Comment by somenameforme | Hacker News Reader

Comment by somenameforme | Hacker News Reader

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Another issue, one that you alluded to, is imagine AI actually was reliable. And a company does lay off e.g. 30% of their employees to replace them with AI systems. How long before they get a letter from AI Inc 'Hi, we're increasing prices 500x in order to enhance our offerings and and improve customer satisfaction. Enjoy.'

The entire MO of big tech is trying to create a monopoly by the software equivalent of dumping (which is illegal in the US [1], but not for software, because reasons), marketshare domination, and then jacking effective pricing wayyyyy up. And in this case big tech companies are dumping absurdo amounts of money into LLMs, getting absurd funding, and then providing them for free or next to free. If a person has any foresight whatsoever it's akin to a rusting van outside an elementary, with blacked out windows, and with some paint scrawled on it, 'FREE ICECREAM.'

[1] - https://en.wikipedia.org/wiki/Dumping_(pricing_policy)#Unite...

Yep. Also the problem that the AI vendor reinforces bias into their product’s training which services the vendor.

Literally every shitty corporate behaviour is amplified by this technology fad.

It's quite easy to switch LLM api, so you can just transition to a competitor. Competition between AI providers is quite fierce, I don't see them setting up a cartel anytime soon. And open source models are not that far beyond commercial ones.

It's easy to switch the LLM API, but in practice this requires having a strong eval suite so that the expected behavior of whatever is built on top changes within acceptable limits. It's really the implications of the LLM switch that matter.

You can run a reasonable LLM on a gaming machine (cost under $5000), and that's only going to get better and better with time. The irony here is that VCs are pouring money into businesses with almost no moat at all.

I think the most is small but it’s not gone yet: in these discussions I almost never see the people reporting productivity wins say they’re running local models, and there’s a standard response to problems that you should switch to a different vendor, which suggests that there are enough differences in the training and tooling to make switching non-trivial. This will especially be true for all of the non-tech specialist companies adopting things – if you bought an AI tool to optimize your logistics and the vendor pulls a Broadcom on your contract renewal, they’re probably going to do so only after you’ve designed your business around their architecture and price it below where it’d make sense to hire a team and spend years building something in house. Having laid off a lot of in-house knowledge directly helps them, too.

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