Boom, bubble, bust, boom. Why should AI be different?
crazystupidtech.com
crazystupidtech.com
Webvan → Instacart, DoorDash, Amazon Fresh
Kozmo.com → Postmates, Uber Eats, Gopuff
Boo.com (fashion) → Farfetch, Net-a-Porter, ASOS
Broadcast.com → YouTube, Netflix, Twitch
The dot-com bubble didn’t prove the internet was a fad — it proved the internet was inevitable, but the valuations assumed adoption would happen in 2 years instead of 15–20. To me it feels like the AI inevitability will be much quicker.
AI is accelerating "let them eat cake" at rates never seen before in history, so I imagine the violence will follow soon after
There is also a customer adoption curve of technology that lags far behind the technologist adoption curve. For example video on the Web failed a long time, until it didn't, when Youtube began to succeed. The problem became "boring" to technologists in some ways, but consumers gradually caught up.
> All this means two things to us: 1)The AI revolution will indeed be one of the biggest technology shifts in history. It will spark a generation of innovations that we can’t yet even imagine. 2) It’s going to take way longer to see those changes than we think it’s going to take right now.
Based on what? We're only seeing linear improvements for increasing spending. There's no new algorithm ideas on the horizon, just more and more hardware, in the hopes that if we throw enough RAM and CPU at the problem, it will suddenly become "AGI."
No one has their eye on power budgets or sustainability or durability of the system. The human brain has such a high degree of energy efficiency that I don't think people understand the realities of competing with it digitally.
The main problem "AI" seems to solve is that humans get bored with certain tasks. The language models obviously don't, but they do hallucinate, and checking for hallucinations is an exceedingly boring task. It's a coffin corner of bad ideas.
Internet did not have enough devices to reach people. At the height of 2002 only a fraction of people worldwide had an already expensive computer and an internet to go with it.
I ran a e-commerce startup from 2005-2010. Having access to demand is a thing.
Today everyone has access in their pockets. Go to small city in Africa, India and China, and observe how they use AI. See how perplexity has put AI answers in hundreds of millions of people's hands before Google in a matter of months.
Forgive me for saying — but "Based on what" for comparing accelerated adoption between 2005 and 2025 — is discarding many huge elephants in the room, starting with that small thing you're reading this in your hand with, and the invisible thing that's sending you this comment.
The LLM algorithms seem pretty clunky to me, like a hack designed for text translation that surprised everyone by getting quite smart. The reason the human brain is so much more energy efficient is quite likely better design/algorithms. I was watching some video comparing brain and LLM function and almost tempted to try building something myself (https://youtu.be/3SUqBUGlyh8). I'm sure there are many more competent people looking at similar things.
I'm not too bullish on architectural gains. There are efficiencies to be had, but far closer to "+5% a year" than "+5000% in a single breakthrough".
You can try to build a novel AI architecture, at a small scale. Just be ready. This field will kick your teeth in. ML doesn't like grand ideas and isn't kind to high aspirations.
AI researchers came up with an architectural improvement that made a lot of previously impossible stuff barely possible. Then, industry ran with it. Scaling that particular trick to the limits by throwing as much raw compute and data at it as humanly possible.
You don't need to be an AI expert to know that there are probably more advances to be had and that funding foundational research is the way to get them.
It's not certain if something like JEPA would ever reach production grade AI models.
This has changed since the cost of equipment and infrastructure has been close to "free" for the large corporations running a cycle of funny-money investment in a bubble. This has allowed them sell access to the computing and models for just above operational energy costs (to the extent of increasing global energy prices), whilst offering free accounts to harvest data. No small competitor could possibly compete with that model.
The calculation for profitability (useful output for humans in a cost-benefit analysis) of the current setup is broken, and trades on our dreams of the future. Scaling computing forever simply does not work. It will never be profitable without further leaps forward in the technology--either more efficient models or hardware. By this time, the extent to the excessive investment in new data-centers will be clear.
The internet is a medium, an interconnection of autonomous computer networks
A "web" of hyperlinked HTML pages is one use of an internet
However this internet is more than a handful of popular websites incorporated as companies
Perhaps that's why it was called the "dot-com" bubble and not the "internet" bubble
You see that same pattern with AI now. Products are being provided for free or nearly free, and plenty is being spent on marketing.
That the key to success is developing a brand and user base faster than the next person can.
And that’s where AI makes things so hard. Creating a protective moat.
The minute Amazon stops being good about refunds or a cheaper delivery app comes out than DoorDash I’m gone. No loyalty.
And both of those are on the verge as they focus on profits over customer experience.
Honestly anyone who thinks AI has intrinsic value to rival the GDP of nations is a bagholder in denial and I'll be happy to buy your puts.
