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Saying Goodbye to GitHub

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Re: Saying Goodbye to GitHub

#391

Post by dragonwriter »

avodonosov wrote: post #188
Aaron2222 wrote: post #12

Earlier quoted context omitted.

Aren't they claiming that it's fair use? IANAL, but wouldn't that make the licence irrelevant if training AI/ML models was found to be fair use? And if not, it's a licence violation anyway?

It will be difficult to claim fair use if training AI model is explicitly mentioned in the license, I think. Currently GPL says: > To "modify" a work means to copy from or adapt all or part of the work in a fashion requiring copyright permission, other than the making of an exact copy. The resulting work is called a "modified version" of the earlier work or a work "based on" the earlier work. > A "covered work" means…

> It will be difficult to claim fair use if training AI model is explicitly mentioned in the license, I think

Fair use is a statutory right (codifying what courts had 0reviously found to be an aspect of Constitutional free expression rights limiting the copyright power) that limits the exclusive rights of copyright owners. It can't be reduced in scope by license terms, because it deals with what the owner has no right to control in the first place.

(You may be confusing “fair use” with “implied license”, and, yes, explicit license terms would be a powerful argument against an implied license argument.)

Re: Saying Goodbye to GitHub

#392

Post by usrbinbash »

FeepingCreature wrote: post #332
usrbinbash wrote: post #294

Earlier quoted context omitted.

> it is because I understand the stochastic-parrot argument and think it is erroneous. Okay then, what exactly about it is erroneous? Because stochastically sorting the set M of known tokens by likelyhood of being the next, is literally what LLMs do.

There's a class of statements that can be either interpreted precisely, at which point the claim they make is clearly true but trivial, or interpreted expansively, at which point the claim is significant but no longer clearly true. This is one of those: yes, technically LLMs are token predictors, but technically any nondeterministic Turing machine is a token predictor. The human brain could be viewed as a token predi…

> The human brain could be viewed as a token predictor

No it really couldn't, because "generating and updating a 'mental model' of the environment." is as different from predicting the next token in a sequence, as a bees dance is from a structured human language.

The mental model we build and update is not just based on a linear stream, but many parallel and even contradictory sensory inputs that we make sense of not as abstract data points, but as experiences in a world of which we are part of. We also have a pre-existing model summarizing our experience in the world, including their degradation, our agency in that world, and our intentionality in that world.

The simple fact that we don't just complete streams, but do so with goals, both immediate and long term, and fit our actions into these goals, in itself already shows how far a humans mental modeling is from the linear action of a language model.

Re: Saying Goodbye to GitHub

#394

Post by usrbinbash »

m4nu3l wrote: post #314
usrbinbash wrote: post #302

Earlier quoted context omitted.

That changes exactly nothing about the validity of my statement. Yes, GPT-4 is better at this mimicry than GPT-3 or GPT-3.5. And GPT-3 was better at it than GPT-2. And all of them were better than my out-of-fun home-built Language Model projects that I trained on small But being better at mimicking reason, is still not reasoning. The model doesn't know what a coffeemug is, and it doesn't know what a football is. It a…

> But being better at mimicking reason, is still not reasoning How do I know people are not using a similar process when they perform "reasoning" but with a way more elaborate model? Can you prove me that the two are inherently different in the type of output they produce regardless of how large a ML model is or can be? Because if you can't, and they produce the same type of output, the processing could be similar en…

> but with a way more elaborate model?

Simple: I know that humans have intentionality and agency. They want things, they have goals both immediate and long term. Their replies are based not just on the context of their experiences and the conversation but their emotional and physical state, and the applicability of their reply to their goals.

And they are capable of coming up with reasoning about topics for which they have no prior information, by applying reasonable similarities. Example: Even if someone never heard the phrase "walking a mile in someone elses shoes", most humans (provided they speak english) have no difficulty in figuring out what this means. They also have no trouble figuring out that this is a figure of speech, and not a literal action.

Re: Saying Goodbye to GitHub

#395

Post by usrbinbash »

ianbutler wrote: post #307
usrbinbash wrote: post #302

Earlier quoted context omitted.

