Elon won after all

Do you know what Microsoft, Google, and Anthropic all have in common? I'll give you a hint. It's the title of the video. They're all massively constrained by compute. The CEO of Microsoft said directly that they grew a ton Q1, but the problem that they have is that even with the additional data center capacity they're bringing online, they expect to remain capacity constrained through the first half of the fiscal year. That literally is them saying we cannot make more money because we don't have enough compute for it. Here is Sundar, the CEO of Alphabet and Google, saying directly that they are supply constrained even as they're ramping up capacity. This is a company that makes their own chips, and they still don't have enough. That's why Anthropic partnered with a company they hate, SpaceX. The same Anthropic that banned xAI and SpaceX from using their models they were concerned about distilling is now paying a billion dollars a month to use SpaceX's spare compute. And apparently Google thought this was a good idea because now they're paying SpaceX 920 million dollars a month for compute as well, because everyone is desperate for GPUs. Every way I check, standard H100s on PCI are just not available anymore cuz the demand is so insane. What's even crazier is this goes beyond GPUs. So companies like Western Digital, the hard drive company, sold out for all of 2026 as of February. Things are pretty crazy with compute right now, and I don't think most people understand the severity of the problem. I want to do my best to break this all down for you guys, but if I want to be able to afford the RAM that I just bought, I need to take a quick break for today's sponsor. Today's sponsor is without question the single product that people ask me about the most in my comment section. You've seen me use it before. It's WhisperFlow. Wait, that's ChatGPT. Isn't there already a voice-to-text thing there? There is, but it's nowhere near as useful as WhisperFlow. Just watch. I'd like you to explore the T3 Code code base at T3 Code URL and tell me what you think. Notice what it did there. It replaced the words T3 Code URL with the GitHub URL. That's not a thing it will do by default, although it does do a lot well. like it auto-capitalizes things correctly, it knows proper nouns, it learns from the mistakes when you go back and make changes, it saves those. It's awesome. What it's way cooler for is the ability to set up snippets, and I use these all the time. Like, I even do silly things like, "Who is today's sponsor?" Today's sponsor is WhisperFlow is what it puts out instead. I'm a fast typer, so I didn't think WhisperFlow would be for me, but the more I use it, the more I realize it makes me better at prompting. I'll actually talk a bit more and go in detail in ways I would have when I'm using my keyboard. But, even cooler is when you combine that with the power of their snippets. I also don't like loading up my projects with skills cuz I find when I do the agents reach for them when I don't want to. So, treating snippets as a way to save a bunch of skills has been really cool. For example, grill me skill. It just pasted the Matt Pocock grill me skill, so I don't have to have it saved in the project. I can just type it, hit enter, and now it's going to grill me. I could go a bit further if I want. For example, G Stock office hours. Yes, I pasted the entire G Stock office hours skill into my WhisperFlow, so I can say three words and have it run. Because you should feel a little guilt before you run it. There's so many little things WhisperFlow gets right, especially for developers, like their ways of hacking cursor to make the file paths work is crazy. They're a really good team, they built really good software. I didn't think I would like it, and I ended up loving it. See why I'm so hyped at sodalite.link/whisperflow. The reason I'm making this video today is because of the Google SpaceX deal. The Anthropic SpaceX deal surprised me, but like Anthropic's not a compute company, they're a model company. Makes sense that they didn't have infinite GPUs. Google is making their own compute. Google manufactures their own TPUs. They build the chips that they plan to run their inference on. In fact, in February of this year, Meta signed a multi-billion dollar deal to rent chips from Google. So, while Anthropic was buying from a competitor, cuz like SpaceX is Grok, they make AI models, Anthropic is Anthropic, they make AI models. They weren't buying the thing they compete with. They're buying the tools they need to increase the competitive nature of their product. Google sells compute and they sell models. So, despite the fact that they sell and rent compute to companies like Meta, they are still so low they have to go buy it from companies like SpaceX. And that is how we got here. The compute crisis. The amount of compute available has gone up meaningfully year over year, but nowhere near as fast as the demand has gone up. There are many layers to