:03
agenda and that is as somebody who was a never Trumper as you all know in the audience and now somebody who is
01:24:09
supporting him relentlessly that margin that extra 10% of people who support him right now is
01:24:15
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
01:24:22
is and stay away from the Steve Bannon agenda and the grifting those are the things
01:24:26
that will take this all apart so that's my appeal to them I told everybody I give a letter grade I give them a b so
01:24:31
far could do better but pretty good less of the meme coin less of the dra you know we have to make sure that we're not
01:24:38
dragging dishwashers and teachers and and people who've been here 20 years out of the country and it's going to be a
01:24:44
very DEA important um approach here if this is going to be sustained and I think it's a coin toss if he will be
01:24:52
able to maintain his popularity and what he did today with this like I don't know if you saw the Pete budha Jed
01:24:57
he was attacking him over this tragedy that's the kind of stuff people don't want less of that please more of the
01:25:03
Doge that's my little rant can we talk to Travis about wh now Travis can I ask have you taken a production wayo yes
01:25:11
what do you think about it and do you think that's the future of transportation and how does Uber play
01:25:16
into the uh self-driving car business now I mean look it it's funny because as you guys know back in the uh Back in the
01:25:25
Day 2015 16 17 we had our own autonomous vehicles out there and I remember the first one of ours that I
01:25:36
took and I got in the back and all I had was a stop button a big red stop button
01:25:41
that I could push if things got weird yeah and uh I remember this is in Pittsburgh where we had our robotics
01:25:46
Division and autonomy division at Uber and I got out of that car and literally it's like I got off a roller coaster
01:25:54
like my legs were I could not stand straight like I was like a little wobbly cuz I was so freaked out and adrenaline
01:26:01
was pumping you get in a wayo today and it's like you you're not even thinking twice
01:26:07
you're just like it's all good you just get in you get out now part of it just the normalization it's
01:26:12
like it's just working and it that normalizing matters in terms of the psychology around it is we're just there
01:26:20
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
01:26:29
destination for what it means to get transported across the city in a vehicle that is not meant for a human to drive
01:26:37
no steering wheel you know folks potentially even facing each other you know just a whole bunch of different
01:26:44
formats the the technology works we know that there are different ways to get to
01:26:48
the technology I think the the probably the most interesting thing that we should be or one of the most interesting
01:26:54
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
01:27:07
out there and proliferates and gets broadly distributed we should expect autonomy gets easier and easier and
01:27:12
easier and you see some of the stuff that's happening with Tesla and FSD their new models are like I think in a
01:27:18
three-month period he they went up like 10x in terms of performance meaning in number miles per per human intervention
01:27:26
like they're seeing you know that's the thing that elon's seeing right now because cheap AI cheap good AI makes
01:27:33
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
01:27:39
that you're like okay there's the possibility literally that autonomy just gets easy and commoditized similar to
01:27:45
what's happening to AI the next part is okay you get the hardware you're like okay manufacturing's hard that's
01:27:51
interesting that could be a long pull in the tent I think that that could be a place where Tesla of course has huge
01:27:58
Advantage you then look at who are wh's partners are they getting set up to do the right kind of manufacturing and get
01:28:05
scale of cars out there but then there's like this dark horse that nobody's talking about which is it's called
01:28:15
electricity It's called Power and all these vehicles are electric vehicles and if you said you know I just
01:28:22
did some like quick back of the envelope Cals if all of the miles in California went EV ride sharing you would need to
01:28:33
double the energy capacity of California right let's not even talk about what it
01:28:38
would take to double the energy capacity in the grid and things like that in California like let's not even go there
01:28:43
even getting 20% more 10% more is going to be a gargantuan 5 to 10 year exercise you know look I live in you
01:28:54
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
01:29:01
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
01:29:07
neighborhoods in La that's just where we are so I think the the sort of the Dark
01:29:14
Horse kind of hot take is combustion engine AVS because I I don't know how you can
01:29:25