AI if it gets better will be thinking / intellectual work which is a different category.
I remember in the 90s people would say the internet will bring instant conveyance of media including video and people were like yeah right I can just about get one page of crappy text in a minute over the unreliable dial up modem. It's like that now with AI thinking.
The value of modern AI seems very high. That nobody knows how high, that they still haven't figured out applications, and that the technology and its tools are still far from refined, is normal for any new technology.
If you add the value of the potential political power gained by controlling AI, then the value to the owners and investors is astronomical. Many of the investors have demonstrated a strong motivation to sacrifice money for political power, for example by supporting nationalism that undermines a global economy that they benefit enormously from. Somewhere, I read someone explaining their investment by saying 'it's the greatest transfer of power in (modern) history'. Also see: https://news.ycombinator.com/item?id=45983700
A couple of years down the road, their useful applications still are summarizing text, transferring style to text, generating code under strict supervision, and generating images that need retouching.
That’s a lot to get out of a tool, but it’s dubious that investors were pouring trillions of dollars into these things thinking of automating away junior software engineers and low end design work.
Edit: I forgot their other niche, that of generating homework and school test answers
And it's really still very arguable imo if it's even doing this
Like you said, it still needs strict supervision. In my opinion it is not a good use of your supervisory time to be babysitting an LLM versus mentoring actual juniors
Right. Because at least juniors are supposed to learn and at some point become senior and stop needing this kind of supervision. Also, interacting with people can be more rewarding (or not, depending on the people)…
Search is dead or dying
Social media is dead or dying
Content creation is dead or dying
If they cant make AI work, then they are left with AI at a level that continues to devalue their core business.
They have no choice. They made a deal with the devil. And the devil means to collect.
This is why I think Apple is lucky their attempt failed so bad. They dodged a bullet. They have an opportunity to guide a lost tech industry through a post AI bubble world.
The massive planetary investment is not to make more AI chats that summarize text. That's just short sighted.
I think most smart people are looking seriously at different models to try and improve the accuracy of any existing ML uses they had in their business but the new features built post-ChatGPT tend to often just be fancied up chats.
That's happening of course, but that's not really the whole picture. Any org that already invests in R&D is likely considering or already implementing modern AI tech into their existing infrastructure. A big oil or pharmaceutical or materials company likely doesn't care much about chat bots, or any customer-facing tech for that matter.
Hopefully we can retain a lot of this value when the bubble bursts but I just haven't seen any really good success stories of converting these models into businesses. If you try and build as a middleman where you leverage a model to solve someone's problem they can always just go to the model runner and get the same results for cheaper - and the model runners seem (so far - this may change) to be unable to price model usage at a level that actually makes it sustainable.
Those older models running specialized tasks seem to be trucking along just fine for now - but I remain concerned that when the bubble bursts it's going to starve these necessary investments of capital.
I think it's pretty clear to all the big operators that they will need to go whole hog into ads and take some of the Google/Meta pie. It's just a matter of time.
It seems like that at first glance. But in reality, GPUs have had extremely slow adoption for real-world operational meteorology applications. Because of the fundamental design and architecture of most NWP systems, it was very difficult to leverage GPUs as compute accelerators; most efforts barely eked out any performance gains once you account for host/device memory transfers. It really wasn't until some groups started to design new weather modeling systems from the ground up that they could architect things in such a way that GPUs made a significant difference.
Obviously AI / ML weather modeling is a different story.
Yup. It's to make already rich people richer.
So I would fairly limit my experience to consumer and medium-sized business uses - I have no experience with large corporate translation efforts (the largest would probably be Ubisoft or the Mouse-Ears company's gaming divisions if you consider them large) and even the small mobile game company I worked at had a budget in the millions range. It certainly hasn't been a focus of my career but I feel comfortable standing by my statement above.
Not to mention hundreds of other sectors which will benefit from better international communication.
Tourism and travel is one of the worlds largest industries, and companies in that sector can improve their revenue with double digits if they can reach and communicate with more customers. That's real impact, which is worth something, while hacker votes are worth nothing.
Except… can you capture it? A junior dev is… not exactly someone you want connecting to your business-critical database without supervision, and a real human dev will get better with a predictable rate. Will LLMs get better? The makers are betting on that, but we'll only know after the model releases, and even then after we play with them for a bit to differentiate between the record performance on whichever benchmark and the actual work we want them to do.
Then there's the question of can you really keep an edge for 20 years with investments today: Sometime between 2030-2035, there's likely to be models matching 2025-SOTA performance that run on ${year}'s high-end smartphone.
