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selfhoster11

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Executive dysfunction mitigation. Voice based interfaces. Heavyweight personal file classification with a few hours of prompt building vs labelling a bespoke classifier’s data set and training a more “lightweight” option in weeks or days. Language translation that isn’t DeepL or Google Translate for random websites. They are not deterministic, but the error rate is a lot better on these tasks vs classical approaches.

Claude Opus 4.7 3 months ago

They are trained on natural language. Not anthropomorphizing them is the worse end of the spectrum.

I didn't even realize that this is (allegedly) written with AI. If it's AI, then it's the kind of AI writing that's closer to the real deal and that I want to see more widely applied if AI is to be used.

Which is why that's not what it does. It asks you to input the hostname instead, just like deleting a repo in Github does.

I refuse to engage in "LLMs are evil, period" views. That's like walking out into a battlefield with a samurai sword, while your enemy has Gatling guns. You'll be shredded. The pressure to survive means new tools have to be examined and incorporated as and when needed. The resources needed to run a 24B LLM on a gaming GPU are not costing the earth.

Counterpoint: B corporations.

It's clearly possible for companies to self-impose safeguards: ESG/DEI, Bcorp, choosing to open source, and so on. If investors squeal, find better investors or tell them to put up with it. You can make plenty of profit without making all the profit that can be made.

I don't think the parent comment was saying it can be solved, only that the LLM paradigm is better at dealing with complexity. I agree that they are not great at it yet, but I've seen vast improvements in the past 3 months alone.