So I do think we're in a bubble, but I also remember when all the discussion around here was around Uber, and I read many, many hot takes about how they were vastly unprofitable, had no real business model, could never be profitable, and only existed because investors were pumping in money and as soon as they stopped, Uber would be dead. Well, it's now ten years later, Uber still exists, and last year they made $43.9bn in revenue and net income of $9.8bn.
This is underselling the Uber story to a degree. The original sell for Uber was that their total addressable market was the entire auto industry because people will start preferring taxis over driving. They are still trying to achieve that with similar stories now pushed to sell robotaxis.
Uber was undercutting traditional taxis either through driver incentive or cheaper pricing. Many hot takes were around the sustainability of this business model without VC money. In many places this turned out to be true. Driver incentives are way down and Uber pricing is way up.
That said, this is also conflating one company with an industry. Uber might have survived but how many ride sharing companies have survived in total? How many markets have Uber left because it couldn’t sustain?
In a bubble the destruction is often that some big companies get destroyed and others survive. For every pets.com there is one Amazon. That doesn’t mean Amazon is good example to say naysayers during the dot bubble were wrong.
I think Uber’s profitability has also been achieved by passing what would be debt to a traditional taxi company (the maintenance of the fleet of taxis) onto the drivers. I think many drivers aren’t making as much money as they think they are.
Did this change since Uber was created? Did Uber previously, back when people were making their "Uber is Doomed" comments pay to maintain drivers' cars? If not why bring it up?
This is a pattern where people have their pre-loaded criticisms of companies/systems and just dump them into any tangentially related discussion rather than engaging with the specific question at hand. It makes it impossible to have focused analytical discussions. Cached selves, but for everything.
But did their business model require them doing that forever? That seems like something they can cut back on once there is a healthy size of drivers in a market.
Yeah I agree it was the original plan from the beginning: use Saudi money to strangle competition and then get the prices back to taxi level (or higher). I believe they partly succeeded by making a compromise here: they both cut the payments to drivers and increased prices.
The original plan worked because in the switch-and-bait phase they were visibly cheaper so in the last year people's mental and speech model changed from "call me a taxi" to "call me an uber". But at least in my local market, the price difference between a taxi an and uber in 2025 is negligible.
What I think has never changed, is that most people do not understand depreciation on an asset like a car, or how use of that vehicle contributes to the depreciation. People see the cost of maintenance of a vehicle as something inevitable that they have almost no control over.
I think the point is about Uber's profitability and not necessarily about their business practices or ethics, and we should be careful not to conflate the two. It is absolutely valid to criticize the latter, but that (so far) seems mostly orthogonal to the former.
Now, it is totally possible that their behavior eventually create a backlash which then affects their business, but then that is still a different discussion from what was discussed before.
There is also a significant difference in insurance. Taxi companies usually have comprehensive insurance, hence the higher standards for drivers and vehicles (monitored and maintained) while Uber has a more differentiated model (part driver, part company, not monitored):
Oh dear, we are definitely in a bubble, it's just not in the way of total burst.
Back when everybody got into website building, Microsoft released a software called FrontPage, a WYSIWYG HTML editor that could help you build a website, and some of it's backend features too. With the software you can create a website completed with home, newspages and guestbooks, with ease, compare to writing "raw" code.
Now days however, almost all of us are still writing HTML and backend code manually. Why? I believe it's because the tool is too slow to fit in a quick-moving modern world. It takes Microsoft weeks of work just to come out with something that poorly mimics what was invented by an actual web dev in an afternoon.
Humans are adoptive, tools are not. Some times, tools can better humans in productivity, sometime it can't.
AI is still founding it's use cases. Maybe it's good at acting like a cheap, stupid and spying secretary for everyone, and maybe it can write some code for you, but if you ask it to "write me a YouTube", it just can't help you.
Problem is, real boss/user would demand "write me a YouTube" or "build a Fortnite" or "help me make some money". The fact that you have to write a detailed prompt and then debug it's output, is the exact reason why it's not productive. The reality that it can only help you writing code instead of building an actually usable product based on a simple sentence such as "the company has decided to move to online retail, you need to build a system to enable that" is a proof of LLM's shortcomings.
So, AI has limits, and people are finding out. After that, the bubble will shrink to fit it's actual value.
This is fair but it's also assuming that today's AI has reached its potential which frankly I don't think any of us know. There's a lot of investment being spent in compute and research from a lot of different players and we could definitely make some breakthroughs. I doubt many of us would've predicted even the progress we've had in the last few years before chatGPT came out.
I think the bubble will be defined on whether these investments pan out in the next two years or if we just have small incremental progress like gpt4 to gpt5, not what products are made with today's llm. It remains to be seen.
Well just look at the price of Uber and Lyft rides. I regularly had single-digit fares on both Uber and Lyft early on. Of course they were unprofitable then. Now that they have gained mindshare they have increased prices drastically.
Uber proposed $43.00 yesterday for a 23 minute drive from park slope to brooklyn heights in New York City, versus $2.90 for a 35 minute R train ride.
I am humbled by how myopic I was in 2010 cheering for a taxi-hailing smartphone app to create consumer surplus by ordering taxis by calling taxi companies.
It's been my experience (~ 4 years ago) that generally taxis were cheaper than Uber in new york, especially for anything like "Get me to the airport", sometimes like $25 cheaper.
In my experience its actually cheaper at least for airport rides. $50 flat through yellowcab app and no surge nor tip when ordered through app compared to $65 at best sometimes well over double during a bad surge.
Airport trips these days are often over $100 for me. What is crazy is yellowcab will take me to my area for $50 flat tip included through their app. We’ve exceeded even taxicabs by this point.
The story about Uber was that they were going to be unprofitable until they destroyed taxi services, then they were going to charge more than taxis and give less of a share to the driver.
Nobody is predicting that AI is going to do that. One thing I hadn't considered before is how much it was in google's interest to overestimate and market the impact of AI during their antitrust proceedings. For the conspiratorially minded (me), that's why the bottom is being allowed to drop out of the irrational exuberance over AI now, rather than a couple months ago.
it doesnt look likely that any particular ai service will have a moat. every time one of them does anything right now, theres a dozen competitors able to match it within months
Uber was unprofitable and when it ceased to be unprofitable ceased to be better.
They did managed to offload price on weaker actors party by simply ugnoring laws and hoping it will work for them. It did, but it was not exactly some grand inspiring victory and more of success of "some dont have to follow the law" corruption.
