> And Google is a major shareholder in SpaceX, so they certainly have incentive to juice the valuation of the IPO.
Google own 5-6% of the shares of SpaceX. SpaceX is seeking a valuation of $1.77T which means Google's shares would be worth $88.5B-$106.2B. I'm not a skeptic of AI/LLMs but this makes me deeply suspicious of these circular deals. What happens when the music stops?
You seem to imply that with this deal their shares are worth 88B but without it they're worthless.
It's very hard to know how much the deal actually increases SpaceX market cap, but unless Google exits their SpaceX position soon it doesn't even make much sense as a circular deal.
Google also just announced a new equity raise of $80B. I have no idea if doing this via equity vs debt is trying to suck some of the wind out of the IPO Market for Anthropic and OpenAI but it’s going to be interesting to see how the markets deal with all the new equity being floated. Someone isn’t going to hit their raise targets and the later IPOs may be the ones holding the bag.
The music would have a risk of "stopping" if these deals were backed by a speculative entity. However AI actually has real value/revenue, and is not a speculative product (i.e. people aren't buying tokens to resell them, a token is "consumed" at moment of inference)
Enron collapsed due to legitimate fraud. To imply Enron is an apt comparison requires assertion that AI companies are actually cooking the books. Is that what you are saying?
The ARR were fine but showing skewed quarterly profitability numbers by slowing down research due to hitting compute capacity suggests otherwise.
I am certain Anthropic spent less on building the next model this quarter if they make it to profitability due to the shear fact that they don't have enough compute.
Which solves the profitability problem with relative ease momentarily.
Also just to confirm, AI subscriptions are definitely being sold at a loss how big I don't know but these models are much harder to run.
API is definitely being sold at a decent profit.
So if you rate limit users and do usage billing + lower research costs which is a money pit temporarily.
(Proof is the fact that we don't have a new pre training run since 4.5 yet, they used to do one every 2 releases)
4.9 will probably be the same.
Next model Mythos doesn't seem to have a successor yet and was trained previous quarter most likely, they don't seem to have pre trained another one just improved Mythos if at all.
As much as I am into AI these attempts to show that there can be a profitable quarter seem like cooking the books, even if we assume no shady dealings otherwise.
Unless one of the Labs can say for certain training is going to stop they can't be profitable and I don't think training can stop because marginal gains is all they have.
8-12 months behind narrative for Chinese labs literally is going to kill the company that stops training first.
If we assume only a 3-6 month gap once China has more compute, then well then even if they keep training the lack of ability to arbitarily scale data centers in US, will kill them first.
DeepSeek V5 might actually just end the AI race for good.
Also given Mythos is atleast a 10x model compared to Opus, then it's pricing is likely going to be 10x as well so well token prices are likely never coming down, especially if these companies want to IPO.
Why would V5 kill the AI race? Do you believe that there are diminishing returns on model intelligence when applied to real-world tasks?
I think there are accelerating returns: i.e. a models are still not good enough to be “drop in” remote workers, but once that threshold is passed, the value of each token of inference has a far higher multiplier.
This justifies the buildup. However not everyone agrees that model intelligence will continue scaling thus they assert that eventually the economics will hit a wall.
>Also given Mythos is atleast a 10x model compared to Opus, then it's pricing is likely going to be 10x as well so well token prices are likely never coming down, especially if these companies want to IPO.
I don't know why people say this when cost per unit of intelligence has been going down continuously over the past few years. When Opus 3 was first released, its API cost was $15.00 per million input tokens and $75.00 per million output tokens. Opus 4.8. which is significantly better, is $5.00 per 1 million input tokens and $25.00 per 1 million output tokens
Please address the primary point first: Selling some product does not disprove speculation.
In the case of Enron, people were obviously speculating in its stock, and that remains true regardless of why it collapsed later, or even whether it collapsed at all.
I say "first" because if you still can't agree that speculation in AI stocks even exists, then it's pointless to discuss what people might be doing to exploit or encourage it.
Speculation exists for every security. However wrt revenue numbers, Anthropic/OpenAI’s revenues are largely made of companies/individuals purchasing tokens. Enron’s was accounting which stated future potential revenue as current earnings. They are not the same. Enron pulled off a lot of shady schemes to hide their accounting practices. All of the “circular deals” AI labs are doing are publicly known and clear to see, so its not like anyone who knows what a circular deal simply knows something everyone doesn’t.
Circular dealing or round tripping is a form of cooking books and sometimes results in accounting fraud. Especially when circular revenue is booked without cash flow growth. Do you see cash flow growth on any side of these transactions.
We are basically dealing with the fallout of the 2008 GFC bailout to this day.
The fiat economic system is irreparably broken, and we are circling the drain. Another bailout is _probably_ inevitable. But the cycle sure as hell isnt resetting and we are speeding towards something... what it is is unclear though, and when is also unclear.
The part people cant wrap around is the scale of it and the time it takes to go through the super cycle. Theoretically, it all started with the Dot com bubble, which indirectly cause the housing bubble, which caused the GFC. Which caused whatever happened in 2019, which caused QE in 2022 under the guise of COVID, which is causing whatever the hell is happening now.
Capitalism has become uncorked, and money is irreversibly flowing to the top at an increasing rate. The logical next stage is that like 75% of the world's population is literally not even part of any economy. And that doesnt really make any sense
Sigh, no. Money is not flowing; company valuation might be, but that's temporary and only works if the company keeps delivering insane amounts of value.
yeah I intuitively have felt something like this has been happening, too. And finding the evidence is such an immense task, and feels way out of my current energy level.
When COVID was ongoing there was a term floating around I liked, "Psychosis" was it. The spell is like that of, denial? Terror & shock?
Trauma might be better?
Looking at trauma responses and how to detect it in humans is an interesting perspective to look at all this with. Personally, if I look at it from "people are afraid, traumatized, defending themselves" and use that to extrapolate how most people (the masses, the non-rich) would act and also the rich - that points me to why theres such a sudden hastening of action and pace of wealth up towards the top in the name of AI & war.
And you would have been massively wrong. People have been complaining about quantitative easing since post GFC, and if you took the figures at face value, those would imply inflation was nearly 100% between the end of GFC and before the pandemic. Whatever you thought about the post-pandemic inflation, the period between GFC and pre-pandemic definitely did not see the level of inflation implied by those figures.
> "The idea that inflation and the money supply are linked is one of the most dumb one in folk economics"
"folk economics" implies it is by untrained people.
Milton Friedman's famous quote of "inflation is always and everywhere a monetary phenomenon" shows that he deeply believed the relationship between inflation and money supply, and one certainly cannot call Friedman a "folk economist" considering he won the Nobel prize in economics and was a professor at the University of Chicago.
Note: I am not saying he is right or supporting his belief. I am merely stating that such a belief is not a "folk economics" belief. This belief is still very prevalent in the freshwater schools of economics. [1]
As a personal anecdote, at Ronald Coase's 100th birthday party, I personally got Gary Becker and Richard Posner debating a very related topic (whether and by what degree the velocity of money of fluctuates and whether helicopter drops of cash would have been better during the early days of the money supply collapse in 2008/2009 than just giving money to the banks). In a room full of Nobel Prize winning economists in 2010, there was a very rigorous debate on the topic.