go fast getting AV out there really really really massive with the electric grid as it is
01:29:34
what do you think about regulation in this regard because obviously there was the
01:29:39
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
01:29:48
the tragedy in Arizona where somebody was playing Candy Crush when they were a safety driver you know what is what is
01:29:53
your outlook on on this stuff rolls out and somebody gets hurt and then that you
01:29:59
know tens of thousands of cities that you brought Uber to how receptive are they going to be towards this and what
01:30:05
do you think the regulatory framework will be like you know I think similar to how you
01:30:10
get normalized it's like you're used to getting in a car it's normalized psychologically and in the sort of
01:30:16
public sphere the public mindset you get used to it so like we're getting to a place where these vehicles are provably
01:30:24
safer than human driven Vehicles so yes there are mistakes but they are just provably safer and people are just
01:30:31
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
01:30:38
into like yeah it's just great like talk to people who are using it and they feel
01:30:45
safer from a of course like I I I feel like we're going to get in less accidents but also I feel safer because
01:30:52
there's like there's less chance of like an interpersonal problem that does happen especially you
01:30:57
know late at night you know when people are out partying and things like this there's just like there is a level of
01:31:04
safety on many different aspects to for the drive no it's for the yeah there's like there's there's safety
01:31:12
aspects across the board sure right what do you think about byd and like you sort
01:31:16
of mentioned everybody getting to autonomy at the same time obviously wh Mo's got the biggest lead Tesla's behind
01:31:22
them byd and about 10 other providers are out there doing this does does you know do 10 players get there at the same
01:31:29
time and then it's just who can incorporate these into their Network and what do you think of the strategy that
01:31:34
Uber's doing of hey we've got these eight Partners we'll take everybody into the network and we'll manage people
01:31:40
vomiting the back of cars cleaning them and charging them so look I think the big issue you have with anything Chinese
01:31:46
is will you be allowed to bring it in the US just period like you maybe kind of can now what happens with teror will
01:31:54
there be blocks and bringing this kind of Technology into the US what happens there I think that's a whole thing the
01:32:00
bet that Uber makes is that whether consciously or subconsciously it's like will AI will
01:32:07
cheap democratized AI happen and if so does that make cheap democratized autonomy then you've got to line up your
01:32:15
physical sort of Hardware Partners car manufacturers then you've got to say okay is the electricity where it's at
01:32:21
and are there other bets to make to make sure that I can charge my cars so like there
01:32:27
is a huge real estate play here and Fleet Management play of like how do I Electrify these plots of land known as
01:32:36
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
01:32:46
whole when you we talk that's super interesting Travis that's like it's almost like the idea that we all talk
01:32:52
about today is Data Centers and data centers need their own power substation in order to meet the Power demands but
01:32:57
if if we do see a world of Robotics automation generally and we've got these kind of moving robotic systems in our
01:33:05
world they need to have a similar sort of like power demand met that probably looks like hey they all go into their
01:33:12
their recharge building and they get recharged whether they're a car or a humanoid robot or a food delivery robot
01:33:18
on the sidewalk or whatever or Dr and they just kind of get recharged huh robots need actuators
01:33:24
you know what you need for an actuator a permanent magnet you know what you need
01:33:27
for a permanent magnet rare Earths who's the rare earth king X China Greenland Greenland let's go so so guys
01:33:39
I think there is a there is a there's a couple interesting things one of them is
01:33:44
going to be how are these companies thinking about real estate electrifying that real estate in urban environments
01:33:51
and robotizing that real estate so that they can do the servicing maintenance Etc look I guess it could be manual for
01:33:56
a while can I can I put you on the spot just go one level above it because merge
01:34:00
the last two concepts together you talked about we talked about the federal government Doge Etc isn't there the
01:34:06
potential for just a complete surplus of physical inventory that exists in America oh yeah okay so big time so what
01:34:15
does that mean for commercial re like how do you like navigate around that because you got to evade the falling
01:34:20
knives first so okay so let's just just go down ride sharing Lane it's autonomous ride sharing Lane you go down
