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What Will You Do When AI runs Out of Money and Disappear?

louwrentius.com

41–48 of 48 posts

Re: What Will You Do When AI runs Out of Money and Disappear?

#42
post #25

Earlier quoted context omitted.

>> Sam Altman has said “We’re profitable on inference. If we didn’t pay for training, we’d be a very profitable company.” Any individual Sunday service is nearly cost free if we don't calculate in the 100+ years it took to build the church...

Lol anyway, the point is that even in a scenario where all the major models disappeared tomorrow (including OpenAI, Anthropic, etc), we would still keep using the existing open source models (GLM, Deepseek, Qwen) for a long long time. There's no scenario where AI goes away completely. I don't think the "major AI services go away completely" scenario is realistic at all when you look at those companies' revenue and cu…

> There's no scenario where AI goes away completely.

the scenario is if training becomes impossible (for any reason), then the currently available models quickly become out of date

say this had happened 30 years ago

today, would you be using an "AI" that only supported up to COBOL?

Re: What Will You Do When AI runs Out of Money and Disappear?

#43

Earlier quoted context omitted.

Wildly different experience of frontier models than I have, what's your problem domain? I had both Opus and Gemini Pro outright fail at implementing a dead simple floating point image transformation the other day because neither could keep track of when things were floats and when they were uint8.

Low-level networking in some cloud applications. Using gpt-5.2-codex medium. I've cloned like 25 of our repos on my computer for my team + nearby teams and worked with it for a day or so coming up with an architecture diagram annotated with what services/components live in what repos and how things interact from our team's perspective (so our services + services that directly interact with us). It's great because we…

Yeah wild, I don't really know how to bridge the gap here because I've recently been continuously disappointed by AI. Gemni Pro wasn't even able to solve a compiler error the other day, and the solutions it was suggesting were insane (manually migrating the entire codebase) when the solution was like a 0.0.xx compiler version bump. I still like AI a lot for function-scale autocomplete, but I've almost stopped using agents entirely because they're almost universally producing more work for me and making the job less fun, I have to do so much handholding for them to make good architectural decisions and I still feel like I end up on shaky foundations most of the time. I'm mostly working on physics simulation and image processing right now. My suspicion is that there's just so many orders of magnitude more cloud app plumbing code out there that the capability is really unevenly distributed, similarly with my image processing stuff my suspicion is that almost all the code it is trained on works in 8bit and it's just not able to get past it's biases and stop itself from randomly dividing things that are already floats by 255.

Re: What Will You Do When AI runs Out of Money and Disappear?

#46

Perhaps this is a helpful model, rather than worrying about the "billions spent" and whether its inference vs training. How much would it cost you to deploy a model that you and maybe a few coworkers could effectively use? $400k probably to buy all the hardware required to host a top-tier model that could do a few hundred tokens per second for 10 concurrent users? That's $40k per person. Ammortize the hardware over 5…

After a hypothetical AI crash, the cost of hardware will plummet . It will suddenly become quite affordable to spin up a GPU or five on-prem to host a couple of models for internal use. The only reason hardware is so expensive now is to scalp the hyperscalers. Once that demand crashes, the supply will skyrocket and prices will crash.

Fair point -- but my overall point about how much users may have to pay to make these companies profitable stands. Maybe if prices stay depressed for years, but these companies are doing buildout at current prices, and they need to make returns on hardware they are buying now. I suppose they could bank on prices coming down in 2 to 3 years by a factor of 10, then current price ($200 per month) might be profitable (disregarding training, employees, power, etc).
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