Lagged processes are one of the most fundamental concepts in economics. If merely recognizing the possibility that one could be at play here is throwing you for a loop, you need the simplified monetary model more than most.
Someone told me this isn't "fraud". (Was in another one of these hacker news thread where a guy called all this Brilliant Financial Engineering). How is this not unethical at least, it befuddles me.
Maybe we've come to celebrate unethical behavior and its become so normalized that we forget to ask ourselves what should be allowed.
Government hands Wall Street another bailout to the tune of trillions of dollars. Wall Street executives and hedge funds use funds to enrich themselves as usual. Main Street and tax payer get fisted again. These massive data centers go bust. Get gutted during bankruptcy and foreclosure proceedings Public deals with the fallout with no help from government.
The sci-fi SpaceX S1 talks about asteroid mining and other imaginary chimeric stuff like space data centers... while 80 to 90 of the case is about AI. But their AI case is like BMW bragging about their thriving auto business...while renting all their car factories to Toyota.
It’s funny because that is a guy with enough sense to both see what is going on and also not short it, because he knows that none of this actually matters with regard to stock performance for a properly frothy investor class.
It's not interesting to say "this is a bubble!" I've heard that about virtually everything (and in many cases it's likely true). What is interesting is pointing out the mechanics that make the bubble pop.
This is precisely what makes the movie the Big Short interesting: we see that people did identify, within a reasonable time frame, when people would start defaulting and how that would cascade into a true crisis.
It's pretty clear that while the fruits of AI are quite useful, the entire thing is rife with very questionable financial engineering... but I still don't know what it is that makes all of this break. For example, it's obvious that the SpaceX IPO is a massive wealth transfer program, but it's not obvious that it will immediately end in a crash. Given how irrational the stock market has been, I don't see a reason it can't continue to be irrational for long after the bag has been handed over to the retail investors and retirement funds.
I dont think so. These entities and the hardware they own would be bought for legitimate AI use long before they'd hit the open market. AI is very useful, and even profitable at the inference level. It's just an open question whether this monumental amount of spend for research is worth it.
Until someone can come up with a better option though...
Note that a pension plan that invests for you blindly is no better - either the returns are so bad that they are a scam, or they are investing in stocks anyway and so you get the same results but less control. Similar for things like social security, they are either worse options or you need to pump stocks.
This doesnt fix the systemic issue. Most people put their money in a target fund and leave it alone. Those target funds are at risk of being forced to buy these over-inflated assets. The incentive to do this is there because those target funds and naive investors exist.
This is what financial capitalism and "democratizing finance" has meant in practice. Rich people have access to different types of investments, and by the time those trickle down to common investors the juice has all been squeezed out. Whatever the trend is, by the time you hear about it the market has already been arbitraged by faster investors with more resources.
We are not going to come up with a market-based solution to fix income inequality. The solution, as much as people in the dwindling middle class resist it, is a strong social safety net coupled with a hard reset on taxation and housing policies. Nobody should be homeless, nobody should be allowed to starve, but you might have to accept that your 401K goes down in exchange for a government guarantee of housing and food.
This is hard for people to accept because they currently have equity in their home or a 401K to save them from starving. But those are transient, individualistic solutions. You can lose your house. You can lose your 401K. Society should be taking care of each other in a broader way than letting everyone accumulate a little, private pile of money.
If the S&P 500 dropped 20%, that's about a year's growth. Long-term investors who bought before that would be poorer than they thought they were, but they're not worse off than they started and there wouldn't be any particular bill to pay. If they're a long term investor then they can wait for it to come back. (A similar argument could be made for larger drops.)
The real suffering comes from whatever effect there is on the rest of the economy due to a recession, more layoffs, etc.
When money is cheap you take it. Google sees all the capital waiting to pour into these AI IPOs, and correctly assumed they could tap into that with little dilution.
It makes good financial sense for a company to sell shares when the price is high and do stock buybacks when it's low. I guess they think the price is on the high side?
Also, selling shares puts them in a better position to survive a downturn (more cash, less debt).
Google is also issuing a bunch of debt this year. It sounds like they need a lot of capital and want to keep a particular debt/equity ratio, rather than having a strong opinion on their share price.
There's no realistic way for the music to stop. The demand for LLMs is staggering and the big providers are charging full freight for inference. They might not make back the money from training but these data centers are definitely going to be fully utilized for at least the next 5 years.
> the big providers are charging full freight for inference.
Except they're not. Anthropic's claims of temporary profitability line up exactly with when SpaceX is giving them discounted compute, OpenAI's such a shitfest they threw the CFO off the glass cliff for daring to push back against the IPO. "Profitable on inference" is an unsubstantiated rumour.
Just look at the copilot changes. Demand switching to other providers immediately when prices rise, and there's not even certainty that the new copilot prices cover costs.
> They might not make back the money from training
This is an understatement. With all the datacenter buildout, they need trillions. For the investors get their money back and the bubble to not implode, they functionally need to unemploy everyone in the US.
The pricing on Open router is clear. Anthropic, OpenAI, and Google all garner a massive premium over deepseek and qwen. There's no other realistic explanation except that they're making bank.
Why do you think Chinese companies can do that? It's government subsidising price they do it with literally every ibdustry.
Home grow a bunch discount them federally, let them wipe the foreign markets.
If AI is threatened by china why would US NOT do the same? If they did they're in a much stronger position to do so than china. Cheaper energy, more cash, stronger industries.
Infrastrucure is thr kind of thing that only a foolish US admin would let fall apart to their advesary.
And yet they are not profitable on an ongoing basis, and aren’t even claiming to be.
The supply is currently constrained because 50+% of data center plans were cancelled as a result of the impossibility of the buildouts happening in a timely fashion, and subscriptions are charging a small fraction of the actual cost of inference, leading them to all bleed money, hence the rush to IPO to get one last infusion, since many of the past investors have publicly stated they aren’t putting any more money in until they see an ROI.
Unemploying everyone was what openai described as their success condition when it was founded a decade ago. There was a q&a on their website that said "How will you know when you have reached AGI? When the system performs most or all economically valuable work." Lots of people thought they were joking, or it was marketing, but they were 100% serious from the first.
Data center operators are in the business of selling electricity. They do not command large PE multiples. This is an even worse business, because xAI decided to also be the bagholder for the NVIDIA graphic cards. Not to mention they finance an unreasonable number of 20-somethings on way too large salaries with shitty opinions and no AGI delivered.
This take clearly has a bone to pick. But ignoring that, the first sentence is just not reflective of the reality here—xAI is making a killing on renting out its GPUs, way more than "just power". The dynamics that normally make infrastructure providers have slim margins don't apply when demand far outstrips supply; the situation right now is closer to monopoly pricing power.
It will likely take a few years for supply to fully catch up, which means xAI will eat well for a while.
I can see a world where a few data centers come on line this year and reduce margins a bit, but it's crazy to think the margins will go to "cost of electricity plus a few percent" anytime soon.
Datacenter operators who rent space are selling electricity. SpaceX is selling a fully built datacenter with compute designed for a specific purpose. They’re operating at a higher level of the value chain and can charge accordingly.