(Well, unless we all die in WW3 because of Russia getting desperate from its failure to remove Ukraine's sovereignty, or because China has a hot war with Taiwan and/or the USA messing with global consumer electronics supplies, but I don't think those get priced into the market…).
that's like 5% of NVIDIA's current market cap. sounds like peanuts when you lay it out like that
But that's just the USA's software developers in just their first year after graduating. Software devs are 1% of the US job market, the first year after graduation is (66-21=45 years, 1/45 ~= 2%) of a working life, the US is just 4% of the world's population/25% GDP.
For the 1% to matter, there have to be other jobs that LLMs can do as well as a fresh graduate. I don't know, are LLMs like someone the first year out of law school or medical school, or are those schools better than software? Certainly the home robotics' AI are nowhere near ready yet, no plumber, no driver (despite the news about new car AIs), would you trust an Optimus to cut your hair? etc.
For the 2% to matter, depends how seriously you take the projections of improvements. Myself, I do not. Looks like exponential improvements come at exponential costs, and you run out of money to spend for further improvements very quickly.
For the 4% to matter, depends on how fast other economies grow. 4% by population, about 25% by GDP. I believe China is still growing quite fast, likely to continue. Them getting +160% growth, and thus getting 2.6x times the money available to burn on AI tokens, over the next 20 years would be unsurprising.
All in all, I don't think the USA is competent enough at large-scale projects to handle the infrastructure that this kind of AI would need, so I think it's a bubble and will burst before 2030 because of that. China seems to be able to pull off this kind of infrastructure, so may pull ahead after the US does whatever it does.
Before looking to medical and law schools, I might look to middle-manager school or salesperson school or bookkeeper school.
I don’t know enough to speculate even beyond those crude guesses, but as I thought about this question, I found it interesting to skim the US’ employment-by-detailed-occupation chart:
In my experience, the answer is a resounding no. They’ll nickel and dime some kind of per-seat licensing on a monthly basis that costs less than 100 USD or whatever. So for every 100$ in salary you can automate away, you might get 2$ in subscription payments if you are lucky, at current rates.
There’s probably a good business usecase there for companies wanting to have smoother communication with offshore teams.
Could that be a game-changer? I wouldn’t discount it, but it does sound like something that has to operate at a very low margin and that doesn’t merit a lot more investment.
So, back of the envelope math, the US GDP is 27.72T USD, 80% (22.18) corresponds to the tertiary sector.
Let’s say that this is a 15% increase over a 10 years period, because YoY a boom like the computer revolution itself looks like 2% increases a year.[1]. This amounts to about 1.5% increases each year.
Let’s just make the huge leap that you can just scale the productivity up of all this just by making typing out reports and emails a faster activity, and summarizing information for which you’re not facing liability if the bot gets it wrong.
Yes, including the nurses, cleaners, truckers, teamsters, all of it.
1.5% of it is a cool 330 billion.
How much of a cut of that productivity increase could AI companies take? 30%? That’s 100 billion in one year there.
So with pie-in-the-sky math, they could break even if their obligations throughout the decade don’t amount to 1 trillion (since those 1.5T in bonds issued this year mature in longer periods)
1. https://www.bls.gov/opub/mlr/2021/article/the-us-productivit...
Promise by who? I think the bet is that it would lay off nearly everyone white collar and let AI take its place.
Finding the valuable application is often the hardest part. That it hasn't happened yet is meaningless. Some technologies sit on the shelf for decades.
AI seems to have a lot of potential: It may be the most valuable technology ever; it may not provide more value than it does now, or something in between. Nobody actually knows. The challenge of innovation is managing that irreduceable risk. It starts by accepting risk, accepting that you don't know. One wrong way is to deny the risk - denying uncertainty - by either saying it's worthless or that success is guaranteed.
Very useful, clearly. But valuable? In aggregate it seems clear that it is. But where does that value acrue? It seems to me the value will be thinly spread while the costs are concentrated.
It does not seem possible that any conceivable business can pay for all the announced plans for developing data centres, nor energy available to power them.
If AI systems can be developed to be trust worthy enough to act on their own, none so far (?), then I can see where the value could acrue, but as things stand?
Won't the value will be concentrated in the few with the scale to build competitive AIs?
In a sense, costs are spread thinly across the content creators whose work has been stolen. (But of course, it is indeed incredibly concentrated in building datacenters.)
The law is an ass.
Current IP laws are too restrictive, but scraping public facing websites is not theft even under those crazy laws
I have no moral objection to the use of Anna's Archive to train models. A good use, if illegal. But I do recogise and condemn the hypocrisy of Meta doing it. Not surprising, just disgusting
The wasting of bandwidth is annoying, so silly. We should be better organized
Calling it theft is buying into the mad bad and sad IP legal thinking that has become the dominant paradigm in the West
As a simplistic hypothesis: The already-powerful and super-wealthy taking all that IP from the small content creators is theft, IMHO. The small content creators who can't afford JSTOR finding some free source for a paper, etc. is democratic, empowering, and enriches our society.