this problem. Obviously, there is the massive demand, but there's also the complicated supply chain problem here. Because making GPUs is not trivial. One of the other severely underrated problems here is actually power availability. Because as more compute comes online, we need more power for it. I'm going to do my best to visualize this problem, but it's admittedly going to be difficult. So, bear with me as I try to figure this out. We're going to go through the layers of how sand effectively becomes the prompts that you're writing and getting responses to. We're going to start a little higher up the stack than we probably should. Like I'm tempted to go into quartz, but we'll avoid it. It will start with where most of the things that matter do. TSMC. TSMC is the Taiwan Semiconductor Manufacturing Company. It was formed by a person who used to work at Texas Instruments in the US who left back to his home country of Taiwan in order to build better manufacturing of semiconductors as a generic layer for other companies. Previously, companies would make their own semiconductors and fab their own like process and also make the processors themselves. But, TSMC doesn't sell something you buy as an end user. You can't put a TSMC chip into your computer. You give TSMC the plans on how you want to manufacture your chip and then they help you with the manufacturing process for it. So, every company doing compute now from Apple to Nvidia to AMD to Intel works with TSMC to fab the silicon that they use for their chips. Apple was one of the companies that bet on them biggest initially and others have slowly started to realize TSMC's manufacturing is just far beyond anywhere else in the world and have relied on it more and more heavily as a result. As I mentioned before, some out of their allocation is already purchased up front by Apple. Apple's historically been such a big customer of TSMC and has so many crazy deals with them, they have managed to hold strong with their allocation for a while. That's why they are not having the issues with making new computers or manufacturing new phones that a lot of other companies have because this particular spot in the pipeline and in the supply chain is really strongly purchased and agreed upon for them. So Apple is still relatively marked safe at least in this layer. Don't worry though, that will change as we go. The rest of this was split across lots of other companies, but over time the section of this that is for Nvidia has grown massively. So every couple months Nvidia wants to increase their manufacturing more and as a result the amount of this that belongs to them gets bigger and bigger. Let's just say it's like the majority here and then whatever is left is everyone else. So Apple gets their little share here, Nvidia has a big chunk here and then there is whatever is going on up here. This is just one of the things Nvidia needs to make a GPU though. So right now the size of how much Nvidia can do is at best this big cuz this is the amount of TSMC manufacturing they have, this is how much they can do at best. But there are other things they need in order to make their GPUs because not only do they need all of the TSMC manufacturing for it, they also need memory. And high bandwidth memory manufacturing is a very interesting space because historically like it was important to have good RAM and there was lots of companies that would purchase from the high bandwidth memory manufacturers. Most of the time though, their work was going into consumer devices. They would sell NAND chips that could be used for RAM or for SSDs, and they would sell that to companies that needed RAM for their devices, whether it was Qualcomm to put in phones or Apple to put in phones, or if it was to companies like Crucial or SK Hynix or whoever else that makes memory for users to put into their computers, or if it was to Dell to make memory chips that they would put in their computers. The high-bandwidth memory chips were a very diverse set of places they would go, but there was really only three manufacturers that mattered. SK Hynix, Samsung, and Micron. Historically, they have split their allocation across lots of different groups. But now the demand for things like GPUs is so absurdly high that they have reallocated entirely. SK Hynix maintained a consumer brand of memory called Crucial, and most of the RAM in most of my computers here is from Crucial. Crucial no longer exists. Sorry, it was Micron, not SK Hynix. My bad on the memory there. There's three of them. Sor- Sorry, I made a mistake. Micron was the owner of Crucial, and Micron has decided to shut down Crucial. Micron has made the difficult decision to wind down the Crucial consumer business. Micron will ship Crucial consumer products through February of this year with warranty and support continuing. Micron Crucial consumer products may continue to be available for purchase from distributors and resellers for some time. That is the case. I bought 64 gigs of Crucial memory a