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facts will come out over time let's wrap up on uh Google Google dropped 7% after reporting earnings on Tuesday chamath Revenue up 12% year-over year to 96.5 billion wow Cloud revenue is up 30% year-over year 12 billion YouTube ads surging 14% to 10.5 billion net profit was around 26.5 billion up 28% year-over year so they are really focusing on profitability obviously full year numbers this is just extraordinary total revenue 350 billion with 100 billion in net profit cloud and YouTube finished 20124 with a combined run rate of $110 billion doll YouTube is basically Netflix inside of uh inside of Google and their Google cloud is essentially AWS inide of Google the thing that made investors get concerned shth is that Google said it would invest 75 billion in capex in 2025 42% jump over 2024 29% more than analysts expect obviously this has to do with data center servers and the AI buildout what do you think about that number 75 billion obviously in relation to what we saw with deep seek doing it with maybe a little bit less maybe they're lying is this just an absolute waste of money or gargantuan number or is it something they can easily with that amount of profitability and cash they have absorb and use in the future I think I should stipulate that Google's models are probably the best of all the models across a broad base of capabilities if you test for them and so let's start there which is whatever they're doing is working the thing that they need to do is be able to translate those models now into better products and I think that that will happen slowly like for example if you look at Deep research most of the people online that are evaluating deep research would now say that open aai is both faster and just better on the margins all of these things can be improved I don't think that's a comment on the base model I think it's a comment on post training and how they're attempting to productize these things so the other thing that Google has is a money machine that directly benefits from these Aid driven optimizations on ad targeting the only other company that has anywhere close to the same credibility is meta so I think what both of these two companies need to do is do a better job of explaining how that 75 billion gets segregated how much of that goes to these AI enabled models that actually do better ads optimization there's a there's a really interesting discussion by a former meta machine learning engineer onx about how they did it it's pretty amazing it's staggering but if they could say half the money goes to that and the other half goes to more speculative you know pre-training and posttraining I think the market would have eaten it up so it's probably more of a disclosure issue for Google because I would say right now their model quality is the best you have thoughts on this buildout Antonio obviously I think you've been involved with xai uh and obviously involved with Twitter and X previously and colossus's colossal buildout that was extraordinary to watch in such a short period of time do you have concerns that like some people do that this buildout is too expensive and there would be too hard to monetize all that expense or is it uh maybe a little bit of hand ringing and the opportunity in AI is so obviously huge that you just got to take the leap of faith and and and if you build it the revenue will come yeah I think choth has the right framework here which is R return invested capital and what he's saying by you know if Google had said hey half the money is for ads and half the money is for buet post training the market would have seen that half the money has a high return of capital and Google's rning capital is actually going up uh after the impation of of AI models into their into their company and I I think that sort of abstracts the entire Market which is people are waking up that return invested capital and data s will matter that the models are basic Commodities and super competitive in the best case it's kind of a a land warn Asia it's a melee in in a worst case just total Commodities what does matter is the return on Capital data center which is influenced by how good the data centers are so you mentioned the xci data center it's 100,000 GPU cluster it's the most dense coherent cluster in the world and it will just train faster and better than other clusters and it's also built for the most cheaply and the fastest so XI have the highest train on Capital and I also think the best train data and therefore will win I think Google will also win because they have U their tensor flow chips they make their own some of their own chips they do focus on roic and they have a great Monopoly to kind of fund it all so I don't think it's over blown I think that I think this is going to be as you guys have said before in the podcast you know bigger than Industrial Revolution but uh it's also true that you need to have a good roic and if you don't you're not transparent about it you can see what happens chath popatia recently came out to rant about people losing hope in Nvidia and making the deep- seek debacle a bigger issue than it actually was while the market is scrambling and the Bears are out of the woodwork chath is detailing all the reasons that make him believe Nvidia will surge back to glory and Beyond after their February 26th earnings report and it is not all just about the mere excitement that comes after a huge event let's delve deeper into his reasoning and find out why Nvidia is still the number one choice welcome back everyone to invest ocracy I mean that's the game we're seeing on the field how many companies are we seeing hit a million dollars in Revenue with five employees where that used to take yeah 25 so the efficiency is there chath your your outlook on this issue since it seems to be coming up again specifically with truck drivers and Uber drivers and all kinds of other research jobs that seem to be be doing pretty well um or can be done pretty well by AI where where do you stand on this issue today I think it's a process Buffett wrote about this in an annual letter and what he described was the changing nature of jobs during The Agrarian Revolution and what you saw was a large cohort of people who supported themselves through farming and then the total Quantum of those jobs shrank by 90% when you had industrialized farming and tractors and whatnot but the economy to Antonio's Point grew around that business and added other kinds of businesses that didn't make sense in that moment and I think what you see is that when economies get more and more evolved you see the growth of services businesses that sort of are these things that can only happen when you have excess right the person that you pay for closet organizing would not have had a job