No.
Open AI and their ilk can sell tokens, but how much business is there in that? Trillions? If not, they're bankrupt.
Dead man walking. Zombie
The open and free models are very capable and getting better.
If there is a breakthrough beyond transformers and neural nets that means trustworthy AI that can be agentic (does not exist, the "trustworthy" part) then it will be exponentially more valuable. But that was as likely in 2020 as in 2030.
Meanwhile something like 10% of the USA electricity supply is being "committed" to datacenters and no practical plans to supply it
Meanwhile the Chinese are leaping ahead and in a more community orientated open way. The cognitive dissonance is quite loud for that one!
We are pricing in the hollywood version of AI we don't have as if it is the internet.
I communicated with people exactly like what I am doing right now in this post on usenet in 1995. Message boards by 1997. The internet bubble wasn't based on some wild virtual reality version of the internet that hadn't been invented yet.
It is a categorically different process at work here. This bubble is far more insane and speculative since we don't have what we are pricing in. We don't even really know what we are pricing in besides some vague notation of an inevitable "AGI".
The internet was amazingly valuable, but many of the early companies failed. Investing in internet companies was hardly a sure bet.
How that washes out on net we'll have to see. I'm not gonna pretend I know more than anyone else. Just keep in mind that a major difference between now and 2000 is companies stay private a lot longer. An IPO forces you to open the books and sustain public scrutiny of the broad investor class. A still-private startup only needs to convince one funder of their value. That inevitably leads to higher variance and a greater risk of failure. That doesn't mean the whole sector is necessarily a bubble, but if it is, it can be sustained a lot longer without us knowing. A small number of people with $50 billion they need to park somewhere and no other obvious options can keep shitty ideas afloat in a way that wouldn't be possible if they had to be subjected to broader exposure. We like to believe people with $50 billion can't be wrong, but the wisdom of crowds always beats the wisdom of individual genius.
Heck, AI itself taught us that same lesson!
That might be true, but it also might be true that it's tremendously valuable. The conditions you identify exist for every new technology; obviously the outcomes vary greatly.
The same could be said for the internet. But, and I know this will be hard for younger readers to believe, I seem to recall the value proposition of the Internet being more immediately apparent at the time.
Proprietary, walled garden services, with their own dial-up numbers, such as AOL and CompuServe, were seen as the future. Microsoft thought their similar service (MSN?) was the way forward and didn't integrate the Internet into Windows 95. That was after Netscape's browser was released and (relative to the time, I'm sure) very popular.
That’s part of the difference with AI now: the internet immediately generated significant value almost instantly for relatively modest investments, so there were a ton of small and mid-sized companies who saw almost immediate profits from moving catalog sales or support online, switching software distribution from mailing diskettes to downloads, etc. and some people were able to cut into established markets where the existing companies were slow to change.
AI is different in two key ways: the first is the extremely high cost, which prevents a lot of the bottom-up growth we saw on the web, but the second is that it’s not a reliable technology like the web was so you can’t safely use it in the most valuable contexts. In the 90s, some people screwed up form validation badly but most people didn’t. Right now, companies would love to replace things like customer service or sales with chatbots but nobody on the market can make a system which is both safe and useful because things like prompt injection require theoretical breakdowns, not just attention to detail.
All I can say is, that was the opposite of what I've heard. Did you participate?
Also, Google was many years after Netscape's IPO, seen as the first SV boom. And what about Windows 95, if the Internet's ROI was so obvious?
In Google's case, the key thing was that they were out-competing in what was already an established market. Search companies were making money from ads and sales referrals, so the questions were things like marketshare and efficiency rather than the ability to make revenue at all, whereas Netscape struggled with that once Microsoft used their Windows monopoly to set the price for browsers at $0. They tried to sell server software but that was a different market with limited synergy for browsers and there was a ton of competition even if they'd been better at writing software.
I mention all of that because one thing to remember is that the dotcoms weren't the only game in town. A lot of people focused on them because the IPOs and market valuations were wild by traditional standards but most of the real money and energy was in established businesses moving online since there were clear and immediate benefits from doing so. When the bubble popped, that stuff didn't really change and a ton of people moved from dotcom jobs to traditional companies.
I worked for a web development company at the time and we were turning away business for years because there were so many companies looking to add a web presence to their existing business. It made quite an interesting contrast to our startup clients who tended to be a lot more focused on stock prices rather than business fundamentals. I remember being on a call with pets.com people who were basically openly stating that they were basically frittering time away waiting for the IPO to make them rich, whereas our customers who were in manufacturing, banking, insurance, etc. were a lot more realistic about working within a budget to do something they would actually turn a profit from.