few days ago. It was very expensive. So, all of this allocation used to be split across consumer manufacturing of consumer hardware, lots of other devices, and then data center use cases, and GPU use cases. Since AI requires so much RAM to run, even smaller models like Deep Seek V4 Flash require over 100 gigs of RAM. Memory is super valuable to these businesses, so the need for it has skyrocketed, and with such, prices have skyrocketed as well. So, Nvidia needs a allocation of this as well, and the price of that allocation is skyrocketing massively. I will say that the numbers in these charts, like the the percentage split here, is not super accurate. TSMC has reported that Nvidia is only about a fourth or so of their manufacturing allocation right now. So, this is a huge chunk here. This is just meant to emphasize the point, not to be literally TSMC's majority Nvidia. Just trying to make this as easy to visualize as possible. Give me some creative wiggle room, okay? So, we have these two key components that are necessary for Nvidia to be able to make GPUs, but there are other layers here as well, and not all of them are directly in front of Nvidia, either. Because in order to run those Nvidia GPUs, you need a few other things. First, you need hard drives. Because you need somewhere to store the data that these GPUs are actually operating on, and apparently, the demand for hard drives is skyrocketing like never before. Last year, I bought four 16 TB hard drives refurbished from ServerPartDeals, one of my favorite sources for hard drives, for about 170 bucks each for 16 TB drives. Worse 16 TB drives than what I have in my NAS right now are going for $360, more than 2x the cost when my purchase was in 2024. Insane. I just bought a handful of 28 TB drives, and they were like 600 plus each. I spent like $3,500 on hard drives recently. It's crazy. So, hard drive manufacturing is also very tight right now, and something that like consumers have barely even needed for a while, cuz we all moved to flash storage. Hard drives are still useful for lots of big archival stuff, especially when they were cheap. But now, hard drives are like as expensive as SSDs were not long ago, which is unbelievable to me. So, if a company is able to buy all the Nvidia GPUs they need, but they can't get enough hard drives to actually run them, then they're not going to buy those GPUs cuz they're making all of these decisions up front. So, if there aren't enough hard drives, then Nvidia's manufacturing capabilities barely even matter anymore. But then, all of this gets bottlenecked by yet another layer, power. How much power is available? Power grids are struggling right now. Electricity demand growth is led by an increase in the commercial sector, which is expected to outpace residential demand in 2027 for the first time on record. We are now at the point where industry use of power in the US is higher than consumer residential use. This is why these big compute companies like Microsoft with Azure are starting to invest in power, like actual introduction of new power plants to the grid, trying to get nuclear energy unblocked and more. And when you compare the rate of electricity generation in a the US compared to in China, you see how bad we have to catch up here. We are not introducing more power to the grid anywhere near fast enough. The amount of increase to the grid that China does in any given year from 2016 onwards is higher than we have done since the '90s. We should still be focused on making things more efficient, but we also need to have more energy and ideally more clean energy from resources that we know we can get it from. This chart scares me. I don't think we've properly prepared our nation for the increasing demand of power to get where we want to in the AI race. And if any one of these sections gets any smaller, it effectively works as a filter preventing Nvidia from selling more GPUs and preventing AI businesses from being able to grow and increase the number of customers they have. Everyone's compute constraint. Except for one company. SpaceX. And this raises a couple important questions. One is, why isn't SpaceX affected? Why are they so capable of having all this spare compute that none of their competitors have? And then we have question two, which is why not just make more? Like, why can't we just create more high-bandwidth memory? Why can't we just fab more silicon? Why can't we just make more GPUs or create more hard drives or increase the power availability by making more power grids? Why can't we just make more? Well, as much as AI has accelerated our ability to [ __ ] out new software, it has not made it particularly faster to break ground and create new manufacturing for things like silicon. TSMC estimates that additional fabrication capabilities can take as much as 8 to 10 years to build up. When they decide they want to make more chips and they want to do more manufacturing, they have to start planning 8-plus years ahead and they're often selling