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Very nice stuff


"I don't see any reason to make a video about it". This sentence is so wrong in its depth that's difficult to know where to start arguing against it. "The disclosure is to help maintainers assess how much attention to give a PR." For the same reason we should ask how many years contributing have been writing software and in the specific language, as they are also correlated with quality of produced code. "we need to be responsible about what we're using it for and respectful to the humans on the other side that may have to review or maintain this code" Yes, producing great code and documentation, regardless the process.


There's a world of difference between giving feedback and coaching to a human that might be able to learn from that feedback and use it to do better, and giving feedback and coaching to a LLM that has a human acting as its go-between.

If research continues over the next few decades, these LLMs (and other code-generation robots) may well be able retrain themselves in real-time. However, right now, retraining is expensive (in many ways) and slow. For the foreseeable future, investing your time in providing feedback and coaching intended to develop a human programmer into a better human programmer to an LLM is a colossal waste of one's time.


In my experience (~10 companies, including bigger tech and silicon valley companies) the bigger the size the lower (if not zero) the awareness. In smaller companies and startup I've seen much more "empathy" and we used to give one-shot or recurrent sponsorship especially to projects that we were using extensively. This could also be a partial answer though, bigger companies don't really care as they could afford (or perceive so at the higher level in the ladder) to just move away or fork the project and maintain it themselves, thing that I've also seen applied in a famous telecommunication API company (guess who).


It really depends on the country and its legislation. For EU there's GDPR which has very specific deadlines and specs on how to handle data regardless the end of the company. There is a designated DPO who's in charge legally of the fate of these data, so they have to provide a solution on how to ensure the correct transition/maintenance of the data for the authority.


Especially for big projects or services it's really impractical to read them as a book. I usually end up reading a bunch sitting at the desk while working on the thing itself, but sometimes I send a couple of links/anchor that I want to deep dive on to my phone and read them when queueing/on the bus/etc.


This is really interesting, are your comfortable with OpenAI having your personal details in this case?


This is where having our own LLMs and stacks running locally will save and empower us IMHO


OpenAI's privacy claims are fine. I wouldn't worry about this any more than I worry about my email provider.


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