Re: Windows 95, the web drove a lot of its success. That was around the time normal people could see a lot of immediate personal benefit from being online–shopping, recipes, stock trading, research, forums, games, dating, porn—and Win95 was the first version of Windows to ship with built-in TCP/IP and a web browser, not to mention being a lot closer to the competition on usability. For a lot of PC users, especially in business, the web was what sold them on the need to pay more to have a GUI, mouse, etc. and while that was possible with Windows 3.1 it really went mainstream around the time Windows 95 came out (Windows NT was too demanding on hardware for most budgets outside of engineering/development).
> completely missing the distinction between the dotcoms which were losing money on every sale with no way to close the gap and Amazon, which was expanding rapidly but was profitable in each business segment within a couple years (e.g. books were cash-positive circa 1995) and could go from reporting losses to profits any time they wanted simply by slowing their expansion plans.
Great insight. And of course Amazon would raise any funds possible to expand into this new frontier.
> Win95 was the first version of Windows to ship with built-in TCP/IP and a web browser, not to mention being a lot closer to the competition on usability.
Per Wikipedia:
"Windows 95 originally shipped without Internet Explorer, and the default network installation did not include TCP/IP .... At the release date of Windows 95, Internet Explorer 1.0 was available,[48] but only in the Plus! add-on pack for Windows 95, which was a separate product. ...
Windows 95 OEM Service Release 1 was the first release of Windows to include Internet Explorer (version 2.0) with the OS."
My point is not to nitpick, but that the Internet's value wasn't obvious to Microsoft at that point.
Not really. I mean, not only. The value of the web is immense. And yet, the dot-com bubble was indeed a bubble. What matters is the value in the short term compared to the value of the companies in the current context. Even if AI is huge 20 years from now, it can still crash dramatically tomorrow.
the real answer is that the applications for the military, surveillance, and population control are proven, and the pathways to scale those capacities are clear, so the money will pour in no matter what. the implication is that we had better come up with some more consumer/humanity friendly applications that create comparable value, or that is all we will get.
Homes as assets should pass on, higher cost services of today would be replaced by lower cost which only temporarily would increase units sold(but should eventually plateau because #units/person is not going to change). No component of the GDP will move.
If the fertility rate of developed economies is less than 2.1 then there should be wealth and asset accumulation among the younger people over time. The demand for newer goods and services from the people who get richer is inelastic: most goods and service's prices dont matter to the rich they buy them any ways, and it continues to keep becoming more inelastic.
So within like a several years the demand should just collapse as wealth accumulates a lot and people work less and become more price insensitive. Immigration is set to remain low to developed nations for the next 3-5 years.
This seems to be quite evident in Japan and EU already(though in the EU if you adjust the productivity for work hours the GDP becomes same as America's).
So why do people assume developed countries would even buy this much more new stuff. 1.5 trillion$ worth of new things over the next 5 years?
You have a hundred people, they have a GDP of N. Tomorrow, their productivity doubles because of a technological innovation. Your GDP is 2N.
Prices matter extensively to the rich and poor. The cost of a given compute capacity has gone from "literally the entire United States can't afford it" to "my lightbulb has this much compute because it's cheaper than choosing a dumber processor".
What happens tomorrow if eg ChatGPT 5.1 performance becomes doable for $500 of tech? $50? Swap this for grain harvesting, waste bin collection, etc if you don't like the LLM case.
The bubble would burst and the US economy would face a recession?
So now that value is just shifted into the companies that were going to purchase from openai.
It would just hurt the investors who have exposure to openai/anthropic/google/microsoft.
Much of the value of this AI boom is not from the direct model companies but its from companies which use their technology.
Although the government could be stupid and bail out these companies which WOULD hurt all us citizens and the inflation caused by money printing due to that could cause a recession.
* It would stop datacenter- and other related infrastructure construction, making huge investments effectively worthless for companies like Oracle and Amazon, and of course hurt the construction sector.
* It would hurt the companies you mention, plus a many more including NVidia, likely in ways that would lead to large-scale layoffs.
* It would seriously hurt corporate and VC investors and likely make them much less interested in large investments for quite some time, thus affecting other sectors as well.
* It would seriously hurt index funds and pension funds.
A number of years down the line, if LLMs are indeed capable of significantly boosting productivity, I'm sure we'd see a recovery, but when large bubbles suddenly burst there's usually some pretty serious fallout.
Sure, the average person has no interest in self hosting, but businesses will at least run the numbers.
Think about the unsatisfied needs and desires most people have. In extremely low income areas, it may be a roof over your head or knowing where your next meal comes from. Moving up a tier, it might be the ability to send your children to education or better clothing. In wealthier areas it might be things like a better car or higher quality food even though you're not in danger of going hungry. For the extremely wealthy it might be more leisure time, art, and new experiences.