What's their novelty or moat to maintain the value chain? And why do we only see google, who already owns it, raising their hand to rent at these prices?
I’m not sure they need novelty or moat. AI compute resources are so scarce that inference providers will buy whatever is available. SpaceX sells inference hardware in bulk, with a proven track record of running inference and training workloads at scale.
They're not any sort of bag holder. They're going to make back what they spent on these data centers in a year.
It's a fairly sweet deal for everyone involved. Anthropic/Google get to sell more tokens and xAI gets a war chest for another bite at the apple. I don't have much confidence that they'll do anything with it but that doesn't mean these deals don't make sense for them.
> the big providers are charging full freight for inference
They're not and it's not clear why you seem to believe that. The immense capex for buildouts, training costs, etc. are not rolled into inference costs. Moreover, companies are already rapidly starting to re-evaluate token spend.
* Company valuations around LLMs are not realistic
Both can be true, much like they were during the Dotcom bubble. The internet turned out to be a pretty real thing. A couple examples below might feel familiar in the next couple months/years.
> Blucora (then InfoSpace): Founded by Naveen Jain, at its peak its market cap was $31 billion and was the largest Internet business in the American Northwest. In March 2000, its stock price reached $1,305 per share, but by 2002 the price had declined to $2.
> Broadcast.com: A streaming media website that was acquired by Yahoo! for $5.9 billion in stock, making Mark Cuban and Todd Wagner multi-billionaires. The site is now defunct.
> eToys.com: An online toy retailer whose stock price hit a high of $84.35 per share in October 1999. In February 2001, it filed for bankruptcy with $247 million in debt. It was acquired by KB Toys, which later also filed for bankruptcy.
> GeoCities: Founded by David Bohnett, it was acquired by Yahoo! for $3.57 billion in January 1999[20] and was shut down in 2009.
> MicroStrategy: After rising from $7 to as high as $333 in a year, its shares lost $140, or 62%, on March 20, 2000, following the announcement of a financial restatement for the previous two years by founder Michael J. Saylor.
I was expecting this comment. You know the answer. A scam will keep scamming.
There are also legitimate companies from the dotcom bubble era like amazon, microsoft, and intel. They all were vastly overpriced during the dotcom era. Probably also now lol.
I am of the same mindset as you, but you also have to look at PE multiples of Cisco in 1999 and Nvidia today. One being the "ammunition" supplier in the battle for the Internet, and the other supplier in the battle for AI.
Cisco was over 400 at one point and Nvidia is around 30. Not quite the same.
Other players today:
- Digital Realty 48x
- Equinix 75x
- CoreWeave (still losing money)
There is likely a bubble of some type here, but I don't think this is the same as the Dotcom bubble.
The circular financing aspects in the current era are really obscuring some of the financials. There are also very legitimate companies offering very real products. The big issue today is that things feel a lot more obscured and interconnected, which makes it hard to discern shit from gold. Does not help when the gold and shit are swimming in the same circles and shaking hands with all the same people.
Retail investors are currently being set up to hold that bag, and presumably the companies themselves will get government bailouts, so the taxpayer gets hit coming and going.
It's not even subtle at this point, what with the attempt at S&P rules changes, the insane valuation, the attempt to change the trade-through rule, and more.
It's not just that there's a circular deal it's that they're prevalent. And worse, with frontier labs IPOing seeking astronomical valuations that means a lot of the public is now exposed too (even if they don't all get fast-tracked into eg; the SP500).
The problem is the valuations assume astronomical growth... that is likely impossible for all of them to simultaneously achieve. Which means something's got to give.
Answering that question requires determining how much of the valuation is predicated on growth in AI spending from Google->xAI, but not counted as a forecasted expense for Google, and similar for other deals.
Circular deals aren't bad; what's potentially bad is if those deals are misinterpreted by active investores.
Google rents from SpaceX enough to show profitability, so that SpaceX can IPO and make googles early shares worth more than enough to pay for the renting they're doing.
Great deal for Google but they end up basically just paying spacex to pay them back, right?
I believe you've described "investing with a hope for a profitable return" which is usually the point of investing.
Circular investing is a thing that is happening with all of these companies related to language models. Google hoping for a ROI isn't a great example of that.
Buying the 5 percent stake is investing, but is paying them to be sure they can IPO normal? It reminds me more of Microsoft paying apple or Google paying Firefox or something.
> A lot of people are emotionally unprepared for a world where the music doesn't stop.
I've been wrong before. However, when was the last time this business model made sense -- that facebook, SpaceX and others, all just pivot from their market niche to general purpose AI datacenter providers.
How on Earth does this make sense?
What happens in a few years when DeepSeek runs on the chinese chips like the Huawei Ascend at a fraction of the cost ?
These are all very high value added companies going into comodity AI hosting and they're all going to make a killing?
Yeah, the doomsayers always say that. I'm hearing about bubble bursting at least once a month for last few years. This time it will burst for sure, I swear bro!
The level of denialism when faced to confront hard realities of the world around us never ceases to surprise me. Alas AI capabilities continue to rip through expectations and the next goalposts are moved.
Bubble bursts, somewhere between 2008 housing crisis and the dotcom bust.
Really dependent on if there are any OTHER structural problems to compound a fast re-valuation of tech stocks. There's plenty of noise about banks holding large amounts of bad private credit debt. There could be a lot or only a little collapse. There's so much uncertainty and the combination of war, high oil prices, and uncertainty about tarriffs that the market struggles to value anything as international fear drives investment into the US and high prices confusing whether growth is growth or just inflation.
Definitive peace in Iran combined with some sort of sobering AI news signaling the end to the infinite growth party could crush the markets.
The post-information age has never felt so well-named as it does lately. Investors dumping billions into completely unproven and, largely, undesired tech. Why? Because the Valley doesn't have anything else to sell, seemingly.
Either way, as always, we'll do it the American Way: Privatize the profits, socialize the losses.
>The post-information age has never felt so well-named as it does lately. Investors dumping billions into completely unproven and, largely, undesired tech. Why?
Eh. There's too much money. Covid response involved printing a lot of money and it all ended up somewhere. The chaos of the current administration has made everything considerably harder to price and the coincidental rise of the LLM has put us in strange situation that is legitimately difficult to price things correctly.
> There's plenty of noise about banks holding large amounts of bad private credit debt.
This is still only big enough to cause funny banking collapses not actual 2008 scale financial disasters. Banks hold a lot of bad debt, but it's isolated from consumer accounts. Might not want to hold equity in SoftBank though.
> There's so much uncertainty and the combination of war, high oil prices, and uncertainty about tarriffs that the market struggles to value anything as international fear drives investment into the US and high prices confusing whether growth is growth or just inflation.
The big concern lies in what the Trump admin will do. Things could end up merely a bad recession, like the Dotcom and Telecom bubble.
Or they can attempt to keep the bubble going once it collapses, crashing interest rates, and doom the US economy.
On other hand private corporate credit freezing might take down lot of business that need credit lines to operate regularly. Even the not so bad zombie companies. Tightening up and not being able to revolve credit anymore could lead to bankruptcies.
> I'm not a skeptic of AI/LLMs but this makes me deeply suspicious of these circular deals. What happens when the music stops?