At the prices they were charging back then that was indeed the accurate take. Of course prices rose and a lot of middle and lower income riders were kicked to the curb in favor of those who can afford to blow another $60 per leg on a night out. I guess there turned out to be enough of them at scale.
The "hot takes" were that they were using investor money to illegally undercut the taxi industry until ride share had an oligopoly and that the government would stop them from breaking the law.
I don't know why law enforcement is considered a hot take here, but I have a few guesses.
I'm 52. I experienced the dot-com bubble very up close. I was in the Raleigh-Durham area for most of it. There were hundreds of startups all over the area. Companies like Nortel were booming. IBM was booming. By 2003 it was all gone--Nortel was a shell of its former self, IBM laid off huge numbers of workers. There was suddenly a glut of office space all over. We moved out in 2006, but even around then there was still a glut of office space! I don't know if it ever recovered because it was so overbuilt.
I remember having lunch with a guy who was stubbornly holding on to his Nortel stock, which was worth mere pennies by like 2005 or so. They not only lost their jobs, they lost their 401Ks which were all in company stock. Anyways, this guy was sure it was going to bounce back. I saw in like 2008 where Nortel finally closed its doors and the stock was de-listed at $0. His dream was dead. I never worked for equity after that time period.
The enormous build out of data centers reminds me of that time period. Yeah, it's all going to collapse.
> Plan for a future where you can buy GPUs for ten cents on the dollar, where there's a buyer's market for hiring skilled applied statisticians, and where there's a ton of extremely promising open source models that have barely been optimized and have vast potential for improvement
This doesn’t square entirely with the earlier claim that AI companies have (and will continue to have) “dogshit unit economics”.
If you have a bunch of cheap “applied statistician” labor (kind of a reductive take, btw), cheap GPUs, and powerful open source models, it is a near certainty that companies would achieve favorable unit economics by optimizing existing models to run much more efficiently on existing GPUs.
I happily pay $20/month for Google One to use Gemini 2.5 Pro. I don’t really need it to be a whole lot better. It’s a great product. If they can deliver inference of that level with positive margin (and keep it ad free), it’s a viable business.
Investors will likely lose billions, if not trillions, but I don’t think the industry is inherently unprofitable - I just don’t think anybody has been incentivized to optimize for cost yet. Why would you, when investors continue to throw money at you to scale?
The difference to the dot com bubble is that the unprofitable companies are privately held and the public companies are extremely profitable and have finally found something to soak up their ridiculous profits other than stock buybacks. How a crash affects anyone other than high-net-worth individuals with money tied up in VC funds is not explained.
The real question would be the debt on the GPUs. If a hyper scalar puts 100B from profits into data centers, and borrows 400B against the datacenters (or their suppliers do!). Then the buildout could be quite problematic.
If it’s just profits getting invested + some VC exuberance… I don’t actually know if it matters. If zuck simply shut off the money spigot and never spoke on ai again… would anything actually happen?
CoreWeave has taken on $11.2B in debt with interest rates ranging from 7% to 15%, paying $250M in interest on that debt last quarter on just $19 million in operating income. Half of their assets are GPUs, depreciating over six years.
> How a crash affects anyone other than high-net-worth individuals with money tied up in VC funds is not explained.
That is even worse. There are many so-called "AI companies" drowning in spending lots of tokens and the majority of them have lots of assumptions when going to raise more money to VCs.
What if the VCs say no?
What if 90% of all these startups get competition from a frontier AI lab and undercuts them? We are seeing this with Cursor and Anthropic already.
What if early-stage startups cannot afford the 100K per H-1B hire anymore AND cannot hire remote overseas due to the HIRE act?
Additionally, we are going to find out what does not mix well together with AI and will inevitably cause a crash that could come unexpectedly.
> Real estate and crypto on the other hand...
At least we do *know* that both of them do not mix well together.
I mean, sure we're in a bubble, but the trick is to call it, with that old Keynes quote about the market staying irrational longer than you can stay liquid.
But also:
> "So, you're saying a third of the stock market is tied up in seven AI companies that have no way to become profitable and that this is a bubble that's going to burst and take the whole economy with it?"
> I said, "Yes, that's right."
that is something different in this case isn't it? those seven companies making up a third of the market do not need to become profitable, they are insanely profitable. Mostly they invest a lot in AI but if that doesn't pay out, all but NVidia have their day job to go back to.
Is it that impractical that the GPUs would find another use case? Of NVidia cut enterprise gpu prices by 10x (which they absolutely could!) the gpu+memory combo would be cheaper than all other compute for database-like operations, simulations, and whatever ai is left.
Is gpu good for that? It seems like it is a very niche capability that can't easily be re-purposed the way regular cpu compute could be.
I did a lot of projects with Kafka (big data) in cloud environments and companies had big, pie in the sky dreams that came crashing back to reality when they got the bill for compute services. It's happened several times on projects I was on.
Older GPUs had nowhere near enough memory to be really interesting for big data crunching.
Now however, the biggest limit for AI workloads is GPU memory capacity (and bandwidth). The billions invested are going into improving this aspect faster than any other. Expect GPUs with a terabyte of ultra-fast memory by the end of the decade. There are lots… and lots… of applications for something like that, other than just LLMs!
> I mean, sure we're in a bubble, but the trick is to call it, with that old Keynes quote about the market staying irrational longer than you can stay liquid.
It might be worth it just to call it now. All you really have to do is get out of the S&P, you don't have to get out of everything.
For a relatively new 80-day-old account, I thought you'd have much fresher material for jokes.
It's the year 2025 and we've had 9 ample months of seeing more second-term policies, tariff-tax-by-schizo-tweet, the steepest decline in the dollar in decades, etc. etc.
You want to see real delusion? Look for someone still trying to brush off critiques of this administration as just "being fashionable."
> Plan for a future where you can buy GPUs for ten cents on the dollar, where there's a buyer's market for hiring skilled applied statisticians, and where there's a ton of extremely promising open source models that have barely been optimized and have vast potential for improvement.
This actually sounds like a kinda cool outcome as long as you aren’t an applied statistician.
>AI is the asbestos we are shoveling into the walls of our society and our descendants will be digging it out for generations
Seems a bit pessimistic. AGI may not be here next year to keep the bubble going but will probably happen in the next decade or two and do much of the stuff advertised. It's like the dotcom bubble - much of commerce, banking and the like did move to the internet but not till a while after the financial bubble burst.