When GDP increases, broadly, those are the areas you see expand. Looking at life today in a baseline American household, the things which are mass produced are far more available and affordable than they were a century ago - in the 1930s households spent about 10-12% of their income on clothing.
Sadly, the rate of improvement for non-mass-produced items like college tuition, medical care, and especially housing has ballooned compared to median income, so life doesn't feel inexpensive, certainly, but GDP has a lot of room to grow in a lot of areas.
Total GDP can keep rising so long as technologist can improve efficiency through robotics, inventions and scientific breakthroughs.
GDP just describes peoples amount of activity. People will always build bigger buildings or monuments (see egypt pyramids, dubai skyscrapers, cambodia angkor wat). These are actaully not inelastic as megaprojects will quickly hit real limits regardless of the amount of capital. (I can always add 10 more floors to the tallest skyscraper, or 10 feet to the longest wall, or 10 facets to the most ornate church)
There has never once in history been a point where people decieded that they where going to stop innovating or producing permanently. This is equivalent with death.
So the people with the most money at some point will decide to build things which they spend all their money on which increases GDP.
Also the actual "number" of gdp if heavily controlled by USA inflation rates. So we should always look at gdp in regards to inflation adjusted dollars to get a clearer picture.
So the way I understood it, productivity, efficiency and quality gains can increase GDP year over year.
Say we are a country of 1 person. If that person can make a car in 2025, but in 2026 manages to make both a car and a house, the GDP has more than doubled. Doesn't matter that nobody paid the money for them.
Another weird thing is, say that 1 person country makes a car in 2025, and in 2026 makes a similarly priced car, if the car is higher quality, it counts as a higher GDP, because they'll measure its value as greater than last year's model, even if it sells for the same price, because the old model would now be worth less.
GDP is a fucked up way to look at life. It's go to way to look at whether a country is doing good, but it's consuming our environment and our own sanity in so many ways.
That's one of the reasons why I think that actually limiting the working hours (bringing it down to 30, and eventually to 20 hours a week) should be one of the main agenda points for this coming century. It's important for our environment, but also for our own sanity.
One could argue that given a sufficiently large GDP, one can make the individual choice to earn less and have more time. But that's sadly not how things work, since having more workforce available also devalues work relative to subsistence goods (e.g., you can't afford a roof without a full time job). Also, individualism is such a powerful ideology in a market driven economy. Maximizing individualism itself can help you get ahead in the marketplace, and spreads through society via marketing, private media. At some point, we even stop seeing how to behave differently than to maximize our own profit. We need democratic instruments outside of the marketplace to steer our society in a way that improves our lives, regardless of what that does to GDP.
A human life, it's worth what? 1 millions usd? 10million usd? 20 million usd? Is it worth saving lives of GDP goes down?
We're due for a reckoning.
That's why in my 1 person country example, GDP still goes up, nobody has to buy the cars.
Why not? It has been changing forever. It was on a pretty consistent upward trend in the US since there was a US, roughly doubling since 1790, but it has started to decrease in the last few years.
I'm not a real "investor" (index funds only) but I am feeling more willing to forgo gains to be more risk averse just based on my own neuroses.
Maybe I cash out and buy T-bills? Gold? Bullets? What's the non-crazy person equivalent?
What are the implications of bond prices in this dubious interest rate environment? It seems no one knows what the Fed should or wants to do, including the Fed. And if the economy is on shaky ground, won't that be bad for bonds if companies can default?
You're not expecting it to earn much, but it should hold its value over the long term. This will reduce the expected return of the portfolio, but the goal is to get volatility to a level you can stomach, allowing you to ride out fluctuations on the equity side. Because even though we can all look at the current situation and say the stock market appears overvalued, we can't know how much higher it will go, when we've hit the top, or once it starts declining, when we've hit the bottom. Even experts do no better than luck would dictate at that game.
I'd say ex-US international value stocks, especially EU, are a better hedge.
For this round I've bought (well, bought and sold, and now waiting to buy via an order) puts on a semiconductor ETF. Since I own some of the stocks, if it goes sky high still I win, if it crashes I win, and if nothing happens I'll have to sell it 30 days before it expires to avoid the theta decay, which starts to really bite in that last month.
No one knows anything - which is the environment I'm learning to operate it.
A very conservative investor, say a boglehead or a 'value investor' would tell you to buy in an index fund and not look, unless you know for sure what you are doing and have done insane research on a company and it's priced low. They would say, buy VTI or VOO if you don't need the money within 5 years, and stop looking at it. Oh, and DCA into it versus all at once.
Gold is only for very rich people if you want to have something in the case the whole economy goes to the bin.