A financial crash that will make the 2007ff crisis look tame in comparison. That is why Anthropic, OpenAI and SpaceX (which xAI belongs to) are all going public soon and why NASDAQ bent the rules to include them... the current owners all want to raid pension savings worldwide [1] to get their payday before the bubble inevitably bursts.
And when it bursts, you can bet that the vultures will use their fresh cash to buy up assets at fire-sale prices. For the truly rich, a boom-bust cycle is only one thing, an opportunity to achieve extraordinary profit.
It's hard for me to see this being bigger than the great recession unless there's some vulnerabilities in the banking system we're not aware of. However, the amount of money that's being spent is going to demand a large return that I'm not sure will be made whole given the scale of investment in a time frame they want
> It's hard for me to see this being bigger than the great recession unless there's some vulnerabilities in the banking system we're not aware of.
The scenario I see is write-offs. At the moment there are hundreds of billions in IOUs being passed around, much more in liabilities than Lehman had back then in 2007. Compounding that is the frankly insane valuation - it's as clear as day that at least one of the major AI shops will go bust, they all run at a (huge) loss and sooner or later, one of them will run out of cash before achieving market dominance.
Unfortunately, OpenAI and Anthropic are valued at almost 1 trillion $ - backed by nothing but the hope on the winner surviving and achieving the classic VC-backed near-monopoly. The staff can be poached, they don't hold much in IP like patents, the servers and GPUs are mostly owned by third parties like AWS, Microsoft, Google or Oracle - once the cash runs out, they can't sell any assets for even some runway extension because there are no assets. Even the model weights and training data aren't worth much - all competitors already have training data sets of their own, it does not make sense to acquire further data, and model weights are being rendered obsolete by the constant churn of open-weight models particularly from China.
SpaceX is valued even higher, but unlike the other two candidates, they still at least got a viable business even if the entire AI BS bubble collapses, Starlink is a money printer and there's no alternative in sight that matches SpaceX and their reusable rockets.
Now, if either of the three even experiences a large drop in valuation for whatever reason, it's not just experienced VCs that can readily afford (and expect) investments to fail, but this time a lot of "everyday" investment vehicles (such as pension funds) will have to issue write-off losses, and now that they are publicly traded, that may also trigger stop-loss cascade orders further dropping prices, and retail investors will probably join in on the mass panic. That's the #1 risk IMHO.
The #2 risk is that after a collapse, the service providers (i.e. the ones owning the servers) will be sitting on a ton of hardware that has nowhere near recouped its cost. AWS, MS and Google can probably repurpose most of the hardware for their own use and rent out what remains, but they will have to eat significant accounting losses, provoking again a drop in their stock price, but this time with even more blast radius as all three of them are established stock index (and thus ETF) members that a looooot of people have exposure to. But someone like Oracle? They might actually get fried for good.
And the #3 risk is further downstream, particularly relating to NVDA. They have enjoyed years of insane profits because they are the only ones making high-performance AI chips. When demand for new chips collapses due to the event(s) I just described, they can easily shift their TSMC production slots back to GPU wafers and sell these to gamers - but at a far lower profit than before, which again can trigger stock price drops and write-offs.
I won't go further downstream - TSMC and their suppliers are IMHO pretty safe because there is just so much pent up demand from everything not AI, and the construction companies building datacenters don't have too much of a blast radius when the big guns stop expansion projects.
The concrete scenario I'm really, really afraid of: all three succeed with their IPOs, maybe they all survive a year and get included even in S&P 500. The existing shareholders and insiders all slowly dump a lot of their vested stock onto the public market, which in cleartext means into the dozens of billions of $ of retirement contributions. One day, the bubble bursts for whatever reason. The stock markets drop in a panic sell-off, either triggered by stop-loss orders or because retail investors are a herd of sheeple (just like in the 1st covid lockdown). Eventually, circuit breakers on the stock markets will trigger (just like they did in the GME post-apes collapse) and trading will pause, but it will resume until the markets have adjusted to the new valuation... and once the dust clears up, there will be a lot of blood on the floor. Possibly even riots, depending just how much retirement assets just got wiped out.
Weren't we just talking about how SpaceX is valued based on some profits from starlink + tons of speculation?
Yet when we learn of this new $26B in yearly revenue (2.2B/month from Google and Anthropic)the conversation does not return to that discussion. It transforms into:
"xAI's tech sucks"
"Google/SpaceX is Structurally Bad for the Economy"
etc
This is called motivated reasoning. We get new information and instead of the obvious thing, updating prior conclusions, we just find a different way to react negatively. The negative reaction will be achieved. The narrative here is completely polluted by people who dislike Elon/SpaceX.
Think two things can be true at once. They should be using their capital to achieve their speculative price. Instead, they are using their capital to achieve a modest ROI, thus invalidating the speculation AND proving they have tech issues in what the speculation is around.
There is a shortage, they are short lived assets. It's a blip and unrelated to their long term profitability and valuation. They can't make a long lived business of building and renting out compute at those margins.
It was definitely a smart business move. It should be troubling to any shareholder than xAI is unable to utilize this infrastructure as renting it out to competitors.
> he narrative here is completely polluted by people who dislike Elon/SpaceX.
Hard disagree. It's polluted by Elon in general (pro and con), just like Tesla's idiotic valuation.
But in this case, a pivoted business model fundamentally changes the value proposition, and I'm not clear why "this space company making money on space things is now pretending to be a compute reseller and that's a good thing" is the narrative you think is preferable.
It's also beyond lame to essentially subtweet a "narrative" instead of responding to it directly. Who is "we", aside from a transparently dishonest way to pretend consensus exists?
I have the pro account for ChatGPT, Claude, Gemini, and Grok.
They all have various strengths and weaknesses. My favorite is still ChatGPT, then Gemini/Claude, then Grok.
Grok often feels 1-2 generations behind the competition in general use, but it has three things that I love:
1. It seems to be the best at understanding current events. Maybe due to X integration, or some other tool call optimization in the backend? I don't know, but I often ask about things going on, and the other models have outdated info, give unhelpful answers, etc.
2. It is generally the least sycophantic for personal things. Anthropic is getting here too. ChatGPT and Gemini are working on this, but previous models in those families would almost never say anything negative about what I am doing. Sometimes I need career advice, personal advice, etc and I like the tone of how it responds. I think Claude will be caught up soon.
3. For professional work, there are certain topics that other models would refuse to engage with. At my last company we had an enormous amount of legal users. When a deposition would need a summary on certain topics, most models would refuse. Grok would not. I understand the need for safety and I don't blame the other model providers, but for some professional use cases you NEED a model that is capable of handling sensitive subjects.
I recently worked with NRC dataset, specifically about nuclear reactor events and status reports(example: https://www.nrc.gov/reading-rm/doc-collections/event-status/...). Public data that just needed some cleaning. Several time Claude API would refuse to engage. Because of that I can't trust Claude to clean production data sets.
1. It seeks to manipulate the information you see and your lens to the world. This is already partially true from independent and major publications.
As soon as we hand over searching out information to social media algorithms and LLM tools, we abandon our ability to see reality outside our direct vision.
Grok's ownership has already demonstrated capacity to influence major world elections and other events. You cannot trust it with this sort of information gathering and reporting.
