2026-07-13 06:14 UTC
Replies (5)
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@david_chisnall@infosec.exchange 2026-07-13 12:26
@hfalcke@mastodon.social LLMs will stay and people will use it. There's a big assumption here, that comes from the previous one: It is not that AI does not work, as often said here, it does work for many applications. That's not the question. The first-order question is: do they deliver more value than they cost. And the answers to that are skewed by the fact that the current services are heavily subsidised and customers are paying 10-50% of the minimum viable price. So, if people actually have to pay the real price, how many of those use cases still exist? The follow-on to that is, given that increasing the price by a factor of 2-10x will significantly reduce the demand, what will the resulting price be? Inference costs won't change much, but the price to users is the inference costs plus the training costs amortised across users (plus profit). Fewer users means that the training costs are amortised across fewer users and so the per-user costs go up. So how many use cases are still economically feasible if the prices go up by a factor of 20x? But that's just the first order. The second order is: how affordable is it when you factor in the cost of externalities. Current LLMs are trained by doing something that, in any other context, would be a clear-cut case of large-scale copyright infringement. If LLM vendors had to actually pay for licenses for the things that they are ingesting in training, the cost of training would go up by at least a factor of 10x. So there's a huge assumption in 'LLMs will stay'. The companies that train them do so on the assumption that they'll eventually be able to recoup that (huge) investment. If you don't train new ones, they become stale quickly. To be useful, they need to include recent events. For software, an LLM that doesn't know about new APIs and language features and does know about deprecated / removed ones is useless. For other uses, the shifts may be slower or faster. But training isn't a one-shot cost as a result, you're constantly needing to do retraining. And that's what needs the massive datacentres full of GPUs. So, if you want to claim LLMs are here to stay, you need to answer a simple question: Who is going to pay for the training? If no one is, then how will LLMs remain useful? The entire industry is spending enormous amounts of money for tiny returns. How do you expect this to shift to actually making money? Note that the numbers in this page look much better than they are, because all of that $516 B in revenue for NVIDIA is spending from other companies (which must be passed on to customers for anyone else to become profitable).
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@letterus@kirche.social 2026-07-13 06:23
@hfalcke@mastodon.social Yes, regulating is the political way to go. Same as you‘re regulating the production and export of weapons or the usage of nuclear power. There are better algorithms, but those using as much data (LLM) will use as much energy. Their advance will be too slow. It will cost us enormous amounts of energy, water and and resources needed elsewhere to save human lifes on the planet.
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@jknodlseder@mastodon.social 2026-07-13 06:28
@hfalcke@mastodon.social Well, the same that we do with other things that are ethically not acceptable: prohibition.
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@GrahamDowns@mastodon.africa 2026-07-13 06:37
@hfalcke@mastodon.social I often feel like the people who are screaming, "No! No! Absolutely not! Under no circumstances should you use an LLM!" today are the same sort of people who would've been screaming, "No! No! Absolutely not! Under no circumstances should you deploy conveyer belts in your factory/shop!" back in 1913.
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@GrahamDowns@mastodon.africa 2026-07-13 06:50
@hfalcke@mastodon.social AI isn't making workers happier either, though. They're making management and executives happier (*maybe*, depending on their industry and their individual comfort levels and their company policies and such), but by and large, they're not making general, run-of-the-mill workers happier. But overall they [conveyer belts] were a good thing, because they improved the speed of production, increased GDP, sped up progress in a variety of different industries... and I don't think many workers today could imagine their lives without them. LLMs have a lot of problems, it's true. Maybe even more than conveyer belts had back then. :) But ultimately, it's about progress, and as you intimated, you can't stop progress. I attended a webinar a while ago about using AI as a software developer, and the big takeaway quote was, "AI is not going to take your job. But your competitor who is using AI probably will."