How so? If it's not local, it's not yours, a third party owns it.
Why would you expect that third party specifically trained their model to be more aligned to you and your needs than to them and their (business) needs?
>Why would you expect that third party specifically trained their model to be more aligned to you and your needs than to them and their (business) needs?
That is my point. Why do you think Gemma, a local model trained by Google, is aligned to you and not the values of Google.
You can similarly have a model aligned to you which you pay someone to remotely host for you instead of running it locally.
> Please don't post insinuations about astroturfing, shilling, brigading, foreign agents, and the like. It degrades discussion and is usually mistaken. If you're worried about abuse, email hn@ycombinator.com and we'll look at the data.
That also isn't saying "don't say this is an LLM". If the guidelines didn't want us to say someone is an LLM, it would explicitly say "don't say someone is an LLM". It wouldn't hint at it in an indirect way.
FWIW I do find it somewhat useful to have someone point out "this is an LLM" - I don't always have my AI detector on and I appreciate it when other people do. And when someone says particular text was LLM generated I need to go back and think about whether I believe it a bit harder.
This issue does not come from the coding assistant. In fact, humans will occasionally do the exact same thing as long as their tools have enough permissions to deploy to both local and prod from the same environment.
Fix it by separating the tools (different non-interconnected VMs, etc for dev/qa/preprod/prod environments) and the permissions (different accounts, sessions, tokens, etc for the run/debug/test/deploy loops).
Indeed, the more accurate way to say it is that people in the US don't care enough about mass school shootings to do something about it besides thought and prayers.
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