Almost too much so, it often feels like opus is pushing back for the sake of pushing back. The way old models used to add disclaimers to every message regardless of content
All 4 of these still regularly insist that I am a genius and everything I say is brilliant. Grok definitely pushes back more than the others, but I don't like how sycophantic they all still are.
I don’t want to open up that whole can of worms but Grok on any vaguely philosophical or political topic is a scaredy cat and has a very hard time staying factual if it could make Musk or the conservative movement appear negatively.
My favorite was ChatGPT, and I still use it often, but it becomes way too 'hair splitting' argumentative too often over very minor non controversial topics. Like it's always going out of its way to "well actually..."
Grok used to be really really bad ~8 months ago or so, but it's gotten better.
ChatGPT team needs to turn down the 'disagree just because' factor by a lot.
I guess the benchmarks disagree, but whenever I need to find specific information that does not easily show up with a web search, I try chatgpt, gemini and grok. Grok surfaces what I was looking for more often than the others.
Things like "find the github repo from 2017 that does $vague_thing".
Eh. It was a leading model for a few weeks, it was a real effort, but they never built a real revenue model around it. It wasn't SaaS, it wasn't for governments, it couldn't get B2C payments. Made it hard to justify the training cost to stay at the frontier.
And they are planning (well "planning" if you believe Elon) to start building their LLM over from scratch, which means they need a HUGE ass training data center, i.e. not a data center for inference to do so.
Pretty funny how making it anti-woke made it suck, whereas Claude's ultrawoke sensibilities and "constitution" didn't prevent it from being the de facto leader of the pack the moment it came out
It's a general problem of defining yourself in negative terms. Being "un-{thing I don't like}" doesn't say what you are. It only excludes one possibility while leaving behind an infinitude of mostly crappy alternatives to try to choose from.
Having a positive set of beliefs annoys people and and can make them feel judged, but at least it provides a vector that points somewhere definite in possibility space.
So we know what they are renting these GPUs for. I'm really curious about the input costs of their power generation. Is there actually enough margin in these deals for xAI to cover their depreciation cost?
Edit: from the footnotes:
> Colossus actually runs largely on its own on-site gas turbines, which comes out even cheaper: at a simple-cycle heat rate of ~10,000 Btu/kWh and Henry Hub gas at ~$3.50/MMBtu, the fuel bill is only around $90mn a year.
OK, that's crazy. How can I get into renting GPUs to hyperscalers?
I suspect that this is the start of a play for SpaceX's orbital datacenter project - if they're really planning on launching as many satellites as they've said (and Starship is going to massively lower the cost of launch), they won't be able to fill them with Grok. So perhaps it's best to become the infrastructure provider to the other AI Labs.
Makes sense. Very difficult to catch OpenAI and Anthropic now since their flywheel of generate revenue, use revenue to buy more compute, train a smarter model with more compute, made it hard to compete.
Being able to supply compute makes more sense for SpaceXAI if you can't compete in SOTA LLMs anymore.
If xAI is a datacenter REIT, it is a special kind that has a promise that no other datacenter provider could dream of: LEO datacenters. As far-fetched as that may sound, the biggest profit center for SpaceX in my understanding was Starlink. xAI already has extremely high-bandwidth connections from Earth to LEO available. Connecting that to solar powered orbital datacenters seems doable in realistic timeframes, especially once Starship comes online and gives them a significant boost in launch capacity.
If that ends up being viable and profitable, there is no realistic competition for decades. In this view, xAI earning a reputation as a reliable AI hyperscaler is just another tactic in that strategy.
Technology has a very short life. The difference is that a REIT might contain an office buildings that can be used for any business, but a data center is filled with carcasses that start rotting and stinking from the day of installation.
The idea that the AI data centers would depreciate in just a few years is plain wrong. The argument was that new chips would be so much more powerful and efficient that it would be cheaper to buy and operate the new chips than to just operate the old chips. Except that demand is significantly outpacing new chip manufacturing, and until it catches up years and years from now, the efficiency argument doesn't matter at all.
No, that's silly. Chips don't rot like produce. Some components will go bad and will need to be replaced. The owner can choose how fast to replace them depending on how prices look in a few years. The rest of the building (including things like power) will still be useful.
i think what op meant is they're instantly out of date. You're not going to be able replace every GPU in your datacenter on every new release from Nvidia and customers are going to go to whoever has the highest performing gear.
> While this doesn't include opex[2] and depreciation, if the deals continue for 18 months, xAI recoups all the capex they spent and still has many hundreds of MW of GPUs available. With the giant compute shortages likely to persist into the medium term, even older H100s are likely to be extremely useful even 18 months out.
xAI is more than half of SpaceX revenue with the Google sublease. SpaceX is looking like a datacenter REIT.
Moreover they're leasing compute - the actual infra around it is much less important - and how long does anyone expect heavily utilized GPUs to run? How likely is SpaceX to be able to re-lease this compute capacity? It will be broken down or out of date in 2-3 years.
This should be essentially ignored in the long term for SpaceX business prospects, and is low margin business that barely justifies a 10x earnings multiple let along a 100 revenue multiple for the xAI unit.
It makes sense. They've long since fallen behind the big 3 in quality of their models. There's no good reason at this point to keep burning money on Grok rather than making back some of that money renting out their Colossus data center.
Google own 5-6% of the shares of SpaceX. SpaceX is seeking a valuation of $1.77T which means Google's shares would be worth $88.5B-$106.2B. I'm not a skeptic of AI/LLMs but this makes me deeply suspicious of these circular deals. What happens when the music stops?
There are no dark GPUs. Compute translates directly to money for these frontier labs.
I think everyone is reading way too much into this. Sure there is some circular transactions that are sus, but this ain't it.
Let us pin this comment and see how it ages
It's very hard to know how much the deal actually increases SpaceX market cap, but unless Google exits their SpaceX position soon it doesn't even make much sense as a circular deal.
I am certain Anthropic spent less on building the next model this quarter if they make it to profitability due to the shear fact that they don't have enough compute.
Which solves the profitability problem with relative ease momentarily.
Also just to confirm, AI subscriptions are definitely being sold at a loss how big I don't know but these models are much harder to run.
API is definitely being sold at a decent profit.
So if you rate limit users and do usage billing + lower research costs which is a money pit temporarily.
(Proof is the fact that we don't have a new pre training run since 4.5 yet, they used to do one every 2 releases)
4.9 will probably be the same.
Next model Mythos doesn't seem to have a successor yet and was trained previous quarter most likely, they don't seem to have pre trained another one just improved Mythos if at all.
As much as I am into AI these attempts to show that there can be a profitable quarter seem like cooking the books, even if we assume no shady dealings otherwise.
Unless one of the Labs can say for certain training is going to stop they can't be profitable and I don't think training can stop because marginal gains is all they have.
8-12 months behind narrative for Chinese labs literally is going to kill the company that stops training first.
If we assume only a 3-6 month gap once China has more compute, then well then even if they keep training the lack of ability to arbitarily scale data centers in US, will kill them first.
DeepSeek V5 might actually just end the AI race for good.
Also given Mythos is atleast a 10x model compared to Opus, then it's pricing is likely going to be 10x as well so well token prices are likely never coming down, especially if these companies want to IPO.
