I know few CEOs/Business owners who are non programmers (well one was exposed to it/learning, but didn't go down that path) and they do use AI for various work and non work related things. One told me how at manufacturing plant someone solved some unpleasant process to input specs into machine for manufacturing by having AI creating the automation.

His comment to me was: People who don't embrace AI will eventually be outcompeted by the ones who do.

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lproven an hour ago | parent [-]

Uhuh.

And what happens when the price goes up by an extra zero on the end?

And then another one?

And then the cloud stuff goes away because all the vendors go broke, despite the price rises, and you have to switch to using local models?

That is, models that are hugely slower, unless you have a computer with hardware tensor-math acceleration, which costs 10x more because of the chip famine?

And then, suddenly, those local models cost an absolute bomb to license, because the companies that bought up the wreckage of the original model creators are trying to recoup their spend?

Meanwhile the company is being hit by nuisance litigation from people whose code the bots plagiarised, or customers who are annoyed it doesn't work?

There are so many ways all this stuff can just go away.

	▲	someaccount1234 2 minutes ago \| parent \| next [-]
		> And then another one? But what when salaries would increase by factor 100-1000? This would make AI use even cheaper. (About as realistic...) > And then the cloud stuff goes away because all the vendors go broke, despite the price rises, and you have to switch to using local models? In this case there will be cheap inference hardware on the market as someone will sell all those assets. They don't disappear when a company goes broke (object permanence). We could also speculate what would happen if all hyperscalers (AWS, GCP, Azure, Alibaba, ...) would suddenly be broke. Again, about as realistic a scenario.
	▲	revolvingthrow 26 minutes ago \| parent \| prev [-]
		>And what happens when the price goes up by an extra zero on the end? >And then another one? Well so far the price trends towards going down by the zero at the end. Inference isn’t expensive, there’s a whole laundry list of providers to choose from. It’s training (for everybody) and salaries (for US labs) that are expensive. >and you have to switch to using local models? Many companies are interested in that, if for no other reason than to avoid uploading secret sauce to we-totally-dont-train-on-your-chats-pinky-promise API endpoints. A mid sized company can cough up $500k for dxg b200 which will be useful for years and years and the only ongoing cost is electricity. Put glm 5.3 on it and it’ll zip along for a number of employees at the same time. >And then, suddenly, those local models cost an absolute bomb to license, because the companies that bought up the wreckage of the original model creators are trying to recoup their spend? How are they recouping anything on a mit licensed model released into the wild? There are plenty of models released by "who?" companies and the cost to download those is zero. >Meanwhile the company is being hit by nuisance litigation from people whose code the bots plagiarised Any day now The doom scenario makes no sense in the race to the bottom that’s happening now. China being the other big entity that’s invested in AI makes all the what-ifs about litigation and plagiarism moot; they will gladly offer everybody inference for dirt cheap, if for no other reason that they’d like it if you gifted them your IP that they will then use to outcompete you with their manufacturing prowess. The genie’s out of the bag. AI is never going away, and we all need to adapt whether we like it or not.