Wow, thanks, I have not seen this comment, yet I hinted about this in some of my other replies that I’ve done before.

Yes, I think ML is fair use, but there it would also be fair to force something into the public domain/open source if, in order to be accrued, it has to make use of fair use at unseen amounts of scale.

This would be a difficult to make law, though. Current ML is very inefficient in the amount of data it requires, but it could (and should) be made better.

Now I sail the high seas myself, but I don’t think Paramount Studios would buy anyone’s defence they were only pirating their movies so they can learn the general content so they can produce their own knockoff.

We don’t know exactly how they source their data (and that is definitely shady), but if I can gain access to a movie in a legal way, I don’t see why I would not be able to gather statistics from said movie, including running a speech to text model to caption it, then make statistics of how many times a few words were used, and followed by which ones. This is an oversimplified explanation of what a LLM does, but it’s the fairest I can come up, and it would be legal to do so. The models are always orders of magnitude smaller than the data they are trained on.

That said, I don’t imply that I’m happy with the state of high tech companies, the AI hype, the energy consumption, or the impact on the humble people. But I’ve put a lot of thought into this (and learning about machine learning for real), and I think this is not a ML problem, but a problem in the economic, legal and political system. AI hype is just a symptom.

It’s not AI

It’s not AGI, it’s not general intelligence, and it’s not comparable to a human (well, you can compare anything, but human and ML are just very different things in tons of ways).

But it is AI. The ghosts that chase Pacman are AI. A search algorithm is also AI, dammit. Of course an LLM is AI. Any agent that maximizes a function is AI. You are just embarrassing yourself.

“Theft” is never a technically accurate word when dealing with the so called “intellectual property”, because the digital content being copied without authorization is legal in tons of cases, and because, come on, property is very explicitly exclusive. I cannot copy my house or my car, but I can make copies of my works for virtually 0 cost.

Using data for training ML models is even explicitly allowed in some jurisdictions (e.g. Japan), and is likely to be fair use everywhere else. LLMs are very transformative, and while they often can produce verbatim copies of fragments of copyrighted works, they don’t store the whole works or significant pieces of them.

Don’t get me wrong, I don’t like big companies making big money. I would not mind a law that would force models to be open sourced. But restricting them to train their models on public data by restricting fair use, it would harm them very little (they could pay something if they are making some profit), while small researchers or companies would never be able to compete, because they would not have the upfront costs, nor the economic engineering to disguise profits and pay less.

I’m not fully sure what the intent of the joke is, but note that yes, it’s true that a header typically just has the prototype. However, tons of more advanced libraries are “header-only”. Everything is in a single header originally, in development, or it’s a collection of headers (that optionally gets “amalgamated” as a single header). This is sometimes done intentionally to simplify integration of the library (“just copy this files to your repo, or add it as a submodule”), but sometimes it’s entirely necessary because the code is just template code that needs to be in a header.

C++ 20 adds modules, and the situation is a bit more involved, but I’m not confident enough of elaborating on this. :) Compile times are much better, but it’s something that the build system and the compilers needs to support.

Seems very simple yet very useful. Thanks for sharing this to Lemmy!

How come it requires such a newer neovim, though? I’m still in 0.7, and I’ve not bothered to upgrade (mostly because the many OSs in which I work on, this tends to be painful).