the allocation off of these theoretical presses that don't exist yet 6 to 8 years ahead. Apple's deals are insanely long-term in that regard. Despite the insane growth we've seen at companies like Nvidia, TSMC is only seen about a 40% growth in their revenue year over year. Not because the demand isn't massively skyrocketing, simply because they can't supply the demand as it skyrockets. People are buying out allocation years in advance because they have to, cuz they can't get it right now. There's a reason TSMC's the only company doing this well and it's because they invested really heavily, really early, and it took them a decade and a half of failures to get there. Ready for a really funny fact about TSMC that not a lot of people know? Remember this? Bet you didn't know this was TSMC's fault. Microsoft and Nvidia were two of the first companies to bet heavily on TSMC manufacturing. TSMC used an external vendor for the effectively the glue that they would use to seal the chip. And that manufacturer was not correct about the thermal range in which that paste actually operated properly. And the cause of the red ring of death was that getting really hot and then cooling over and over again would cause that glue to loosen causing the chip to come slightly off of the slot that it was meant to be in. That's also why you could wrap your Xbox in a towel and turn it on until it overheated or throw it in your literal oven and that would temporarily fix it because when the glue got warmed up again, the chip would fall back into the slot supposed to be in. But then when the glue got cold, it would pull the chip out of the slot. And that was because TSMC didn't have good enough process to detect these types of failures in their manufacturing cuz this was early in their history. So the Xbox failed so Nvidia could win. As silly as that is, they just took a long time for this company to get their [ __ ] together. Not that long ago, TSMC's process was not thorough enough because they were still new and getting all this [ __ ] right is hard. And the result was that they weren't even reliable enough for game consoles. Now we're relying on them to power the entire [ __ ] world. And the same goes for all of these other sources of manufacturing. Things like high bandwidth memory is not easy to produce. There's a reason only three companies in the world can do this. And those three companies are also making all of the chips that go into all the SSDs that we use, all of the phones that we use, all the SD cards and CFast cards that we use for our cameras and things. All of that is made by three companies. And those three companies can make the same thing for Nvidia instead. Why would they sell us consumer chips that sell okay at reasonable prices when they could sell way more to Nvidia? So to put it simply, we are trying our hardest to manufacture more, but it's going to take a long time. And if you get your bets wrong here, you're kind of screwed. If TSMC ramps up production so they're making 10 times more silicon, but the hard drive sector doesn't pick up enough or HBM doesn't pick up enough, then they just spent billions of dollars spinning out fabs for demand they no longer have because everybody is constrained. I guarantee you if Microsoft could snap their fingers and spend three times more money to get two times more compute, they would do it immediately, but they can't because every single one of these bottlenecks needs to be resolved together. If TSMC does 10x production, we just get constrained on HBM. If high bandwidth memory also 10x's, then we get constrained on hard drives and power. We need to bump everything up and if any company bets too hard on one specific piece that they are in this puzzle, they get screwed. And this also ties into the first question of why isn't SpaceX affected? Because SpaceX and Anthropic are kind of opposites here. Anthropic had the concern if they overbuy GPUs and they don't have the demand for their inference or the models don't work as great good with scaling laws as they hope where more compute means better model. If any of that goes wrong and they purchase too much compute, they're out of money and they fail. Anthropic was a little conservative with their compute bets last year and that has screwed them because now the compute they could have bought last year isn't available anymore. Elon had a lot of conviction about compute becoming a bottleneck. He believed this was going to be a really big deal. So he overbought compute for SpaceX and Grok and xAI. That went kind of poorly for them because Grok just didn't do great. A lot of the best researchers that were at xAI have since left. The progress they're seeing just isn't great, but they already bought all of this compute. Thankfully, they learned how valuable that is and that if they can't use it, someone can. And now this compute that they spent a lot of money on, let's see it. How much did xAI spend on Colossus one? Apparently, building the initial phase for the Colossus