01:34:27
that lane car ownership which is already dropping drops Like a Knife all the way
01:34:33
down and there's this thing in cities which takes up 20 to 30% of all the land it's called parking is no longer
01:34:40
necessary because cars are getting utiliz the cars that exist on the roads are getting utilized 15x more than they
01:34:45
were before per car so you need hypothetically 115th the number of cars maybe you could say fth or 11th because
01:34:54
you want to be able to Surge to like rush hour and things like that it depends on what kind of car pooling and
01:35:00
things like this are going on let's just call it 10x fewer cars on10th the land necessary for parking at least on Tenth
01:35:09
like maybe it's less than that okay so now you're opening up you're opening up 20% of the land in a city that just goes
01:35:19
fallow but what what should we do with that and is there a demand for that land well look I mean maybe it's the should
01:35:26
it be housing you know like and then don't we have to re-evaluate all of the city planning today because City
01:35:33
Planning today to your point Works backwards from all these constraints that are 1.0 constraints like here's the
01:35:38
traffic flow here the traffic patterns those don't exist theoretically anymore or they would exist in a totally
01:35:44
different way right yeah I mean we've got a there's like a massive amount of creativity to say what can I do with
01:35:49
that land at with a high Roi right like some people are like you're going to have Farms you know uh
01:35:58
hydroponic farms in urban environments I'm like uh you know that's not a bad idea if you want to have Farm to Table
01:36:04
healthy food it's literally Farm to Table it's like a mile away from you yeah so there's some interesting ideas
01:36:10
the land price has to really come crashing down and there's interesting ramifications if it were to do that you
01:36:15
could imagine that's that's what I wanted you to say not to try to get you there but that winess well that seems
01:36:21
like the crazy thing that nobody is thinking about which is in this push this physical built inventory has so
01:36:27
much value built up in the 401ks of of individuals to the balance sheets of huge Pension funds but that value is
01:36:36
could be very different right but the crazy part is is it could just be electricity production and electric
01:36:42
capacity on the grid could be the gating factor that makes it a slow burn potentially I'm just riffing here
01:36:50
guys right right right right right makes total sense and if want to see what happens when you have like unlimited
01:36:55
land if you live in Austin and you see the distance between San Antonio Houston and Dallas and Austin in that triangle
01:37:03
you know you get 30 minutes outside of the city centers there's just unlimited land and there's less regulation and you
01:37:08
know what's happened housing prices and rents have come down two or three years in a row so this could happen in other
01:37:12
major cities and if Doge has less regulation you can build more it could be amazing for Americans to actually be
01:37:18
able to afford homes again and maybe convert some of this space you go energy storage electric grid upgrades sort of
01:37:29
modular energy capacity upgrades like and production these are this is going to be very very important right now if
01:37:38
you want to I we do this all the time we have of course facilities all over every
01:37:42
major city in the US and really around the world utility upgrades is the long pull
01:37:49
in the tent in in construction development in a lot of our cities not all cities
01:37:55
but in a lot of our cities the FED um held rates they're getting close to the goal of 2% I guess we're at 2.4
01:38:03
2.9% in terms of inflation any thoughts on uh where we're at with the FED deciding to not cut and just uh you put
01:38:11
it on the docket here jamat any any wider thoughts there I would just say that the long end of the yield curve is
01:38:17
basically telling us that there's a still a chance for inflation so I think that the the question is these next 30
01:38:24
or 60 days from the administration I think are basically they're they're critical and I think if if Doge gets to
01:38:31
the three billion a day number quicker than people thought there's going to be a lot of room for I think the president
01:38:39
to make a very valid argument that rates are too high for where they are and that
01:38:44
we're going to be able to have a lot more cost control in the expenses which means that
01:38:50
they'll be less need to spend it doesn't solve the problem that Yellen created Yellen
01:38:56
and Biden on the way out the door the biggest problem was that they put America in this very difficult position
01:39:03
because they issued so much short-term paper that is extremely expensive and as all of that rolls off we have to go and
01:39:09
finance a ton of this debt at now 5% so it's still nearly 30% of of the debt is going to get refinanced this year and