I think there are accelerating returns: i.e. a models are still not good enough to be “drop in” remote workers, but once that threshold is passed, the value of each token of inference has a far higher multiplier.
This justifies the buildup. However not everyone agrees that model intelligence will continue scaling thus they assert that eventually the economics will hit a wall.
>Also given Mythos is atleast a 10x model compared to Opus, then it's pricing is likely going to be 10x as well so well token prices are likely never coming down, especially if these companies want to IPO.
I don't know why people say this when cost per unit of intelligence has been going down continuously over the past few years. When Opus 3 was first released, its API cost was $15.00 per million input tokens and $75.00 per million output tokens. Opus 4.8. which is significantly better, is $5.00 per 1 million input tokens and $25.00 per 1 million output tokens
In the case of Enron, people were obviously speculating in its stock, and that remains true regardless of why it collapsed later, or even whether it collapsed at all.
I say "first" because if you still can't agree that speculation in AI stocks even exists, then it's pointless to discuss what people might be doing to exploit or encourage it.
The fiat economic system is irreparably broken, and we are circling the drain. Another bailout is _probably_ inevitable. But the cycle sure as hell isnt resetting and we are speeding towards something... what it is is unclear though, and when is also unclear.
The part people cant wrap around is the scale of it and the time it takes to go through the super cycle. Theoretically, it all started with the Dot com bubble, which indirectly cause the housing bubble, which caused the GFC. Which caused whatever happened in 2019, which caused QE in 2022 under the guise of COVID, which is causing whatever the hell is happening now.
Capitalism has become uncorked, and money is irreversibly flowing to the top at an increasing rate. The logical next stage is that like 75% of the world's population is literally not even part of any economy. And that doesnt really make any sense
When COVID was ongoing there was a term floating around I liked, "Psychosis" was it. The spell is like that of, denial? Terror & shock?
Trauma might be better?
Looking at trauma responses and how to detect it in humans is an interesting perspective to look at all this with. Personally, if I look at it from "people are afraid, traumatized, defending themselves" and use that to extrapolate how most people (the masses, the non-rich) would act and also the rich - that points me to why theres such a sudden hastening of action and pace of wealth up towards the top in the name of AI & war.
See "M2SL" or "TOTBKCR" on tradingview if you want to see inflation live.
https://fred.stlouisfed.org/series/M2SL
https://fred.stlouisfed.org/series/TOTBKCR
And you would have been massively wrong. People have been complaining about quantitative easing since post GFC, and if you took the figures at face value, those would imply inflation was nearly 100% between the end of GFC and before the pandemic. Whatever you thought about the post-pandemic inflation, the period between GFC and pre-pandemic definitely did not see the level of inflation implied by those figures.
Just look at these charts: they were declining when inflation was raging on in 2022-23 …
"folk economics" implies it is by untrained people.
Milton Friedman's famous quote of "inflation is always and everywhere a monetary phenomenon" shows that he deeply believed the relationship between inflation and money supply, and one certainly cannot call Friedman a "folk economist" considering he won the Nobel prize in economics and was a professor at the University of Chicago.
Note: I am not saying he is right or supporting his belief. I am merely stating that such a belief is not a "folk economics" belief. This belief is still very prevalent in the freshwater schools of economics. [1]
As a personal anecdote, at Ronald Coase's 100th birthday party, I personally got Gary Becker and Richard Posner debating a very related topic (whether and by what degree the velocity of money of fluctuates and whether helicopter drops of cash would have been better during the early days of the money supply collapse in 2008/2009 than just giving money to the banks). In a room full of Nobel Prize winning economists in 2010, there was a very rigorous debate on the topic.
[1] https://en.wikipedia.org/wiki/Saltwater_and_freshwater_econo...
Maybe we've come to celebrate unethical behavior and its become so normalized that we forget to ask ourselves what should be allowed.
Government hands Wall Street another bailout to the tune of trillions of dollars. Wall Street executives and hedge funds use funds to enrich themselves as usual. Main Street and tax payer get fisted again. These massive data centers go bust. Get gutted during bankruptcy and foreclosure proceedings Public deals with the fallout with no help from government.
https://youtu.be/sL9hq7Qj1qc?t=252
shows why the boat is about to go down.
The sci-fi SpaceX S1 talks about asteroid mining and other imaginary chimeric stuff like space data centers... while 80 to 90 of the case is about AI. But their AI case is like BMW bragging about their thriving auto business...while renting all their car factories to Toyota.
If it looks like a bubble and waddles like a bubble and quacks like a bubble what is it?
This is precisely what makes the movie the Big Short interesting: we see that people did identify, within a reasonable time frame, when people would start defaulting and how that would cascade into a true crisis.
It's pretty clear that while the fruits of AI are quite useful, the entire thing is rife with very questionable financial engineering... but I still don't know what it is that makes all of this break. For example, it's obvious that the SpaceX IPO is a massive wealth transfer program, but it's not obvious that it will immediately end in a crash. Given how irrational the stock market has been, I don't see a reason it can't continue to be irrational for long after the bag has been handed over to the retail investors and retirement funds.
Nvidia is not losing anything if their stock falls.
So whats left? The typical candidates of course: We poor people. 401k, ETF, etc. we pay the bill.
Note that a pension plan that invests for you blindly is no better - either the returns are so bad that they are a scam, or they are investing in stocks anyway and so you get the same results but less control. Similar for things like social security, they are either worse options or you need to pump stocks.
A welfare state maybe?
We are not going to come up with a market-based solution to fix income inequality. The solution, as much as people in the dwindling middle class resist it, is a strong social safety net coupled with a hard reset on taxation and housing policies. Nobody should be homeless, nobody should be allowed to starve, but you might have to accept that your 401K goes down in exchange for a government guarantee of housing and food.
This is hard for people to accept because they currently have equity in their home or a 401K to save them from starving. But those are transient, individualistic solutions. You can lose your house. You can lose your 401K. Society should be taking care of each other in a broader way than letting everyone accumulate a little, private pile of money.
You mean hedge funds and private equity/private credit that all under perform S&P500?
The real suffering comes from whatever effect there is on the rest of the economy due to a recession, more layoffs, etc.
And some others might need to pull out when its down.
Money doesn't appear out of thin air.
Why would it lead to recession if a handful of big companies lose money they have?
It will show that the USA is in a recession for sure, but otherwise
Also, selling shares puts them in a better position to survive a downturn (more cash, less debt).
Whatever financial games they play in the background, doesn't matter when you make that much per 2 quarters alone.
Except they're not. Anthropic's claims of temporary profitability line up exactly with when SpaceX is giving them discounted compute, OpenAI's such a shitfest they threw the CFO off the glass cliff for daring to push back against the IPO. "Profitable on inference" is an unsubstantiated rumour.
Just look at the copilot changes. Demand switching to other providers immediately when prices rise, and there's not even certainty that the new copilot prices cover costs.
> They might not make back the money from training
This is an understatement. With all the datacenter buildout, they need trillions. For the investors get their money back and the bubble to not implode, they functionally need to unemploy everyone in the US.
If the AI dream is real, society just breaks.
More like $75/mo per user for the next 5-10 years if they can get 5% of the global population to pay that.