deployment was only three to four billion dollars. They are now renting that compute for a billion dollars a month. In 4 months it pays for itself. Another one of the reasons xAI was actually kind of well equipped for this is the power constraints because Elon with Tesla knows a lot about power and was able to make deals with Tesla battery manufacturing in order to make sure that their power would be reliable. And if they were ever constrained by the grid, they would have enough backup power to last for some amount of time. They also did crazy stuff like gas-powered generators, which is funny from the guy who made the electric car company that made electric seem much more valuable to then go burn a bunch of gas in order to power his GPUs to make racist AI. But at least they're making money off it now. So it turns out that compute was as much a bottleneck as Elon had predicted, but their need for it didn't go up as much as he predicted. So in order to make money off that bet, he's now reselling it to companies like Anthropic and like Google, which is still just so crazy to me. Like I honestly thought it was a troll when I saw this post today that SpaceX is now doing a billion dollars of compute a month through Google. That Google's paying them a billion dollars every single month, 12 billion a year almost, just for compute. Google's revenue last year was 400 billion dollars. That means that 3% of Google's total revenue is now going to xAI. It's now going to SpaceX. It's now going to one of their competitors. This is up there with Google's deal with Apple where they pay Apple billions of dollars a year to be the default search engine. Like this is that level of crazy. The point I'm trying to make here is that however bad you think the compute crisis is, it is probably worse. Whenever you think you see these companies pinching pennies cuz they want to try and squeeze more money out of you, it's probably not that. They're probably just dealing with the compute crisis because they just don't have enough compute available for all the demand they're getting. And if you think they could just fix this by making more stuff, they kind of can if everybody makes exactly more enough in the demand sustains for long enough. But right now, the winner is whoever has the GPUs. And at this point in time, that winner is, funny enough of all companies, apparently SpaceX. But also, OpenAI, who I've managed to not mention at all so far. Because OpenAI made the bet a couple years ago that compute would matter, that scaling laws would matter, and would go and buy all the compute they possibly could. This is the real reason why Anthropic's rate limits are so much less generous than OpenAI's are. They have been considerate of the compute crisis since before it even really started. And that put OpenAI in a really good spot. Google pretended they could work around it by making their own chips. That didn't go great for them, and now they're stuck paying Elon for their mistake. Anthropic didn't want to overspend on compute, they screwed up, and now they're paying Elon for their mistake. There's only really one winner in all of this, and that winner's Nvidia. Because they know how in demand their stuff is, and they literally cannot manufacture enough to keep up with the demand that exists. They can't really make less money right now, because as long as any of these other bottlenecks get resolved, their amount of GPUs they can sell just keeps going up. They cannot make enough, and if everything resolves, it does great for them. If most things resolve, it still does pretty great for them. So, Nvidia, congrats. You're going to be holding your position in the stock market for a while, it seems. And this is not meant to be financial advice, this is just my read of how chaotic things are. I hope this breakdown is helpful as you question why your cloud code keeps running out of usage every couple hours. Ha. I think I've said all I have to on this one. If you want to build a computer, now might not seem like the time, but it's going to get a lot worse before it gets better. So, if you're staring at an SSD that you wanted for a while, or some RAM, or a GPU, and you've been holding off hoping that prices go down, this is not financial advice, but realistically speaking, I don't expect this stuff to get cheaper anytime soon. The demand is just too insane, and the world is changing around us. I don't think our phones are going to keep getting faster and more powerful. I think they're going to rely on the cloud more and more as the compute that we use every day gets centralized in these big players' hands. The world's going to look very different than it did when I was a kid building computers for my neighbors, and I don't know if I like that. I'm just trying to do my best to share where things are going so we can all understand and have better conversations about it. Let me know how y'all feel about the compute crisis and if you think I'm overblowing it. Until next time, peace nerds.