01:39:20
then it's like what are these auctions going to look like guys this is the thing we we all got to bre the last
01:39:25
auction barely had 2x coverage and I think that that could take a lot of the energy out of the market watch the doo
01:39:30
interview because this this is exactly the topic he covers you know as we end up needing to refinance this debt the
01:39:36
rates climb the appetite isn't there and it becomes a spiral that's why we have to cut fast in
01:39:42
terms of the deficit to basically attract the market now you know the markets moved a little bit right so on
01:39:49
January 13th the 30-year treasury peaked at exactly 5% and it's come down today it's
01:39:56
at 4.77 so a little bit of relief since that that Peak as as kind of the administration's gone into office and
01:40:03
actually taken action but as more of this action is realized if people do appreciate and doge is successful and
01:40:11
the Court's adjudication does allow reduction in spending which I think is the intention I think we could see this
01:40:17
rate drop from 478 much more significantly than where it is and that'll create a great deal of and David
01:40:23
it's like it either does that or it really really doesn't or ites the exact super nasty
01:40:32
really bad that's right I got a text from someone who is pretty senior in capital markets thinks this is going to
01:40:38
go to five and a half% before it goes down so they think that there's going to be a little bit more of a turbulent run
01:40:45
ahead but it's like but the thing is it's like that whole thing of like it's going to get to five and a half before
01:40:49
it comes down it's like it spirals on itself it's like you got to print money to then get to that place and then the
01:40:56
printing drives it for you know you get to that spiral the problem is if we go to 5 a half% that's not 80 basis points
01:41:03
what you really need to think about is the total tonnage of actual dollars that need to get repaid back and if you look
01:41:09
backwards that's effectively like 10% rates from 2000 could you imagine what the economy that's right would have done
01:41:15
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
01:41:22
here where you can walk rates up to 5 half 6% without a lot of things starting to break this is why I actually think
01:41:28
Doge will be successful because as people internalize all of these things where every single Congress person
01:41:35
freeberg that may have wanted their own benefit for their Community they'll have
01:41:39
to take a step back because the broader optimization for America just needs to take priorities sham it just doesn't
01:41:45
work like that man like my thing is like I like I agree with the notion but I just don't believe that any individual
01:41:51
Congress person will take responsibility in this way no they won't they won't but
01:41:55
the question is can they block it yeah but or put another way again the executive
01:42:01
branch can slow roll spend in a lot of different ways except you cannot with Medicare and Social Security
01:42:10
discretionary spending is like 20% the mandatory spending Social Security Medicare Medicaid these are the
01:42:20
the larger outlay and this where where we come back to the fact that this will never I hear you get addressed until it
01:42:29
has to be because of the political suicide that arises I just think there's this is where I think elon's Fame can be
01:42:35
helpful and I mean very specifically this following idea you know that famous Sputnik comment
01:42:41
where NASA spent millions of dollars trying to engineer a pen that could write upside down and it turned out that
01:42:47
in Sputnik the Russians just took a pencil that is what we need to do to the US government because I suspect even
01:42:54
though there's a lot of mandated spend the real question that nobody knows the answer to Is is that spend useful so
01:43:00
even though it's appropriated by Congress there has to be a feedback loop that says you can just use a pencil you
01:43:07
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
01:43:14
and this is where I think Trump gets enormous leverage by having Elon being the westwing that nobody else could give
01:43:19
him the rest of us would just be chirping into the darkness yeah this is the naming and shaming of government
01:43:24
waste that's actually going to work and the Doge account on Twitter is doing it they're basically saying hey we're
01:43:30
giving foreign aid for this project for that project is it going to be perfect every time no but you show an empty
01:43:35
office space you show people not coming to work you show people wasting money well yeah if that's even real you know
01:43:41
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
01:43:47
projects and then you know they were talking about blockchain or whatever and supposed is a Report Elon is at like the
01:43:52
Govern building working on leases at the moment like this stuff is going to be extraordinar popular because you can