Bullets if you are paranoid.
Edit: Notably, you don't have to fully stop investing in the SP500. If you were previously 60% weighted towards the SP500, you can still reduce your exposure by changing that to 20%, or something like that.
And this isn't even about the total number of high-paying jobs. Even having too much income concentration (fewer, but higher paying jobs) will mean that there's less demand at the margin. To put it another way, if the job growth in say, silicon valley, starts to reverse because of AI, there will still be newcomers, but not enough to buy out the available housing at an ever increasing price.
If the price trend ever reverses and holds that way long enough to seem like a new normal, I suspect the price will suddenly correct downwards. Everyone holding on to real estate as an investment will have a great reason to sell once it becomes a depreciating asset. If it goes on long enough, people will be underwater on housing and start walking away.
The price trend is already somewhat flattened, which reduces FOMO. Why buy now when AI is uncertain and the price seems pretty flat?
Depends on equity and interest rate of course.
I'm not really an investor btw, this is just my intuition. I'm curious what others here are doing.
> I'm not really an investor btw, this is just my intuition
Don't give advice when you don't know the subject. For a start, there are more than 2 assets. For some, certain corporate bonds look nice right now. Although indices are overpriced and carry risk due to the bubble, much of the wider market is extremely cheap. Developed and undeveloped foreign markets have also been outperforming the US. And commodities...
Diversification is the bedrock of portfolio management, meaning owning a range of assets that collectively perform acceptably under a range of scenarios. But it’s generally not sexy, not something you catch individuals bragging about - avoiding permanent loss of capital.
Think about what risk you’re willing to take, in the context of your job/career prospects, current investments etc.
These are things for you to decide. Wouldn’t trust anyone who says buy x without knowing your individual circumstances.
What I can say is there are consistent patterns for many successful investors, and the media will tend to focus on the outliers / lottery winners, which by definition are difficult to emulate / replicate. Be wary of survivorship bias and the narrative fallacy.
Particularly as it seems contagion is more AB’s more likely. That the implosion won’t be limited to the mag 7.
Wow, what a sentence. It starts out bad and just gets worse.
Identify the therefore part of the prediction and enumerate the three highest priority steps.
Have you determined that the stock market will crash and bought positions accordingly? Have you sold all your nvidia stock? What are the implications in the broader economy and what steps have you taken?
This sort of approach is pretty aggressive and definitely contrarian to the general market, but some alternatives to mitigate the coming pain (if you believe it's near) would be shifting into a more liquid position to take advantage of tightening liquidity, i.e. big companies may see their shares tank but will likely still be able to service their debt. In the meantime you'll miss out on a market that still seems pretty strong.
AI literally does people's jobs for them. There's not much imagination required.
It's also not doing peoples' jobs for them, for the most part. AI's supporters do very loudly proclaim this, though.
From what I can tell at this point it's a solution looking for a problem. Incredibly impressive, not so useful
The closest thing I can think of is fiverr type gigs, and I'm still paying someone on fiverr for like, UI assets/design for an extremely simple game with 5 screens, and it's not particularly close.
The bubble may deflate but every company mentioned will still be standing, whereas in 1999 many of them were basically Ponzi schemes relying on further investor dollars to subsidize losses. All this AI spending will hurt some investors if the bubble pops but just make for a few bad quarters for the big tech cos.
Plenty of old companies spiked in 2000. Companies like Microsoft, Intel, or Cisco. Shovel sellers with a history of decent profits. I mean, the NASDAQ crashed, an it is not all made of start ups. You sound in denial, but there are more similarities than you seem to realise.
"All but Alphabet have seen big share declines in the past month. Microsoft is down 12 percent, Amazon is down 14 percent, Meta is down 22 percent, Oracle is down 24 percent"
That fluctuates anyway and profits are made by some - nothing new here.
I think the world needs to detach from the stock markets though. That may not seem realistic right now, but if you look at the current US president and the ties to superrich, we really have a huge problem now. A few parasitize on the masses. That can not be sustained. It is not ethical.
"It will spark a generation of innovations that we can’t yet even imagine."
I am not so sure. So far I successfully avoided AI, including becoming dependent on AI - I am not. So that is good.
I can not really see what "innovation" would make me want to embrace AI. Perhaps I can be forced into it, but right now I am happy avoiding it.
"Because we humans are pretty good at predicting the impact of technology revolutions beyond seven to ten years."
No, we really are not.
"Not only does the AI bubble in 2025 feel like the internet bubble in 1999"
It is still not the same.
I feel the article is falling apart there. It tries too much to compare to the 1999, but it is not the same.
The Tulip mania (if it existed) was a bubble. It popped, it's never coming back. BeanieBabies was a bubble for the same reason. NFT art remains to be seen, but I think it was likely a bubble.
