The (economic) AI apocalypse is nigh

... 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?

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.

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.

https://jjlegal.com/blog/rideshare-vs-taxis-understanding-ac...

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.

Uber was undercutting traditional taxis because, at least in the US, the traditional taxis was horrible user experience. No phone app, no way to give feedback on driver, horrible cars, unpredictable charges... This was because taxis had monopoly in most cities, so they really did not care about customers.

The times when Uber was super-cheap have long passed, but I still never plan to ride regular taxis. It's Waymo (when availiable) or Lyft for me.

His points are not backed by much evidence

Wile E Coyote sprints as fast as possible, realizes he zoomed off a cliff, looks down in horror, then takes a huge fall.

Specifically I envision a scenario like: Google applies the research they've been doing on autoformalization and RL-with-verifiable-rewards to create a provably correct, superfast TPU. Initially it's used for a Google-internal AI stack. Gradually they start selling it to other major AI players, taking the 80/20 approach of dominating the most common AI workflows. They might make a deliberate effort to massively undercut NVIDIA just to grab market share. Once Google proves that this approach is possible, it will increasingly become accessible to smaller players, until eventually GPU design and development is totally commoditized. You'll be able to buy cheaper non-NVIDIA chips which implement an identical API, and NVIDIA will lose most of its value.

Will this actually happen? Hard to say, but it certainly seems more feasible than superintelligence, don't you think?

The second interesting part is also the part you're assuming in your argument. Does the fact that OpenAI doesn't have 300 billions now and neither has the revenue/profit to generate that much matter? Unless there are deals in the background that already secured funding, this seems very shady accounting.

Well... to be fair it's only really Anthropic (and the also-ran set like xAI) that runs the risk of being over-leveraged. OpenAI is backstopped by Microsoft at the macro level. They might try to screw over Oracle, but they could pay the bill. So that's not going to move the market beyond those two stocks. And the other big players is obviously Google which has similarly deep pockets.

I don't doubt that there's an AI bubble. But it won't pop like that, given the size of the players. Leverage cycles are very hard to see in foresight; in 2008 no one saw the insanity in the derivatives market until Lehman blew up.

If it’s overt then it’s easily filtered out, if it’s baked in to deep the it harms response quality

I am sure that you already heard this sort of argument for AI. It's a way to bait that juicy government money.

This is the crux of bubbles - timing and where do you move assets so they have protection.

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.

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.

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.

> we'll have a ton of folks out there psychologically dependent on a product that is either priced out of their ability to pay or completely unavailable, and the ensuing mental health crises that might entail.

I doubt that this will become true. If there's one really tangible asset these companies are producing, which would be worth quite a bit in a bankruptcy it's the model architectures and weights, no?

Very similar to the circular funding happening between Nvidia, and their customers, Nvidia funding investments in AI datacenters which get spent in Nvidia equipment, each step of the cycle has to take a cut for paying their own OpEx where the money getting back to Nvidia diminishes in each pass through the cycle.

How about some guy not invested in the stock market, building a house and working as a plumber be impacted?

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.

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.

Check out /r/wallstreetbets for expert advice on this. /s

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.

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?

The author’s thesis seems to lack rigor.

If companies are shipping AI bots with a "human in the loop" to replace what could have been "a button with a human in the loop", but the deployment of the AI takes longer, then it's DEFINITELY not really an improvement, it's just pure waste of money and electricity.

Similarly, what I see different from the pre-AI era are way too many SV and elsewhere companies having roughly the same size and shipping roughly the same amount of features as before (or less!), but are now requiring employees to do 996. That's the definition of loss of productivity.

I'm not saying I hold the truth, but what I see in my day to day is that companies are masters at absorbing any kind of improvement or efficiency gain. Inertia still rules.