What percent of consumption will go to ai ? For me probably atleast 10%. What percent of investment will go to ai ? For me another 10% probably. I mean some of it will come from less consumption and investment in other things.
Something of a logical leap here: if LLMs aren't capable of replacing workers and it's all lies, then what company is going to engage in mass layoffs without seeing results first? Sounds like companies that deserve to go away.
Yes. A lot of these people should have been laid off anyway. The Musk Twitter massacre taught everybody a lesson, and layoffs were hot before AI was even the main concern.
Also, the DEI massacre is probably going to develop (or has developed) into a full scale HR/Social PR massacre. Instead of getting yelled at for doing the wrong thing, better to do nothing but make more money. And a side-benefit is that firing all of those people makes it even easier to fire more people. (Is that the singularity?)
I don't doubt that some industries are going to be nearly wiped out by AI, but they're going to be the ones that make sense. LLMs are basically super-google translate, and translators and maybe even language teachers are in deep trouble. In-betweeners and special effects people might be in even more trouble than they already were. Probably a lot more stuff that we can't even foresee yet. But for people doing actual thinking work, they're just a tool that feeds back to you what you already know in different words. Super useful to help you think but it isn't thinking for you, it's a moron.
> for people doing actual thinking work, they're just a tool that feeds back to you what you already know in different words. Super useful to help you think but it isn't thinking for you, it's a moron.
Beautiful description of AI. It’s the tech equivalent of the placebo effect. It does truly work for some, until you look closely and it’s actually a bunch of hot air.
> The Musk Twitter massacre taught everybody a lesson
Well, depends on which lesson. "The company can still run" or "we actually won't build anything new for years".
Twitter released a couple things that were being worked on before the acquisition, and then nothing else (grok comes from a different company which later was merged into it, but obviously had different employees).
Yeah exactly. The question should always be - are these layoffs incremental because of AI? If not, then they should not count in this kind of analysis.
> The Musk Twitter massacre taught everybody a lesson
That companies can be kept on KTLO mode with only a skeleton crew?
I think everybody knew that already. The hot takes that Twitter was going to disappear were always silly, probably from people butthurt that a service they liked was being fundamentally changed.
> If LLMs aren't capable of replacing workers and it's all lies, then what company is going to engage in mass layoffs without seeing results first?
We see companies layoff workers for all sorts of short-sighted reasons. They'll mass layoff to reduce labor costs for short term profits and stock price increases, so the execs and shareholders can cash out. AI is just the current reason the executive class has decided to use for the layoffs they were going to do regardless.
Further: business and management are exceptionally fad-driven, for numerous information-theoretic reasons.
Performance is difficult to measure and slow to materialise. At the same time, everyone, especially senior leadership and managers, is desperately competitive, even where that competition is on the perception rather than reality of performance. There's a very strong follow-the-herd / follow-the-leader(s) mentality, often itself driven by core investors and creditors.
A consequence is a tremendous amount of cargo-culting, in the sense of aping the manifest symbols of successful (or at least investor-favoured) firms and organisations, even where those policies and strategies end up incurring long-term harms.
Then there's the apparent winner-take-all aspect of AI, which if true would result in tremendous economic power, if not necessarily financial gains, to a very small number of incumbents. Look at the earlier fallout of the railroad, oil, automobile, and electronics industries for similar cases.
(I've found over the years various lists of companies which were either acquired or went belly-up in earlier booms, they're instructive.)
NB: you'll find fad-prone fields anywhere a similar information-theoretic environment exists: fashion, arts, academics, government, fine food, wine collecting, off the top of my head. Oh, and for some reason: software development.
There were chicken littles during the run up to 2008, too. Actually, I think most were a little bit premature. I take articles like these as an early sell signal.
I think both are kind of inevitable with bubbles like the dotcom, 2008 and the present one.
You get a positive feedback loop where the industry hypes their thing which causes the pubic to buy in which causes stocks to go up and the industry to hype more and the public to buy more. Then people point out prices are too high and capital misallocated but that doesn't stop the feedback loop so it goes on longer.
It has to stop at some point though, often because the buyers run out of money to buy with.
Then it goes into reverse - falling prices put off buyers, the industry doesn't get new cash flow to pay for its commitments to GPUs/office leases/mortgages, some of them go bust which puts off buyers even more. Then eventually, after around three years it level out.
I'm a believer in the internet, housing and AI but during the bubbles you get money misallocated on stuff like pets.com or maybe OpenAI spending zillions on data centers to provide free idle chat to the public. Money on fundamental AI research is probably good but all those data centers... dunno.
I was just thinking about this. Exposure from a short is theoretically limitless. Some sort of derivative would be a better approach? Asking for a financially clueless friend.
The financially illiterate don't understand that "going short" is not the simple reverse of "going long" and that there are more difficulties involved with borrowing stocks to short or in buying puts. Well, puts are easy to buy, at least, but the manner in which they decay makes it hard to win with that strategy, harder, in fact, than buying calls to go long. But yes, you can technically buy puts. You can also play Powerball.
There is still a demand for these tools. I know they are useful to me. Do they make me more productive as a software engineer? Probably not, at least not significantly. But they're still useful, especially for little tools and one-off scripts which are not intended to become production code anywhere.
I also just enjoy using them for bouncing ideas off of them and doing sanity checks on all sorts of topics, personal and work-related. Sometimes they spark a better idea that I may not have had otherwise. I will still be using them after the bubble bursts.
That being said, I'm also fine if all the current AI companies implode and I'm just running an OSS model locally.
That’s still not good enough. Being a mildly good idea assistant doesn’t come close to paying for the investment spent and valuations of these companies. It’s all bet on completely changing everything. And if that doesn’t happen soon, the valuations are going to crash bad.
And since the entire US economy is being propped up by AI investing, it’s going to be a disaster.
Yeah. For example I use chatgpt to refine my thoughts and dig deeper into ideas (to get my brain thinking by interacting with a machine with knowledge). But is this worthy of all the investment done? Absolutely not. Would I pay for this service? Nah. Personally I am incredibly sensitive to changes in price - I wouldnt pay a penny and thus my demand would disappear.
Im sure there are others who find more value from it, however, I dont think that group of people is enough to get OAI to be free cash flow to the firm positive any time soon. Note this is not accounting profit - FCFF takes into account reinvestment, and is the cash profits left after.
The problem with this is, what you are using it for is not commensurate to what has been invested. In other words, to date, the investment has not been productive for society and doesnt seem to be on track to deliver what has been promised.