Home grow a bunch discount them federally, let them wipe the foreign markets.
If AI is threatened by china why would US NOT do the same? If they did they're in a much stronger position to do so than china. Cheaper energy, more cash, stronger industries.
Infrastrucure is thr kind of thing that only a foolish US admin would let fall apart to their advesary.
If they were, they'd never shut up about it. Yet they keep quiet about the financials.
The supply is currently constrained because 50+% of data center plans were cancelled as a result of the impossibility of the buildouts happening in a timely fashion, and subscriptions are charging a small fraction of the actual cost of inference, leading them to all bleed money, hence the rush to IPO to get one last infusion, since many of the past investors have publicly stated they aren’t putting any more money in until they see an ROI.
So is "unprofitable on inference".
Thankfully we should find out for real as soon as those S-1 documents arrive.
It will likely take a few years for supply to fully catch up, which means xAI will eat well for a while.
I can see a world where a few data centers come on line this year and reduce margins a bit, but it's crazy to think the margins will go to "cost of electricity plus a few percent" anytime soon.
[1] https://www.businessinsider.com/spacex-ipo-anthropic-paying-...
[2] https://www.nytimes.com/2025/03/11/technology/google-investm...
It's a fairly sweet deal for everyone involved. Anthropic/Google get to sell more tokens and xAI gets a war chest for another bite at the apple. I don't have much confidence that they'll do anything with it but that doesn't mean these deals don't make sense for them.
They're not and it's not clear why you seem to believe that. The immense capex for buildouts, training costs, etc. are not rolled into inference costs. Moreover, companies are already rapidly starting to re-evaluate token spend.
* LLMs are useful
* Company valuations around LLMs are not realistic
Both can be true, much like they were during the Dotcom bubble. The internet turned out to be a pretty real thing. A couple examples below might feel familiar in the next couple months/years.
> Blucora (then InfoSpace): Founded by Naveen Jain, at its peak its market cap was $31 billion and was the largest Internet business in the American Northwest. In March 2000, its stock price reached $1,305 per share, but by 2002 the price had declined to $2.
> Broadcast.com: A streaming media website that was acquired by Yahoo! for $5.9 billion in stock, making Mark Cuban and Todd Wagner multi-billionaires. The site is now defunct.
> eToys.com: An online toy retailer whose stock price hit a high of $84.35 per share in October 1999. In February 2001, it filed for bankruptcy with $247 million in debt. It was acquired by KB Toys, which later also filed for bankruptcy.
> GeoCities: Founded by David Bohnett, it was acquired by Yahoo! for $3.57 billion in January 1999[20] and was shut down in 2009.
> MicroStrategy: After rising from $7 to as high as $333 in a year, its shares lost $140, or 62%, on March 20, 2000, following the announcement of a financial restatement for the previous two years by founder Michael J. Saylor.
** Some scams transcend time **
Great link: https://en.wikipedia.org/wiki/List_of_companies_affected_by_...
There are also legitimate companies from the dotcom bubble era like amazon, microsoft, and intel. They all were vastly overpriced during the dotcom era. Probably also now lol.
Cisco was over 400 at one point and Nvidia is around 30. Not quite the same.
Other players today: - Digital Realty 48x - Equinix 75x - CoreWeave (still losing money)
There is likely a bubble of some type here, but I don't think this is the same as the Dotcom bubble.
It's not even subtle at this point, what with the attempt at S&P rules changes, the insane valuation, the attempt to change the trade-through rule, and more.
The problem is the valuations assume astronomical growth... that is likely impossible for all of them to simultaneously achieve. Which means something's got to give.
Circular deals aren't bad; what's potentially bad is if those deals are misinterpreted by active investores.
Great deal for Google but they end up basically just paying spacex to pay them back, right?
Circular investing is a thing that is happening with all of these companies related to language models. Google hoping for a ROI isn't a great example of that.
I've been wrong before. However, when was the last time this business model made sense -- that facebook, SpaceX and others, all just pivot from their market niche to general purpose AI datacenter providers.
How on Earth does this make sense?
What happens in a few years when DeepSeek runs on the chinese chips like the Huawei Ascend at a fraction of the cost ?
These are all very high value added companies going into comodity AI hosting and they're all going to make a killing?
US is a near monopoly of this pairing. A crash will result in the removal of the fluff and ocerpricing of it all but the stance is beyond strong.
Unless China outcompetes Nvidea AND TSMC AND magically gets 4x cheaper energy they are in a much weaker stance for the long haul.
Nvidia goes back to being a 100 billion dollar business and everyone else reaps the benefits of cheap tokens.
That's a problem for your kids to figure out ~ those currently getting enriched from these schemes.
Bubble bursts, somewhere between 2008 housing crisis and the dotcom bust.
Really dependent on if there are any OTHER structural problems to compound a fast re-valuation of tech stocks. There's plenty of noise about banks holding large amounts of bad private credit debt. There could be a lot or only a little collapse. There's so much uncertainty and the combination of war, high oil prices, and uncertainty about tarriffs that the market struggles to value anything as international fear drives investment into the US and high prices confusing whether growth is growth or just inflation.
Definitive peace in Iran combined with some sort of sobering AI news signaling the end to the infinite growth party could crush the markets.
This and auto loans. I have NO IDEA how people are affording $770 per month car payments _on top of_ $4.50+ per gallon gasoline.
Also the current president of US is Trump and they are in a war that is pumping the energy prices.
Why not bigger than dotcom burst?
Either way, as always, we'll do it the American Way: Privatize the profits, socialize the losses.
Eh. There's too much money. Covid response involved printing a lot of money and it all ended up somewhere. The chaos of the current administration has made everything considerably harder to price and the coincidental rise of the LLM has put us in strange situation that is legitimately difficult to price things correctly.
This is still only big enough to cause funny banking collapses not actual 2008 scale financial disasters. Banks hold a lot of bad debt, but it's isolated from consumer accounts. Might not want to hold equity in SoftBank though.
> There's so much uncertainty and the combination of war, high oil prices, and uncertainty about tarriffs that the market struggles to value anything as international fear drives investment into the US and high prices confusing whether growth is growth or just inflation.
The big concern lies in what the Trump admin will do. Things could end up merely a bad recession, like the Dotcom and Telecom bubble.
Or they can attempt to keep the bubble going once it collapses, crashing interest rates, and doom the US economy.
And who gets stuck with the bonds.
A financial crash that will make the 2007ff crisis look tame in comparison. That is why Anthropic, OpenAI and SpaceX (which xAI belongs to) are all going public soon and why NASDAQ bent the rules to include them... the current owners all want to raid pension savings worldwide [1] to get their payday before the bubble inevitably bursts.
And when it bursts, you can bet that the vultures will use their fresh cash to buy up assets at fire-sale prices. For the truly rich, a boom-bust cycle is only one thing, an opportunity to achieve extraordinary profit.
[1] https://news.ycombinator.com/item?id=48369391
The scenario I see is write-offs. At the moment there are hundreds of billions in IOUs being passed around, much more in liabilities than Lehman had back then in 2007. Compounding that is the frankly insane valuation - it's as clear as day that at least one of the major AI shops will go bust, they all run at a (huge) loss and sooner or later, one of them will run out of cash before achieving market dominance.