01:43:59
just take the number of 330 million Americans and whatever you just saved you can just divide it by that number
01:44:06
and tell every American how much they just paid less in taxes or how much they just saved individually the naming
01:44:12
shaming and doing the back of the envelope math for every American is going to work do we want to wrap maybe a
01:44:18
little bit on this tragedy in DC okay what are your thoughts uh we were talking with our friends Dayton who is
01:44:24
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
01:44:29
invested in to do uh pilot training I'll share two things one is anonymous it's from friend of mine gave it to me and
01:44:38
said I could share it who's a commercial pilot and he and and I posted this so I'll just read it honesty DCA is the
01:44:45
sketchiest airport we fly into I feel like the controllers there play fast and loose hence the periodic Runway
01:44:51
incursions I've said to every first officer in my threat briefings that we both need to be on red alert at all
01:44:57
times there DCA calls out Hilo traffic helicopter traffic and vice versa all the time but it's borderline impossible
01:45:04
to see them when you're bombing along at 150 mph I mean that's from a pilot that
01:45:10
is not I don't think he has any incentive to sugarcoat things and then I just wanted to read a message from Brian
01:45:15
uto who's the CEO of whisk who's building a lot of these aut autonomous systems he said said first autot
01:45:24
trffic Collision of voida systems do exist right now these aircraft will not take control from the pilot to save the
01:45:33
aircraft even if software and systems on the aircraft know that it's going to collide that's the bti flip that needs
01:45:40
to happen in aviation automation can actually kick in and take over even in piloted aircraft to prevent a crash
01:45:50
that's the minimum of where we need to go some fighter jets have something called automatic ground collision
01:45:55
avoidance systems that do exactly this when fighter pilots pass out and it's possible for commercial and then the
01:46:02
second he said is we need to have better ATC Air Traffic Control software and automation right now we use VHF radio
01:46:10
communications for safety and for critical instructions and that's kind of insane we should be using data links Etc
01:46:18
the whole ATC system runs on 1960s technology they deserve better software and Automation in the control Towers
01:46:26
it's totally ripe for change the problem is that attempts at reform have failed so I just wanted you guys to have
01:46:34
that one from this commercial pilot and then two from Brian uto who I I think understands this issue really well
01:46:39
there's so much opportunity here to make this better this should have never happened our other friend Sky Dayton has
01:46:44
been pushing really hard for the US government to do Advanced pilot training one of the things that he says
01:46:51
constantly is just that a lot of the push back is just Union rhetoric around what they perceive the right thing for
01:46:57
their constituency is and hopefully this starts this conversation because I think
01:47:02
guys like Sky guys like Brian are working on this next level of autonomous solution that can just make flying
01:47:11
totally totally safe beyond what it was the crazy stat is that we haven't had a commercial airline disaster in the
01:47:16
United States in almost 25 years isn't that inredible 15 yeah it it's looking like pilot era here and it's there seems
01:47:23
to be some question of why these Apaches are flying around this really crowded airspace and it seems like they're
01:47:29
shuttling you know politicians around and maybe that's not the best idea in this really dense area as your pilot
01:47:37
friend was referring to jamath so God thoughts and prayers and all that stuff for the um for the families of the
01:47:44
people who died it's just terrible tragedy terrible tragedy yeah it's just this really just this is an area to
01:47:50
invest money and use the private private sector and all this incredible Innovation that's available to upgrade
01:47:56
these systems and infrastructure this has been another amazing episode of the all-in podcast thanks Travis for joining
01:48:01
us thankar for coming a lot of fun guys first time this is my first time on a podcast ever yes right in you come back
01:48:09
anytime you were great man appr it apprciate very based is going to like it tell us what you think and we'll see you
01:48:16
all next time love you boys byebye let your winners ride Rainman David and instead we open source it to
01:48:28
the fans and they've just gone crazy [Music] with besties that's my dog taking [Music]
01:48:47
driveway oh man we should all just get a room and just have one big Georgie cuz they're
01:48:53
all this useless it's like this like sexual tension that they just need to release
01:49:03
somehow we need to get [Music] mer I'm going in