The whole thing was lost on the mag 7 being unprofitable and that he was so sick of talking about AI he decided to take his shot at making money writing a book about AI.
> but an AI salesman can 100% convince your boss to fire you and replace you with an AI that can't do your job, and when the bubble bursts, the money-hemorrhaging "foundation models" will be shut off and we'll lose the AI that can't do your job, and you will be long gone, retrained or retired or "discouraged" and out of the labor market, and no one will do your job.
Even if the big AI companies turn off their APIs, people will still be able to run local models as well as some other, new business spun up to run them as SaaS.
Isn't the training most of the cost? In which case the current models could have a very long lifetime even if new models are never trained again. They'll go gradually out of date, but for many purposes will still be useful. If they can pull new info from the web they may stay relevant for decades. It's only if running the chatbots is not cost effective that everything halts and my understanding is that the cost of that is lower relatively. Even now, older models are still being used. Also, performance optimizations seem likely to soon reduce the need for data center build out and reduce costs. Seems too soon to say where this is all going. Who even knows if the GPU chips will improve dramatically or if something else (more AI optimized processor architectures) will replace them? It's true that right now it looks like a bubble, but the future is still very much in flux, and the value of the models already created may not disappear overnight.
As a corporate finance and valuation geek, Ill warn you now: dont try and time mood and momentum. Thats what is driving much of the valuations being thrown around.
If this blows up big time and it is found that the Big Tech firms were operating on lies and false hope, there will be consequences - in the form of shareholders demanding cash returned and setting limits on the cash balance held by Google et al. Apple has stayed smart staying out of this nonsense and not doing M&A.
Investing in projects with negative NPV destroys the wealth of shareholders.
We don’t know how sticky that revenue is, or if it’s going to be a commodity in the long run. Similar things used to happen in ad-tech before investors got wise that there was no moat.
Revenues mean nothing without positive equity earnings, especially so without a viable path to get there. Without a clear path, how do you justify the valuation? Lol.
Uber and Amazon had a very logical path to get there.
The reinvestment is so high that once you tack that onto the earnings youre in a fat negative. What does that mean? You will eat into the cash balance and eventually have to go raise more.
> No what's driving much of the valuations is the biggest leap in human technology since the internet and skyrocketing revenues as a result
That is a 1999-like bubble and how you get 75 - 90% of these companies crashing when the music stops.
> Private companies soaring to $100m ARR in 12 months is commonplace now. That's what's driving the valuation.
We don't even know if that is even real to begin with. Even if it is, that revenue can be lost as quickly as it is gained.
This happened to Hopin and other companies who grew extremely quickly and then their valuations crashed.
The questions you should be asking yourself is even after looking at the competition, what is the retention and the switching cost of these said "$100m ARR in 12 months" companies if a competitor moves into their core business?
I largely agree. I don't think AI is ultimately useless, but I think it's about 10% as useful as the broader market seems to think it is. That said, every time I see another article like this, I think to myself "well it's not going to come crashing down any time soon". This is the nature of bubbles - they only collapse when nearly everyone is finally convinced they never will. Right now, stories about the AI bubble collapsing are everywhere, which means the time hasn't come yet.
I have an idea that the market may actually start to react positively to bad job numbers, as that could be taken as a signal that companies are shedding people to replace them with AI (even if that's not the actual reason for the bad numbers). If job numbers started suddenly improving and the unemployment rate dropping, it could be taken to mean that AI is not going to replace everyone after all.
> they only collapse when nearly everyone is finally convinced they never will
I get that rationale in some bubbles as that means people are not parking their money as cash where they can buy the dip and support the market (tell me if I'm widely off). But I think this case is different because there's actually VAST sums of money being spent in AI by some very big players who will need an return.
I disagree with Doctorow's conversation with a student at Cornell. You can prevent further misallocation of funds by agitating against "AI" usage in general. If you are at Cornell, organize meetings, protests etc. against the dehumanization and decreased job prospects.
As a student, you have much more freedom to protest than as an employee, and that is where the resistance must come from.
We also need to take into account that while there is a bubble, most of the insane amounts of investment that were seen in headlines have not materialized.
Nvidia will crash, Tesla will crash (Optimus robot nonsense) but Microsoft and Google should be fine. If there is a bailout, protest again. preferably in the physical space and focusing on economic topics rather than culture wars (which is what the politicians want you to focus on).
So I do think we're in a bubble, but I also remember when all the discussion around here was around Uber, and I read many, many hot takes about how they were vastly unprofitable, had no real business model, could never be profitable, and only existed because investors were pumping in money and as soon as they stopped, Uber would be dead. Well, it's now ten years later, Uber still exists, and last year they made $43.9bn in revenue and net income of $9.8bn.
This is underselling the Uber story to a degree. The original sell for Uber was that their total addressable market was the entire auto industry because people will start preferring taxis over driving. They are still trying to achieve that with similar stories now pushed to sell robotaxis.
Uber was undercutting traditional taxis either through driver incentive or cheaper pricing. Many hot takes were around the sustainability of this business model without VC money. In many places this turned out to be true. Driver incentives are way down and Uber pricing is way up.
That said, this is also conflating one company with an industry. Uber might have survived but how many ride sharing companies have survived in total? How many markets have Uber left because it couldn’t sustain?
In a bubble the destruction is often that some big companies get destroyed and others survive. For every pets.com there is one Amazon. That doesn’t mean Amazon is good example to say naysayers during the dot bubble were wrong.
I think Uber’s profitability has also been achieved by passing what would be debt to a traditional taxi company (the maintenance of the fleet of taxis) onto the drivers. I think many drivers aren’t making as much money as they think they are.
Did this change since Uber was created? Did Uber previously, back when people were making their "Uber is Doomed" comments pay to maintain drivers' cars? If not why bring it up?
This is a pattern where people have their pre-loaded criticisms of companies/systems and just dump them into any tangentially related discussion rather than engaging with the specific question at hand. It makes it impossible to have focused analytical discussions. Cached selves, but for everything.
Yes, Uber paid drivers more in the beginning, and even facilitated car loans for them lol
But did their business model require them doing that forever? That seems like something they can cut back on once there is a healthy size of drivers in a market.
Yeah I agree it was the original plan from the beginning: use Saudi money to strangle competition and then get the prices back to taxi level (or higher). I believe they partly succeeded by making a compromise here: they both cut the payments to drivers and increased prices.