Unfortunately, OpenAI and Anthropic are valued at almost 1 trillion $ - backed by nothing but the hope on the winner surviving and achieving the classic VC-backed near-monopoly. The staff can be poached, they don't hold much in IP like patents, the servers and GPUs are mostly owned by third parties like AWS, Microsoft, Google or Oracle - once the cash runs out, they can't sell any assets for even some runway extension because there are no assets. Even the model weights and training data aren't worth much - all competitors already have training data sets of their own, it does not make sense to acquire further data, and model weights are being rendered obsolete by the constant churn of open-weight models particularly from China.
SpaceX is valued even higher, but unlike the other two candidates, they still at least got a viable business even if the entire AI BS bubble collapses, Starlink is a money printer and there's no alternative in sight that matches SpaceX and their reusable rockets.
Now, if either of the three even experiences a large drop in valuation for whatever reason, it's not just experienced VCs that can readily afford (and expect) investments to fail, but this time a lot of "everyday" investment vehicles (such as pension funds) will have to issue write-off losses, and now that they are publicly traded, that may also trigger stop-loss cascade orders further dropping prices, and retail investors will probably join in on the mass panic. That's the #1 risk IMHO.
The #2 risk is that after a collapse, the service providers (i.e. the ones owning the servers) will be sitting on a ton of hardware that has nowhere near recouped its cost. AWS, MS and Google can probably repurpose most of the hardware for their own use and rent out what remains, but they will have to eat significant accounting losses, provoking again a drop in their stock price, but this time with even more blast radius as all three of them are established stock index (and thus ETF) members that a looooot of people have exposure to. But someone like Oracle? They might actually get fried for good.
And the #3 risk is further downstream, particularly relating to NVDA. They have enjoyed years of insane profits because they are the only ones making high-performance AI chips. When demand for new chips collapses due to the event(s) I just described, they can easily shift their TSMC production slots back to GPU wafers and sell these to gamers - but at a far lower profit than before, which again can trigger stock price drops and write-offs.
I won't go further downstream - TSMC and their suppliers are IMHO pretty safe because there is just so much pent up demand from everything not AI, and the construction companies building datacenters don't have too much of a blast radius when the big guns stop expansion projects.
The concrete scenario I'm really, really afraid of: all three succeed with their IPOs, maybe they all survive a year and get included even in S&P 500. The existing shareholders and insiders all slowly dump a lot of their vested stock onto the public market, which in cleartext means into the dozens of billions of $ of retirement contributions. One day, the bubble bursts for whatever reason. The stock markets drop in a panic sell-off, either triggered by stop-loss orders or because retail investors are a herd of sheeple (just like in the 1st covid lockdown). Eventually, circuit breakers on the stock markets will trigger (just like they did in the GME post-apes collapse) and trading will pause, but it will resume until the markets have adjusted to the new valuation... and once the dust clears up, there will be a lot of blood on the floor. Possibly even riots, depending just how much retirement assets just got wiped out.
Yet when we learn of this new $26B in yearly revenue (2.2B/month from Google and Anthropic)the conversation does not return to that discussion. It transforms into:
"xAI's tech sucks"
"Google/SpaceX is Structurally Bad for the Economy"
etc
This is called motivated reasoning. We get new information and instead of the obvious thing, updating prior conclusions, we just find a different way to react negatively. The negative reaction will be achieved. The narrative here is completely polluted by people who dislike Elon/SpaceX.
It was definitely a smart business move. It should be troubling to any shareholder than xAI is unable to utilize this infrastructure as renting it out to competitors.
Hard disagree. It's polluted by Elon in general (pro and con), just like Tesla's idiotic valuation.
But in this case, a pivoted business model fundamentally changes the value proposition, and I'm not clear why "this space company making money on space things is now pretending to be a compute reseller and that's a good thing" is the narrative you think is preferable.
It's also beyond lame to essentially subtweet a "narrative" instead of responding to it directly. Who is "we", aside from a transparently dishonest way to pretend consensus exists?
They all have various strengths and weaknesses. My favorite is still ChatGPT, then Gemini/Claude, then Grok.
Grok often feels 1-2 generations behind the competition in general use, but it has three things that I love:
1. It seems to be the best at understanding current events. Maybe due to X integration, or some other tool call optimization in the backend? I don't know, but I often ask about things going on, and the other models have outdated info, give unhelpful answers, etc.
2. It is generally the least sycophantic for personal things. Anthropic is getting here too. ChatGPT and Gemini are working on this, but previous models in those families would almost never say anything negative about what I am doing. Sometimes I need career advice, personal advice, etc and I like the tone of how it responds. I think Claude will be caught up soon.
3. For professional work, there are certain topics that other models would refuse to engage with. At my last company we had an enormous amount of legal users. When a deposition would need a summary on certain topics, most models would refuse. Grok would not. I understand the need for safety and I don't blame the other model providers, but for some professional use cases you NEED a model that is capable of handling sensitive subjects.
As soon as we hand over searching out information to social media algorithms and LLM tools, we abandon our ability to see reality outside our direct vision.
Grok's ownership has already demonstrated capacity to influence major world elections and other events. You cannot trust it with this sort of information gathering and reporting.
Grok used to be really really bad ~8 months ago or so, but it's gotten better.
ChatGPT team needs to turn down the 'disagree just because' factor by a lot.
I guess the benchmarks disagree, but whenever I need to find specific information that does not easily show up with a web search, I try chatgpt, gemini and grok. Grok surfaces what I was looking for more often than the others.
Things like "find the github repo from 2017 that does $vague_thing".
Come on, the most logical thing is that Musk overestimated the compute he needs and got lucky with the secondary usage of it.
As soon as the IPO is done and if it didn't fail, he will buy curser and try to push again if he hasn't given up on it.
He also needs some compute for the robotics stuff and for Tesla in-car entertainment and for training FSD.
So they’re cutting edge in that way.
Having a positive set of beliefs annoys people and and can make them feel judged, but at least it provides a vector that points somewhere definite in possibility space.
Edit: from the footnotes: > Colossus actually runs largely on its own on-site gas turbines, which comes out even cheaper: at a simple-cycle heat rate of ~10,000 Btu/kWh and Henry Hub gas at ~$3.50/MMBtu, the fuel bill is only around $90mn a year.
OK, that's crazy. How can I get into renting GPUs to hyperscalers?
Makes sense. Very difficult to catch OpenAI and Anthropic now since their flywheel of generate revenue, use revenue to buy more compute, train a smarter model with more compute, made it hard to compete.
Being able to supply compute makes more sense for SpaceXAI if you can't compete in SOTA LLMs anymore.
If that ends up being viable and profitable, there is no realistic competition for decades. In this view, xAI earning a reputation as a reliable AI hyperscaler is just another tactic in that strategy.
if the bubble doesn't burst until then...
Moreover they're leasing compute - the actual infra around it is much less important - and how long does anyone expect heavily utilized GPUs to run? How likely is SpaceX to be able to re-lease this compute capacity? It will be broken down or out of date in 2-3 years.
This should be essentially ignored in the long term for SpaceX business prospects, and is low margin business that barely justifies a 10x earnings multiple let along a 100 revenue multiple for the xAI unit.