That changes exactly nothing about the validity of my statement. Yes, GPT-4 is better at this mimicry than GPT-3 or GPT-3.5. And GPT-3 was better at it than GPT-2. And all of them were better than my out-of-fun home-built Language Model projects that I trained on small But being better at mimicking reason, is still not reasoning. The model doesn't know what a coffeemug is, and it doesn't know what a football is. It a…

I agree about the utility part. However, I don't really accept the idea that this isn't reasoning, but I'm not entirely sold either way. I'd say if it mimics something well enough then eventually it's just doing the thing, which is the same side of the argument I fall on with Searle's Chinese Room Argument. If you can't discern a difference, is there a difference? So far GPT-4 can produce better work than like 50% of…

> I'd say if it mimics something well enough then eventually it's just doing the thing

Right up to the point where it actually needs to reason, and the mimickry doesn't suffice.

My above example about the Football and the Coffemug is an easy one, the objects are well represented in its training data. What if I need a reason why the Service Ping spikes every 60 seconds, here is the code, please LLM look it up. I am sure I will get a great and well written answer.

I am also sure it won't be the correct one, which is that some dumb script I wrote, which has nothing to do with the code shown, blocks the server for about 700ms every minute.

Figuring out that something cannot be explained with the data represented, and thus may come from a source unseen, is one example of actual reasoning. And this "giving up on the data shown" is something I have yet to see any AI do.

Re: Saying Goodbye to GitHub

#396

Post by natch »

bombolo wrote: post #217
natch wrote: post #186

Earlier quoted context omitted.

This seems to be what people imagine about it, not what it actually does, although I don’t doubt you could cherry-pick some snippet after a lot of trial and error to try to claim that it had regurgitated something verbatim. But certainly let’s see the examples.

You never know if a snippet it created came from another project verbatim or not… unless you claim you know all of the code that exists?

Search tools are a thing. Grep, Google, Github, etc.

But yes, exactly, you never know if a snippet came from another project or not, so let's not assume it did without some convincing evidence.

Re: Saying Goodbye to GitHub

#397

Post by natch »

bombolo wrote: post #364
bqmjjx0kac wrote: post #285

Earlier quoted context omitted.

That's a bit extreme. In theory, an LLM's proclivity for plagiarism could be studied by testing it with various prompts and searching its training data for its responses (maybe with some edit distance tolerance).

Except the training data is secret…

You can search github and other open sources to find at least a likely subset of the training data though.

Re: Saying Goodbye to GitHub

#398

Post by muyuu »

fariszr wrote: post #33

> The code that was regurgitated by the model is marketed as "AI generated" and available for use for any project you want. Including proprietary ones. It's laundering open-source code. All of the decades of knowledge and uncountable hours of work is being, well, stolen. There is nothing being given back. Leaving GitHub wont change that, OpenAI is training its models on every bit of code they can have, sourcehut, cod…

I believe he just wants to do his bit by removing his activity from github towards lowering their dominance numbers in the space. I don't think he intends to stop those LLM code models.

Re: Saying Goodbye to GitHub

#399

Post by theonlybutlet »

EarlKing wrote: post #389
theonlybutlet wrote: post #377

Earlier quoted context omitted.

The same truth holds for you or me writing up that code.

No it doesn't. My mind contains information derived from expressions I've read which I can rearrange into novel expressions. I don't regurgitate protected expressions verbatim. Co-Pilot does.

That's exactly what co-pilot does, ask it to rearrange it if what it comes up with is the same. That's what code plagiarism checkers are for.

Re: Saying Goodbye to GitHub

#400

Post by eyko »

tm-guimaraes wrote: post #194
uuuguaii wrote: post #107

Earlier quoted context omitted.

> I'm not aware of any Open Source license,or Free license for that matter,that has a give-back clause. Source code is available to -users- ,not prior-authors. In essence, copyleft licenses are exactly that. They oblige the author of a derived work to publish the changes to all users under the same terms. The original authors tend to be users. So, a license which would grant this directly to the original authors woul…

> That's the spirit here not really. All this Free Software movement started by something really similar to "right to repair", a firmware bug in a printer that was proprietary software. Free Software is about being in control of software you use. The spirit was never "contribute back to GNU", the spirit was always "if you take GNU software, you can't make it non-free". Those GNU devs at the time just wanted a good an…

The four freedoms[1] of free software specifically state that:

> The freedom to distribute copies of your modified versions to others (freedom 3). By doing this you can give the whole community a chance to benefit from your changes. Access to the source code is a precondition for this.

Emphasis in "give the whole community a chance to benefit from your changes".

1. https://www.gnu.org/philosophy/free-sw.en.html#four-freedoms

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