The original plan worked because in the switch-and-bait phase they were visibly cheaper so in the last year people's mental and speech model changed from "call me a taxi" to "call me an uber". But at least in my local market, the price difference between a taxi an and uber in 2025 is negligible.
What I think has never changed, is that most people do not understand depreciation on an asset like a car, or how use of that vehicle contributes to the depreciation. People see the cost of maintenance of a vehicle as something inevitable that they have almost no control over.
Yes, Uber was paying drivers more and that is how they were able to have good service.
Awesome, Uber is profitable by creating a society damaging business model which is copied by other companies.
Phew, I'm so sad I was a Uber critic from early on...
I think the point is about Uber's profitability and not necessarily about their business practices or ethics, and we should be careful not to conflate the two. It is absolutely valid to criticize the latter, but that (so far) seems mostly orthogonal to the former.
Now, it is totally possible that their behavior eventually create a backlash which then affects their business, but then that is still a different discussion from what was discussed before.
There is also a significant difference in insurance. Taxi companies usually have comprehensive insurance, hence the higher standards for drivers and vehicles (monitored and maintained) while Uber has a more differentiated model (part driver, part company, not monitored):
https://jjlegal.com/blog/rideshare-vs-taxis-understanding-ac...
Oh dear, we are definitely in a bubble, it's just not in the way of total burst.
Back when everybody got into website building, Microsoft released a software called FrontPage, a WYSIWYG HTML editor that could help you build a website, and some of it's backend features too. With the software you can create a website completed with home, newspages and guestbooks, with ease, compare to writing "raw" code.
Now days however, almost all of us are still writing HTML and backend code manually. Why? I believe it's because the tool is too slow to fit in a quick-moving modern world. It takes Microsoft weeks of work just to come out with something that poorly mimics what was invented by an actual web dev in an afternoon.
Humans are adoptive, tools are not. Some times, tools can better humans in productivity, sometime it can't.
AI is still founding it's use cases. Maybe it's good at acting like a cheap, stupid and spying secretary for everyone, and maybe it can write some code for you, but if you ask it to "write me a YouTube", it just can't help you.
Problem is, real boss/user would demand "write me a YouTube" or "build a Fortnite" or "help me make some money". The fact that you have to write a detailed prompt and then debug it's output, is the exact reason why it's not productive. The reality that it can only help you writing code instead of building an actually usable product based on a simple sentence such as "the company has decided to move to online retail, you need to build a system to enable that" is a proof of LLM's shortcomings.
So, AI has limits, and people are finding out. After that, the bubble will shrink to fit it's actual value.
This is fair but it's also assuming that today's AI has reached its potential which frankly I don't think any of us know. There's a lot of investment being spent in compute and research from a lot of different players and we could definitely make some breakthroughs. I doubt many of us would've predicted even the progress we've had in the last few years before chatGPT came out.
I think the bubble will be defined on whether these investments pan out in the next two years or if we just have small incremental progress like gpt4 to gpt5, not what products are made with today's llm. It remains to be seen.
Well just look at the price of Uber and Lyft rides. I regularly had single-digit fares on both Uber and Lyft early on. Of course they were unprofitable then. Now that they have gained mindshare they have increased prices drastically.
Uber proposed $43.00 yesterday for a 23 minute drive from park slope to brooklyn heights in New York City, versus $2.90 for a 35 minute R train ride.
I am humbled by how myopic I was in 2010 cheering for a taxi-hailing smartphone app to create consumer surplus by ordering taxis by calling taxi companies.
Uber charged me $85 (plus tip!) for a 35 min ride from the airport. Yeah, my fond memories of those nascent rideshare apps are long gone...
Yellow cab is still more expensive and the cars are dirtier. I wonder why they don't try to compete on price at least with Uber.
It's been my experience (~ 4 years ago) that generally taxis were cheaper than Uber in new york, especially for anything like "Get me to the airport", sometimes like $25 cheaper.
In my experience its actually cheaper at least for airport rides. $50 flat through yellowcab app and no surge nor tip when ordered through app compared to $65 at best sometimes well over double during a bad surge.
Airport trips these days are often over $100 for me. What is crazy is yellowcab will take me to my area for $50 flat tip included through their app. We’ve exceeded even taxicabs by this point.
>versus $2.90 for a 35 minute R train ride.
Comparing the two makes as much sense as comparing how a $500k rolls royce and a $1k shitbox both get you from point A to point B.
That’s not exactly world changing money.
They found the niche and market to operate in and are running with it until the next thing “creatively destroys” their business model.
That’s a far cry from the multi-trillion dollar hype bubble surrounding AI.
It's a 200 billion dollar company, roughly what Anthropic is raising at
The story about Uber was that they were going to be unprofitable until they destroyed taxi services, then they were going to charge more than taxis and give less of a share to the driver.
Nobody is predicting that AI is going to do that. One thing I hadn't considered before is how much it was in google's interest to overestimate and market the impact of AI during their antitrust proceedings. For the conspiratorially minded (me), that's why the bottom is being allowed to drop out of the irrational exuberance over AI now, rather than a couple months ago.
> Nobody is predicting that AI is going to do that.
... Now that I hear it out loud, I can't help thinking if maybe it's something we should be thinking about.
Subsidization to destroy competitors followed by lock-in is obvious, but is there any way these systems could turn professionals into serfs?
it doesnt look likely that any particular ai service will have a moat. every time one of them does anything right now, theres a dozen competitors able to match it within months
I mean, hey, maybe they _will_ increase all those 10x programmer's bills to 20k per month. At least that would be funny.
Uber was unprofitable and when it ceased to be unprofitable ceased to be better.
They did managed to offload price on weaker actors party by simply ugnoring laws and hoping it will work for them. It did, but it was not exactly some grand inspiring victory and more of success of "some dont have to follow the law" corruption.
At the prices they were charging back then that was indeed the accurate take. Of course prices rose and a lot of middle and lower income riders were kicked to the curb in favor of those who can afford to blow another $60 per leg on a night out. I guess there turned out to be enough of them at scale.
The "hot takes" were that they were using investor money to illegally undercut the taxi industry until ride share had an oligopoly and that the government would stop them from breaking the law. I don't know why law enforcement is considered a hot take here, but I have a few guesses.
