Kind of arbitrary since it doesn't impact their upstreams.
The very first thing I used GenAI for was fixing build and CI pipeline issues, exactly the drudgery no one cares about. Today, LLMs are excellent at the yeoman's work of maintaining patches across multiple versions and upstream, which is what I imagine a lot of Debian devs do.
Why you wouldn't want to hand that off to a computer program is beyond me.
> Debian is a large and complicated project: the release announcement for version 13 says it has 69,830 packages, which take a total of 403 GB of disk, and contain 1,463,291,186 lines of code. So, suitably, it is a large and complex poll.
Surely these are not just Debian-owned packages. Whatever Debian decides won’t apply to packages not owned by Debian
Posting this because I want people to vote -- and ideally vote for a total ban.
Crazy how divided AI is here on HN…
We’re almost to the point where the average non-technical person uses AI daily (just like phones and the internet were once only used by the technocrats) without blinking, it will be ubiquitous and universal in adoption, yet comments here on HN from people that have the vantage point of seeing AND understanding how AI works, and who can also predict the inevitable integration of AI in society, have got their collective heads in the sand to the point they’re soon going to sound like conspiracy theorists.
> If Proposal H has a weakness, it's that it does not distinguish between local and cloud-based LLMs
Is the energy usage so different between local and cloud inference? Both require electricity, the local option even more than the better optimized cloud variant even perhaps. How either is powered makes the crucial difference I suppose. Both can potentially run on solar as well as gas or nuclear.
It's the training that takes the most energy, and that needs to happen for locally running or cloud models regardless.
What am I missing here?