in the turn of the agrarian Revolution or the Industrial Revolution but they can they can exist in 2020 something and frankly they can make a good job the life coach there are all these jobs that just kind of come out of nowhere podcas or influencer all of that Venture venture capitalist Capital allocator absolutely mutant strawberry Creator yeah so I think that I think that you're cut that waiting for this next turn of creativity like the big problem that we all have maybe I'll take the more glass half empty version of what Antonio said is we really haven't been unlocking people's creativity over the last 15 years we've been trending around except safe of a few companies which we all know and we can just repeat them endlessly but we know which ones they are that are truly innovating and at the edge everybody else is kind of diddling around Naval gazing so the real problem is that we have not had a lot of reps in being creative I'll give you just a very simple example Nick can you find this even extremely state industries did you see the byd clip of the car and I thought Park yes with a little swipe it's how tragic is it that you look at this and you're blown away yeah and you're blown away for two reasons one is a I didn't think that that was possible and B why doesn't exist in America but the reality underneath the hood is extremely benign how this is implement and so I think that the problem is we spent so much time losing the script I think Antonio is right when you unshackle people to not focus on the mental load of getting the pronouns right or the this or the that you won't be so overwhelmed by things like this because you will have already been pushing the boundaries of human creativity we need to get back to that we need to let these creative people cook and I hope I hope that that happens I think that that will happen nvidia's stock has taken quite a hit primarily due to the recent unveiling of deep seeks highly efficient AI model but let's not jump to conclusions faster than a day trader on caffeine nvidia's future rests not just on existing Ventures their new Blackwell architecture proclaimed to train AI models four times faster than its predecessor Hopper is creating quite a buzz don't have much of an opinion on that to be honest I think that sort of along the lines of what I said on the prediction show I think that way more and are going to run away with this market and I think it's going to force a bunch of consolidation in the traditional Auto o I think the interesting thing is that they really doubled down and created a pretty decent test bench for robotics I thought that was pretty interesting so I think that reinforces what a lot of smart people including you know what freeberg and Gavin also spoke about just in terms of the long-term future for robots I think that that was cool I was I was a little confused by the low-end PC I don't understand what the point of that is maybe it like creates some crazy deepin Market where you can buy GPU and then contribute it to some distributed Network and allow some distributed workload to run on that I guess I don't know I think it's a toy a hobbyist kind of device that becomes like a bridge and we see this often in technology where somebody creates like even the original PCS let's face it they were kind of like toys and OB devices arduinos and the original drones were kind of hobbyist yeah I guess the point is a toy to do what because if you're trying to do inference like everything is telling us that we are reaching the limits of training and that's an LL though right the point is it's not yeah let me get to yeah yeah so so in this world of AI that we know it today there's training and there's inference and right now we think that there's training that's at a limit and so now the market shifts to inference so if you're going to buy this jacked up personal computer what are you going to use it for my suspicion is some sort of test time compute use case which is an inference use case but it's not clear to me why that's a better solution than all of the AI accelerators plus tensors that are now just prolifically being exposed to the market whether it's Amazon exposing what they've done whether it's Google exposing what they've done a whole Litany of startups exposing what they've done so I was just confused I don't really know what the whole point is on another note nvidia's stock could almost be called a bargain right now while typically not one to be bundled in with the word cheap nvidia's recent trajectory lends itself to a forward price to earnings ratio of just 26 times forward earnings a detail that like an overlooked appendix in a dense financial report warrants attention compared to the S&P 500's average of 22.3 times forward earnings Nvidia offers a premium that's not astronomical reconciling this deep seek news in in your own mind as it relates to this stock would you think it's worth um are you as Resolute in that belief as you were pre deep seek news Well a deep seek you know definitely was a shot across the bow for you know American Tech and I I would say most of all to a name like open AI uh because it really sort of put under scrutiny um you know it's not enough just to raise billions of dollars from Venture capitalists who have an endless checkbook and just think that you can spend spend spend and you're going to have the best models I think what what deep seek showed is that Ingenuity and kind of necessity being the mother of invention and how you optimize your different algorithms to get the most out of your software can mean just as much uh as as the the Nvidia chips themselves uh so I think I saw I saw more of a threat to um to the the big llms anthropic and such but for NVIDIA Nvidia is such a poster child for AI in general and so we have the you know the double ETFs the triple ETF so it it just it just was such a shocker that it really took it down I I stuck with it because I believed it was overdone and I you know despite the fact that we have to work smarter uh at how we build these models I don't think there's anybody who's going to you know pass on the opportunity to get their hands on some Blackwell chips or Reuben chips next year if they have the opportunity so I think the order book for NVIDIA is going to show to be really strong we've seen that with that Google capex guide and the Microsoft capex guide so I expect I expect Nvidia to be just fine with major clients continuing to pour Capital into AI development and burgeoning technological advances like the Blackwell Hardware on the horizon Nvidia shows no signs of slowing down as investors debate whether to capitalize on this dip the key question remains what are your thoughts on nvidia's position in the market amid these developments
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