I'm 52. I experienced the dot-com bubble very up close. I was in the Raleigh-Durham area for most of it. There were hundreds of startups all over the area. Companies like Nortel were booming. IBM was booming. By 2003 it was all gone--Nortel was a shell of its former self, IBM laid off huge numbers of workers. There was suddenly a glut of office space all over. We moved out in 2006, but even around then there was still a glut of office space! I don't know if it ever recovered because it was so overbuilt.
I remember having lunch with a guy who was stubbornly holding on to his Nortel stock, which was worth mere pennies by like 2005 or so. They not only lost their jobs, they lost their 401Ks which were all in company stock. Anyways, this guy was sure it was going to bounce back. I saw in like 2008 where Nortel finally closed its doors and the stock was de-listed at $0. His dream was dead. I never worked for equity after that time period.
The enormous build out of data centers reminds me of that time period. Yeah, it's all going to collapse.
> Plan for a future where you can buy GPUs for ten cents on the dollar, where there's a buyer's market for hiring skilled applied statisticians, and where there's a ton of extremely promising open source models that have barely been optimized and have vast potential for improvement
This doesn’t square entirely with the earlier claim that AI companies have (and will continue to have) “dogshit unit economics”.
If you have a bunch of cheap “applied statistician” labor (kind of a reductive take, btw), cheap GPUs, and powerful open source models, it is a near certainty that companies would achieve favorable unit economics by optimizing existing models to run much more efficiently on existing GPUs.
I happily pay $20/month for Google One to use Gemini 2.5 Pro. I don’t really need it to be a whole lot better. It’s a great product. If they can deliver inference of that level with positive margin (and keep it ad free), it’s a viable business.
Investors will likely lose billions, if not trillions, but I don’t think the industry is inherently unprofitable - I just don’t think anybody has been incentivized to optimize for cost yet. Why would you, when investors continue to throw money at you to scale?
> If they can deliver inference of that level with positive margin (and keep it ad free), it’s a viable business.
That “if” is doing tons of heavy lifting here.
The difference to the dot com bubble is that the unprofitable companies are privately held and the public companies are extremely profitable and have finally found something to soak up their ridiculous profits other than stock buybacks. How a crash affects anyone other than high-net-worth individuals with money tied up in VC funds is not explained.
Real estate and crypto on the other hand...
The real question would be the debt on the GPUs. If a hyper scalar puts 100B from profits into data centers, and borrows 400B against the datacenters (or their suppliers do!). Then the buildout could be quite problematic.
If it’s just profits getting invested + some VC exuberance… I don’t actually know if it matters. If zuck simply shut off the money spigot and never spoke on ai again… would anything actually happen?
Only oracle has taken on debt so far, among the hyper scalers.
CoreWeave has taken on $11.2B in debt with interest rates ranging from 7% to 15%, paying $250M in interest on that debt last quarter on just $19 million in operating income. Half of their assets are GPUs, depreciating over six years.
(per Bloomberg)
> How a crash affects anyone other than high-net-worth individuals with money tied up in VC funds is not explained.
That is even worse. There are many so-called "AI companies" drowning in spending lots of tokens and the majority of them have lots of assumptions when going to raise more money to VCs.
What if the VCs say no?
What if 90% of all these startups get competition from a frontier AI lab and undercuts them? We are seeing this with Cursor and Anthropic already.
What if early-stage startups cannot afford the 100K per H-1B hire anymore AND cannot hire remote overseas due to the HIRE act?
Additionally, we are going to find out what does not mix well together with AI and will inevitably cause a crash that could come unexpectedly.
> Real estate and crypto on the other hand...
At least we do *know* that both of them do not mix well together.
AI + layoffs + mortgages on the other hand...
Still think a middle of the road outcome is most likely here. General purpose technology that changes society but falls well short of agi hype.
As for money side - think it’ll come. There is obvious utility (but not autonomy) and the economics of it will find their equilibrium. They always do
I mean, sure we're in a bubble, but the trick is to call it, with that old Keynes quote about the market staying irrational longer than you can stay liquid.
But also: > "So, you're saying a third of the stock market is tied up in seven AI companies that have no way to become profitable and that this is a bubble that's going to burst and take the whole economy with it?"
> I said, "Yes, that's right."
that is something different in this case isn't it? those seven companies making up a third of the market do not need to become profitable, they are insanely profitable. Mostly they invest a lot in AI but if that doesn't pay out, all but NVidia have their day job to go back to.
Is it that impractical that the GPUs would find another use case? Of NVidia cut enterprise gpu prices by 10x (which they absolutely could!) the gpu+memory combo would be cheaper than all other compute for database-like operations, simulations, and whatever ai is left.
Is gpu good for that? It seems like it is a very niche capability that can't easily be re-purposed the way regular cpu compute could be.
I did a lot of projects with Kafka (big data) in cloud environments and companies had big, pie in the sky dreams that came crashing back to reality when they got the bill for compute services. It's happened several times on projects I was on.
Older GPUs had nowhere near enough memory to be really interesting for big data crunching.
Now however, the biggest limit for AI workloads is GPU memory capacity (and bandwidth). The billions invested are going into improving this aspect faster than any other. Expect GPUs with a terabyte of ultra-fast memory by the end of the decade. There are lots… and lots… of applications for something like that, other than just LLMs!
What’s OpenAI’s and anthropic’s day job?
Which of the seven OP referred to are OpenAI or Anthropic?
> I mean, sure we're in a bubble, but the trick is to call it, with that old Keynes quote about the market staying irrational longer than you can stay liquid.
It might be worth it just to call it now. All you really have to do is get out of the S&P, you don't have to get out of everything.
It can run for another year or two. Long time to sit on the sidelines with your cash inflating away.
This is the crux of bubbles - timing and where do you move assets so they have protection.
The things I'm trying to keep in mind, because hard to suppress the instinct to be reactive:
1. "Time in market beats timing the market."
2. When diversifying, your profession is is already part of your portfolio.
There's also the political mismanagement of the United States, but that's a whole 'nother can of worms.
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For a relatively new 80-day-old account, I thought you'd have much fresher material for jokes.
It's the year 2025 and we've had 9 ample months of seeing more second-term policies, tariff-tax-by-schizo-tweet, the steepest decline in the dollar in decades, etc. etc.
You want to see real delusion? Look for someone still trying to brush off critiques of this administration as just "being fashionable."
> Plan for a future where you can buy GPUs for ten cents on the dollar, where there's a buyer's market for hiring skilled applied statisticians, and where there's a ton of extremely promising open source models that have barely been optimized and have vast potential for improvement.
This actually sounds like a kinda cool outcome as long as you aren’t an applied statistician.
