[aspenmartin]

Exactly. Incredibly hard to understand what hard, non-headline-quoting, steel man arguments there are about how exactly the market will hiccup. And as if all of the AI companies somehow know this and are looking to IPO themselves out when anthropic revenue is growing > 10x per year for multiple years. Feels like a massive disconnect between “this will all implode” people and any real numbers.

[reillyse]

All rallies do come to an end. The fact that we all don't know exactly what will cause this one to end is exactly part of the problem and 100% doesn't mean it won't happen. Usually some external shock spooks the market and a massive sell off happens.

So what could happen, any number of things. An obvious near term issue might be inflation increases dramatically in the US (on account of the oil shock), causing interest rates to increase - maybe dramatically - , which causes the stock market to retract. Also, the housing market is pretty much toast at the moment and an increase in interest rates might finish it off too causing a contraction there. So many ways things can break.

But honestly, I'll tell you after it happens and it will happen. Having lived through a few of these now when everyone tells you it's a sure thing and prices go up for ever you get an inkling you are near the pop.

[aspenmartin]

> All rallies do come to an end. The fact that we all don't know exactly what will cause this one to end is exactly part of the problem and 100% doesn't mean it won't happen. Usually some external shock spooks the market and a massive sell off happens.

Yes sure, but that statement contains zero information -- why do you believe it will end in a time short enough for the "market bubble" comments to even make sense?

External shocks -- sure of course. Inflation problems in US -- absolutely, it's a ticking time bomb with a debt crisis looming. Housing market I don't really know anything about but I'll take your word for it.

But all of this has been true for awhile, and could have been stated with equal veracity over the course of the last 5 years at least. Your beliefs shape your actions; so why does this belief shape actions any differently than it has earlier?

> ut honestly, I'll tell you after it happens and it will happen. Having lived through a few of these now when everyone tells you it's a sure thing and prices go up for ever you get an inkling you are near the pop.

Again totally true, I have also lived through them and expect more. But "these companies are IPO'ing because they know the market will pop" is kind of the thing that I was trying to address. For all the signals of market danger, there are plenty of optimistic signals all over the data. Growth is pretty robust across all sectors today.

[reillyse]

I think the original comment was before the market sneezes. So we all know it will sneeze and the companies want to get in on this business cycle. The longer they leave it the more likely they will miss it.

[torben-friis]

They need a price consumers can't stomach or are unwilling to pay, and without that the company is profitable but not able to justify investments. That's the argument.

[aspenmartin]

I'm interested in your argument but who needs a price for what exactly? Like token costs are unsustainable argument? Or are you saying they need a stock price to keep their valuation high?

[torben-friis]

Token cost might be sustainable but still not profitable enough to make up for the costs of either training or the investments gifted away until it became profitable. They also might have no relevant moat that allows them to enshittify enough. But mainly, they are in "I need to kill whole industries to be worth it" tiers of investment.

[aspenmartin]

> But mainly, they are in "I need to kill whole industries to be worth it" tiers of investment.

Yes agreed. Coding is a pretty big industry though in and of itself. Same with healthcare, legal, etc etc etc. Of course we have zero model today that can seriously kill an industry, but if you look at (1) how good things are today (insanely fast and rapid adoption) and (2) robust performance trends from many complimentary sources, it's kind of inevitable and I haven't really heard a coherent steel man argument for why "killing whole industries" is somehow a far-fetched idea.

> still not profitable enough to make up for the costs of either training or the investments gifted away until it became profitable.

Regardless of the weeds of the economics today, you have a clearly valuable asset that at the very least already a must-have for enterprise and will become even more essential over time. There is token economics that either already do or will make sense. You will have some sort of marginal cost + profit margin that things will stabilize at. You can pay a premium for high quality frontier models. "But it costs more in R&D to fund this!" ok but then token costs will increase. Why is this some sort of death knell?

[torben-friis]

>it's kind of inevitable and I haven't really heard a coherent steel man argument for why "killing whole industries" is somehow a far-fetched idea.

They don't only require "good enough to kill industries" (which is doubtful but certainly feasible), that's just step one. I think about it in terms of potential failure modes:

- if models don't reach worker-substitution levels, they fail

- if models reach that level, but it's too expensive to run and a worker's still cheaper, they fail

- if models reach that level, but the resulting tech is cheap enough to use, they fail (since open models can compete)

- If the models work but there's social rejection leading to regulation (due to mass unemployment for example), they fail

- if the models work but there are significant deal breakers (like a fundamental inability to keep them safeish to use) they fail.

So it's not really a single AI killer reason, it's more that the success case requires things to land in a very specific future where models work, and they're cheap enough, and expensive enough, and valuable enough, and exclusive enough, and safe enough, and...

Each "and" is a multiplier reducing their chances, and there's a ton or factors. Not imposible, but not where I'd put my money.

[aspenmartin]

If 1B people consume via personally or their employer on average $100/mo of tokens or services that solves the problem right there and that is not inconceivable whatsoever and feels like an underestimate. Repayment doesn’t imply you have to build an end to end replacement of an industry.

This also negates this whole like “you have to completely replace a human” fallacy. Why do you need to replace a human? Why not just increase the value each human brings you?

The model of open weights has been around for awhile. You have frontier labs releasing them. They are powerful and capable and track yet lag frontier models. Without massive government subsidies from probably China who did something similar with manufacturing I don’t get the idea of OSS somehow toppling the entire industry of frontier models. How would this happen? Did demand for frontier models drop after GPT-4? GPT-5? Because the cost of GPT-4 perf is maybe 100x cheaper today. You can always pay a premium for a better model (more data spend with proprietary data sources, more compute for training, more thinking budgets), and in the end, things will either go to a monopoly or prices will stabilize around the marginal costs.

Also safeguards are always important. They are thorny fundamental horrific problems and I can tell you there will be a hellscape of pain as people figure out the trivial ways to do bad things with some of the worst security practices we’ve seen. But I don’t get why this is a dealbreaker, we are using these systems everywhere and in loads bearing environments, today, and reliability and hallucination rates continue to increase / decrease.

[atleastoptimal]

They say it’s going to happen because they want it to happen.