The internet was over-invested and decreased significantly when looking on a timeline of 5-7 years.
But outside of that, if you were to take the valuation of internet companies, it is greater than during the period we call the bubble.
We'll see the same with AI. There will most likely be a drop in valuations when looking at a medium term timescale, but long-term, I expect AI companies will be worth far more than they are today.
When the markets drop on a monthly scale, but then rebound, we don't call that a bubble, so why do we call this sub-decade decline a bubble?
Do you think we should have another term for this?
Same with the housing bubble, yes, it popped and lots of people got hurt, but those who were able to hang-on, I think, ended up ok, and on a moderately decent timeline.
Poor old much maligned tulips. The mania isn't coming back but the tulip industry had endured for nearly four hundred years and Holland produces billions of tulip bulbs each year. Some of the more conservative tulip buyers in mania days probably even did ok out of it.
Crazy amount of funding, little to no revenue, no competitive moat, no demand.
Compare that to today, and you see only the crazy amount of funding part is the same.
For the shovels part: Actually Global Crossing tried to sell shovels. But failed since there was no demand and no moat. Now compare that to NVIDIA.
Doesn't this also describe Thinking Machines Lab?
In the late 90's and early 2000's, businesses were SALIVATING to get online, individuals were finding new ways to benefit and profit from it, and massive investment was being made to facilitate what was inevitable: an interconnected network of everything. Do you remember faxing things ? Paper mail? People half in the know were pushing the Boomers and older Gen-X types to get on with it and modernize.
Now? Not only are people not CLAMORING for more AI, it's that The Powers that Be are forcing it down our throats. At work, we have mandatory AI training, we have people getting promoted for promoting extremely dubious AI solutions both internally and on our product. I log into ANY web site now, whether I'm shopping for a vacuum cleaner or logging into a vendor website, and I get AI shoved in my face, from from "assistant" I have to interact with before typing "agent" to new features I don't care about.
Is there some truth, some merit? Absolutely. But my red flag I'm trying to raise is this: never did it feel FORCED in the 90's, there was a salivation from individuals to get more online, and a reluctance from institutions like elementary and high schools to get with the program.
Now? Corporations large and small are shoving it down our throats. Why? Well, to justify the crazy spending.
I'm no prophet and the world (and economy) are fundamentally unpredictable. But I'll say this. I'm putting my money where my mouth is, and I've put in an order to buy a 5 digit dollar amount of puts on a big 'AI' type ETF, that'll expire in the Spring. It's already wobbling and if you can't beat them, profit off of them when they stumble.
There's absolutely something wrong in the current moment, even if AI is somehow the future. For one thing, the U.S. economy would probably be in a recession right now if it weren't for this insane AI spending. It's wobbled with the recent Nvidia earnings release, and I think it is going to dip (not crash, but start dipping) soon.
The author wrote:
"None of these companies has proven yet that AI is a good enough business to justify all this spending. But the first four are now each spending $70 billion to $100 billion a year to fund data centers and other capital intensive AI expenses. Oracle is spending roughly $20 billion a year. "
In my opinion it's a theoretical arms race 'just because my competitor might win', and not based on anything certain.
It’s not as if there were ten million people using and/or building on the Internet, and then this bubble popped and for some years there were only ten thousand people on the Internet.
And I think the same is true for „AI usage/adoption“.
So, if people are wondering out loud (with widespread traction) if there's a bubble, there's probably not one. It may be self-fulfilling. The awareness of a potential bubble influences us to be more cautious.
For the last most explosive bubbles -- "dot-com" (~2000) and "housing" (~2008) -- you can go back and find all sorts of warnings and critiques and fretting and skepticism in newspapers, academic and industry journals, blogs, television, personal ephemera, etc. And not too far from almost all the examples you find, you'll also find somebody blowing off the skepticism.
The tricky part is that you can more or less find similar dialog in all those sources even when there didn't turn out to be a looming collapse. There's just always people worrying about collapse or hard correction when the markets are running hot and always people blowing them off, and sometimes worriers prove right. Eventually. And sometimes they don't, and the underlying economy either catches up with the market or government policy successfully props it up for long enough that some other concern dominates or some other industry can absorb the over-allocated investment.
Basically, it turns out your heuristic for spotting a bubble faces too much noise and isn't actually all that informative at all.
This seems like a variation on the President's (and my CTO's) process of 1. go on record both supporting and denouncing all positions, but commit to none, 2. wait... 3. spin your previous wisdoms based on the actual outcome. A super-inconsistent & confusing track record is actually a major asset when executing this strategy!
LLMs can be useful tools in the right situations and the valuations for companies involved with them can be wildly and irrationally inflated at the same time.