>AI is the asbestos we are shoveling into the walls of our society and our descendants will be digging it out for generations
Seems a bit pessimistic. AGI may not be here next year to keep the bubble going but will probably happen in the next decade or two and do much of the stuff advertised. It's like the dotcom bubble - much of commerce, banking and the like did move to the internet but not till a while after the financial bubble burst.
What percent of consumption will go to ai ? For me probably atleast 10%. What percent of investment will go to ai ? For me another 10% probably. I mean some of it will come from less consumption and investment in other things.
Something of a logical leap here: if LLMs aren't capable of replacing workers and it's all lies, then what company is going to engage in mass layoffs without seeing results first? Sounds like companies that deserve to go away.
LLMs are just a stock price preserving excuse to do layoffs from previous overhiring.
Yes. A lot of these people should have been laid off anyway. The Musk Twitter massacre taught everybody a lesson, and layoffs were hot before AI was even the main concern.
Also, the DEI massacre is probably going to develop (or has developed) into a full scale HR/Social PR massacre. Instead of getting yelled at for doing the wrong thing, better to do nothing but make more money. And a side-benefit is that firing all of those people makes it even easier to fire more people. (Is that the singularity?)
I don't doubt that some industries are going to be nearly wiped out by AI, but they're going to be the ones that make sense. LLMs are basically super-google translate, and translators and maybe even language teachers are in deep trouble. In-betweeners and special effects people might be in even more trouble than they already were. Probably a lot more stuff that we can't even foresee yet. But for people doing actual thinking work, they're just a tool that feeds back to you what you already know in different words. Super useful to help you think but it isn't thinking for you, it's a moron.
> for people doing actual thinking work, they're just a tool that feeds back to you what you already know in different words. Super useful to help you think but it isn't thinking for you, it's a moron.
Beautiful description of AI. It’s the tech equivalent of the placebo effect. It does truly work for some, until you look closely and it’s actually a bunch of hot air.
Is a placebo worth a trillion dollars?
> The Musk Twitter massacre taught everybody a lesson
Well, depends on which lesson. "The company can still run" or "we actually won't build anything new for years".
Twitter released a couple things that were being worked on before the acquisition, and then nothing else (grok comes from a different company which later was merged into it, but obviously had different employees).
Yeah exactly. The question should always be - are these layoffs incremental because of AI? If not, then they should not count in this kind of analysis.
> The Musk Twitter massacre taught everybody a lesson
That companies can be kept on KTLO mode with only a skeleton crew?
I think everybody knew that already. The hot takes that Twitter was going to disappear were always silly, probably from people butthurt that a service they liked was being fundamentally changed.
> If LLMs aren't capable of replacing workers and it's all lies, then what company is going to engage in mass layoffs without seeing results first?
We see companies layoff workers for all sorts of short-sighted reasons. They'll mass layoff to reduce labor costs for short term profits and stock price increases, so the execs and shareholders can cash out. AI is just the current reason the executive class has decided to use for the layoffs they were going to do regardless.
Further: business and management are exceptionally fad-driven, for numerous information-theoretic reasons.
Performance is difficult to measure and slow to materialise. At the same time, everyone, especially senior leadership and managers, is desperately competitive, even where that competition is on the perception rather than reality of performance. There's a very strong follow-the-herd / follow-the-leader(s) mentality, often itself driven by core investors and creditors.
A consequence is a tremendous amount of cargo-culting, in the sense of aping the manifest symbols of successful (or at least investor-favoured) firms and organisations, even where those policies and strategies end up incurring long-term harms.
Then there's the apparent winner-take-all aspect of AI, which if true would result in tremendous economic power, if not necessarily financial gains, to a very small number of incumbents. Look at the earlier fallout of the railroad, oil, automobile, and electronics industries for similar cases.
(I've found over the years various lists of companies which were either acquired or went belly-up in earlier booms, they're instructive.)
NB: you'll find fad-prone fields anywhere a similar information-theoretic environment exists: fashion, arts, academics, government, fine food, wine collecting, off the top of my head. Oh, and for some reason: software development.
Yep, those are the companies that would go away.
There is on the other hand a strong correlation between the sky is falling and the sky not actually falling.
It makes one tempted to take the sky is falling as a buy signal.
There were chicken littles during the run up to 2008, too. Actually, I think most were a little bit premature. I take articles like these as an early sell signal.
I think both are kind of inevitable with bubbles like the dotcom, 2008 and the present one.
You get a positive feedback loop where the industry hypes their thing which causes the pubic to buy in which causes stocks to go up and the industry to hype more and the public to buy more. Then people point out prices are too high and capital misallocated but that doesn't stop the feedback loop so it goes on longer.
It has to stop at some point though, often because the buyers run out of money to buy with.
Then it goes into reverse - falling prices put off buyers, the industry doesn't get new cash flow to pay for its commitments to GPUs/office leases/mortgages, some of them go bust which puts off buyers even more. Then eventually, after around three years it level out.
I'm a believer in the internet, housing and AI but during the bubbles you get money misallocated on stuff like pets.com or maybe OpenAI spending zillions on data centers to provide free idle chat to the public. Money on fundamental AI research is probably good but all those data centers... dunno.
There’s a quote from Gil Luria (Managing Director and Analyst at D.A. Davidson) I love on this bubble, which I hope becomes part of the zeitgeist:
> No of course there isn't enough capital for all of this. Having said that, there is enough capital to do this for a at least a little while longer.
https://www.wheresyoured.at/openai-onetrillion/
What can we do? Short those companies.
Something something irrational something something solvent.
I was just thinking about this. Exposure from a short is theoretically limitless. Some sort of derivative would be a better approach? Asking for a financially clueless friend.
All I have to say is good luck out competing the big firms!
Buy puts
The financially illiterate don't understand that "going short" is not the simple reverse of "going long" and that there are more difficulties involved with borrowing stocks to short or in buying puts. Well, puts are easy to buy, at least, but the manner in which they decay makes it hard to win with that strategy, harder, in fact, than buying calls to go long. But yes, you can technically buy puts. You can also play Powerball.
If you buy a put option, you can’t lose more than you put in. The problem is still one of timing things right.
Check out /r/wallstreetbets for expert advice on this. /s
There is still a demand for these tools. I know they are useful to me. Do they make me more productive as a software engineer? Probably not, at least not significantly. But they're still useful, especially for little tools and one-off scripts which are not intended to become production code anywhere.
