I dunno, I guess I should try it just to see what the buzz is all about, but I am rather opposed to plagiarism and river boiling combination, and paying them money is like having Peter Thiel do 10x donations matching for donations to a captain planet villain.
I personally want a model that does not store much specific code in its weights, uses RAG on compatibly licensed open source and cites what it RAG’d . E.g. I want to set app icon on Linux, it’s fine if it looks into GLFW and just borrows code with attribution that I will make sure to preserve. I don’t need it to be gaslighting me that it wrote it from reading the docs. And this isn’t literature, theres nothing to be gained from trying to dilute copyright by mixing together a hundred different pieces of code doing the same thing.
I also don’t particularly get the need to hop onto the bandwagon right away.
It has all the feel of boiling a lake to do for(int i=0; i<strlen(s); ++i) . LLMs are so energy intensive in large part because of quadratic scaling, but we know the problem is not intrinsically quadratic otherwise we wouldn’t be able to write, read, or even compile the code.
Each token has the potential of relating to any other token but does only relate to a few.
I’d give the bastards some time to figure this out. I wouldn’t use an O(N^2) compiler I can’t run locally, either, there is also a strategic disadvantage in any dependence on proprietary garbage.
Edit: also i have a very strong suspicion that someone will figure out a way to make most matrix multiplications in an LLM be sparse, doing mostly same shit in a different basis. An answer to a specific query does not intrinsically use every piece of information that LLM has memorized.
Its fucking disgusting how they denigrate the very work on which they built their fucking business on. I think its a mixture of the two though, they want it plagiarized so that it looks like their bot is doing more coding than it is actually capable of.
Oh absolutely. My current project is sitting in a private git repo, hosted on a VPS. And no fucking way will I share it under anything less than GPL3 .
We need a license with specific AI verbiage. Forbidding training outright won't work (they just claim fair use).
I was thinking adding a requirement that the license header should not be removed unless a specific string ("This code was adapted from libsomeshit_6.23") is included in the comments by the tool, for the purpose of propagation of security fixes and supporting a consulting market for the authors. In the US they do own the judges, but in the rest of the world the minuscule alleged benefit of not attributing would be weighted against harm to their customers (security fixes not propagated) and harm to the authors (missing out on consulting gigs).
edit: perhaps even an explainer that authors see non attribution as fundamentally fraudulent against the user of the coding tool: the authors of libsomeshit routinely publish security fixes and the user of the coding tool, who has been defrauded to believe that the code was created de-novo by the coding tool, is likely to suffer harm from misuse of published security fixes by hackers (which wouldn't be possible if the code was in fact created de-novo).