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The current state of the theory that GPL propagates to AI models

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Re: The current state of the theory that GPL propagates to AI models

#311

Earlier quoted context omitted.

You don't get to unilaterally make laws for the rest of us, which is what you are trying to do when you throw around terms like "stealing" in contexts where they have no legal meaning. Sorry. If the incumbent copyright interests insist on picking an unnecessary fight with LLMs or AI in general, they will and must lose decisively. That applies to all of the incumbents, from FSF to Disney. Things are different now.

The laws already exist. If you side with corrupt judges disrespecting these laws and interpreting them in favor of big tech corps, it's your choice)

I see; the laws aren't in question or in flux, but it's the judges who are wrong. Enlightening.

I still don't understand how copyright maximalism has suddenly become so popular on a site called "Hacker News." But it's early here, and I'm sure I'm not done learning exciting new things today.

Re: The current state of the theory that GPL propagates to AI models

#312
post #302

Earlier quoted context omitted.

Those first two indeed look correct (third link is not public); indeed free chatgpt is understandably not the best, but I did give it basically the smallest function in my codebase that does something meaningful, instead of any of the actually-non-trivial multi-kilobyte functions doing realistic things needing context.

Would be interesting to push the models with a couple of larger functions, if you have some links you'd like me to try. I have paid pro accounts on all three, but for some reason Gemini is no longer allowing links to be shared on some queries including this one. All it would let me do is export it to Docs, which I thought would be publicly visible but evidently isn't.

Actually, even finding a larger function that would by itself have a meaningful disassembly is posing problematic; basically every function deals with in-memory data structures non-trivially, and a bunch do indirect jumps (function pointers, but also lookup-table-based switches, which require table data from memory in addition to assembly to disassemble).

Like, here's a ~2.7x larger function: https://dzaima.github.io/paste/#0jVdNjxs3DL3nVwzQo30gRY00ChY... (is https://github.com/dzaima/CBQN/blob/90c1dc09e88c5324373281f6... with a bunch of inlining)

(I'm keeping the other symbol names there even though they'd likely not be there for real closed-source things, under the assumption that for a full thing you'd have something doing a quick naming pass beforehand)

This is still very much on the trivial end, but it's already dealing with in-memory structures, three inlined memory allocation calls (two half-deduplicated into one by the compiler, and the compiler initializing a bunch of the objects' fields in one store), and a bunch of inlined tagged object manipulations; should definitely be possible to get some disassembly from that, but figuring out the useful abstractions that make it readable without pain would probably take aggregating over multiple functions.

(unrelated notes of your previous results - claude indeed guessed correctly that it's BQN! though CBQN is presumably wholesale in its training data anyway; it did miss that the function has an unused 0th arg (a "this" pointer), which'd cause problems as the function is stored & used as a generic function pointer (this'd probably be easily resolved when attempting to integrate it in a wider disassembly though); neither claude nor cgpt unified the `x>>48==0xfff7` and `(x&0xffff000000000000)==0xfff7000000000000` which do the exact same thing but clang is stupid [https://github.com/llvm/llvm-project/issues/62145] and generates different things; and of course a big question is how many such intricacies could be automatically reduced down with a full codebases worth of context, cause understandably the single-function disassemblies are way way more verbose than the original)

Re: The current state of the theory that GPL propagates to AI models

#313
post #261

Earlier quoted context omitted.

Humans can generalize. LLMs just predict the statistically-most-likely token.

human brains are just chemical reactions and electrical transmission between neurons too. You're comparing completely different layers of abstraction in your arguments.

You're comparing pie-in-the-sky scifi AIs with humans.

LLMs are what we have today. They can't generalize. Humans can.

That might change someday, but it certainly hasn't yet.

Re: The current state of the theory that GPL propagates to AI models

#314

Earlier quoted context omitted.

You pay them an amount determined by the court or your settlement, and you also have to stop using the code. This is how everything works. Corporations can't go to prison.

Corporations can have their business licence temporarily or permanently suspended.

10 years in prison is about 15% of a typical life.

You could give 15% of the ownership to the aggrieved party.

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