I also just enjoy using them for bouncing ideas off of them and doing sanity checks on all sorts of topics, personal and work-related. Sometimes they spark a better idea that I may not have had otherwise. I will still be using them after the bubble bursts.
That being said, I'm also fine if all the current AI companies implode and I'm just running an OSS model locally.
That’s still not good enough. Being a mildly good idea assistant doesn’t come close to paying for the investment spent and valuations of these companies. It’s all bet on completely changing everything. And if that doesn’t happen soon, the valuations are going to crash bad.
And since the entire US economy is being propped up by AI investing, it’s going to be a disaster.
Automating "little tools and one-off scripts" doesn't pay for $40bn of extra data centers (and that's just one provider), though.
Yeah. For example I use chatgpt to refine my thoughts and dig deeper into ideas (to get my brain thinking by interacting with a machine with knowledge). But is this worthy of all the investment done? Absolutely not. Would I pay for this service? Nah. Personally I am incredibly sensitive to changes in price - I wouldnt pay a penny and thus my demand would disappear.
Im sure there are others who find more value from it, however, I dont think that group of people is enough to get OAI to be free cash flow to the firm positive any time soon. Note this is not accounting profit - FCFF takes into account reinvestment, and is the cash profits left after.
The problem with this is, what you are using it for is not commensurate to what has been invested. In other words, to date, the investment has not been productive for society and doesnt seem to be on track to deliver what has been promised.
The whole thing was lost on the mag 7 being unprofitable and that he was so sick of talking about AI he decided to take his shot at making money writing a book about AI.
So many AI hucksters these days
A good sign that an article is another pointless, naive AI doomerism piece is that they cite that atrocious MIT 95% "study".
A good sign someone is an AI huckster is they ignore the rest of the article and citations.
Plenty of hucksters around and for them I say three words: show me the money (free cashflows).
Um, that's four words.
Not saying you're wrong, though...
> but an AI salesman can 100% convince your boss to fire you and replace you with an AI that can't do your job, and when the bubble bursts, the money-hemorrhaging "foundation models" will be shut off and we'll lose the AI that can't do your job, and you will be long gone, retrained or retired or "discouraged" and out of the labor market, and no one will do your job.
Even if the big AI companies turn off their APIs, people will still be able to run local models as well as some other, new business spun up to run them as SaaS.
Isn't the training most of the cost? In which case the current models could have a very long lifetime even if new models are never trained again. They'll go gradually out of date, but for many purposes will still be useful. If they can pull new info from the web they may stay relevant for decades. It's only if running the chatbots is not cost effective that everything halts and my understanding is that the cost of that is lower relatively. Even now, older models are still being used. Also, performance optimizations seem likely to soon reduce the need for data center build out and reduce costs. Seems too soon to say where this is all going. Who even knows if the GPU chips will improve dramatically or if something else (more AI optimized processor architectures) will replace them? It's true that right now it looks like a bubble, but the future is still very much in flux, and the value of the models already created may not disappear overnight.
Its a matter of time until the implosion happens.
As a corporate finance and valuation geek, Ill warn you now: dont try and time mood and momentum. Thats what is driving much of the valuations being thrown around.
If this blows up big time and it is found that the Big Tech firms were operating on lies and false hope, there will be consequences - in the form of shareholders demanding cash returned and setting limits on the cash balance held by Google et al. Apple has stayed smart staying out of this nonsense and not doing M&A.
Investing in projects with negative NPV destroys the wealth of shareholders.
No what's driving much of the valuations is the biggest leap in human technology since the internet and skyrocketing revenues as a result
Private companies soaring to $100m ARR in 12 months is commonplace now. That's what's driving the valuation.
We don’t know how sticky that revenue is, or if it’s going to be a commodity in the long run. Similar things used to happen in ad-tech before investors got wise that there was no moat.
Revenues mean nothing without positive equity earnings, especially so without a viable path to get there. Without a clear path, how do you justify the valuation? Lol.
Uber and Amazon had a very logical path to get there.
The reinvestment is so high that once you tack that onto the earnings youre in a fat negative. What does that mean? You will eat into the cash balance and eventually have to go raise more.
> No what's driving much of the valuations is the biggest leap in human technology since the internet and skyrocketing revenues as a result
That is a 1999-like bubble and how you get 75 - 90% of these companies crashing when the music stops.
> Private companies soaring to $100m ARR in 12 months is commonplace now. That's what's driving the valuation.
We don't even know if that is even real to begin with. Even if it is, that revenue can be lost as quickly as it is gained.
This happened to Hopin and other companies who grew extremely quickly and then their valuations crashed.
The questions you should be asking yourself is even after looking at the competition, what is the retention and the switching cost of these said "$100m ARR in 12 months" companies if a competitor moves into their core business?
It always amuses me when people who actually know things get downvoted on here simply because their perspectives are unpopular.
Peoppe who actually know things have better things to so than post here.
I largely agree. I don't think AI is ultimately useless, but I think it's about 10% as useful as the broader market seems to think it is. That said, every time I see another article like this, I think to myself "well it's not going to come crashing down any time soon". This is the nature of bubbles - they only collapse when nearly everyone is finally convinced they never will. Right now, stories about the AI bubble collapsing are everywhere, which means the time hasn't come yet.
I have an idea that the market may actually start to react positively to bad job numbers, as that could be taken as a signal that companies are shedding people to replace them with AI (even if that's not the actual reason for the bad numbers). If job numbers started suddenly improving and the unemployment rate dropping, it could be taken to mean that AI is not going to replace everyone after all.
> they only collapse when nearly everyone is finally convinced they never will
I get that rationale in some bubbles as that means people are not parking their money as cash where they can buy the dip and support the market (tell me if I'm widely off). But I think this case is different because there's actually VAST sums of money being spent in AI by some very big players who will need an return.
I disagree with Doctorow's conversation with a student at Cornell. You can prevent further misallocation of funds by agitating against "AI" usage in general. If you are at Cornell, organize meetings, protests etc. against the dehumanization and decreased job prospects.
As a student, you have much more freedom to protest than as an employee, and that is where the resistance must come from.
We also need to take into account that while there is a bubble, most of the insane amounts of investment that were seen in headlines have not materialized.
Nvidia will crash, Tesla will crash (Optimus robot nonsense) but Microsoft and Google should be fine. If there is a bailout, protest again. preferably in the physical space and focusing on economic topics rather than culture wars (which is what the politicians want you to focus on).