dandi8

That’s not creepy or weird, that’s horrifying.

Except “mass” is not useful by itself. It’s not a chair factory where more people equals faster delivery, just like 9 women won’t deliver a baby in a month. I wish companies understood this.

I think the answer to this is lack of adoption.

Ok, but the comment thread is about people preferring Bluesky to Mastodon, hence my confusion.

Isn’t the format literally just Twitter?

Pegasus?

In my experience LLMs do absolutely terribly with writing unit tests.

IMO this perspective that we’re all just “reimplementing basic CRUD” applications is the reason why so many software projects fail.

You seem to think that “open source” is just about the license and that a project is open source if you’re allowed to reverse engineer it.

You have a gross misunderstanding of what OSS is, which contradicts even the Wikipedia definition, and are unwilling to educate yourself about it.

You suggest that Mistral would need to lend us their GPUs to fit the widely accepted definition of OSS, which is untrue.

You’re either not a software engineer, or you have an agenda.

Because of this, I will not be continuing this conversation with you, as at this point it is just a waste of my time.

You’re, hopefully not on purpose, misunderstanding the argument.

You can download a binary of Adobe Photoshop and run it. That doesn’t make it open source.

I cannot make Mistral Nemo from just the open-sourced tools, therefore Mistral Nemo is not open source.

But then it’s the tools to make the AI that are open source, not the model itself.

I think that we can’t have a useful discussion on this if we don’t distinguish between the source code of the training framework and the “source code” of the model itself, which is the training data set. E.g, Mistral Nemo can’t be considered open source, because there is no Mistral Nemo without the training data set.

It’s like with your Doom example - the Doom engine is open source, but Doom itself isn’t. Unfortunately, here the analogy falls apart a bit, because there is no logic in the art assets of doom, whereas there is plenty of logic in the dataset for Mistral - enough that the devs said they don’t want to disclose it for fear of competition.

This data set logic - incredibly valuable and important for the behavior of the AI, as confirmed by the devs - is why the model is not open source, even though the training framework might be.

Edit:

Another aspect is the spirit of open-source. One of the benefits of OSS is you can study the source code to determine whether the software is in compliance with various regulations - you can audit that software.

How can we audit Mistral Nemo? How can we confirm that it doesn’t utilize copyrighted material to provide its answers?

We’ll have to agree to disagree on pretty much everything, then.

You’re trying to change the definition of open source for AI models and your argument is that they’re magic so different rules should apply.

No, they’re not fundamentally different from other software. Not by that much.

The training data is the source of knowledge for the AI model. The tools to train the model are the compiler for that AI model. What makes an AI model different from another is both the source of knowledge and the compiler of that knowledge.

AFAIK, only one of those things is open source for Mistral - the compiler of knowledge.

You can make an argument that tools to make Mistral models are open source. You cannot make an argument that the model Mistral Nemo is open source, as what makes it specifically that model is the compiler and the training data used, and one of those is unavailable.

Therefore, I can agree on the social network analogy if we’re talking about whether the tools to make Mistral models are open-source. I cannot agree if we’re talking about the models themselves, which is what everyone’s interested in when talking about AI.

That’s like saying the source code of a binary is a bunch of hexadecimal numbers. You can use a hex editor to look at the “source” of every binary but it’s not human readable…

Yes, the model can be published without the dataset - that makes it, by definition, freeware (free to distribute). It can even be free for commercial use. That doesn’t make it open source.

At best, the tools to generate a model may be open source, but, by definition, the model itself can never be considered open-source unless the training data and the tools are both open-source.

Gee, you sure put a lot of effort into supporting your argument in this comment.

https://en.m.wikipedia.org/wiki/Open-source_software

Open-source software (OSS) is computer software that is released under a license in which the copyright holder grants users the rights to use, study, change, and distribute the software and its source code to anyone and for any purpose.

From Mistral’s FAQ:

We do not communicate on our training datasets. We keep proprietary some intermediary assets (code and resources) required to produce both the Open-Source models and the Optimized models. Among others, this involves the training logic for models, and the datasets used in training.

https://huggingface.co/mistralai/Mistral-7B-v0.1/discussions/8

Unfortunately we’re unable to share details about the training and the datasets (extracted from the open Web) due to the highly competitive nature of the field.

The training data set is a vital part of the source code because without it, the rest of it is useless. The model is the compiled binary, the software itself.

If you can’t share part of your source code due to the “highly competetive nature of the field” (or whatever other reason), your software is not open source.

I cannot lool at Mistral’s source and see that, oh yes, it behaves this way because it was trained on this piece of data in particular - because I was not given accesa to this data.

I cannot build Mistral from scratch, because I was not given a vital piece of the recipe.

I cannot fork Mistral and create a competitor from it, because the devs specifically said they’re not providing the source because they don’t want me to.

You can keep claiming that releasing the binary makes it open source, but that’s not going to make it correct.

Just because open source AI is not feasible at the moment is no reason to change the definition of open source.

Are the petabytes of training data included in the repo? No? Then how could it ever be called open source?

At best, some of the current AI can be called freeware.

If you’re just including the trained AI itself, it’s more like including a binary, rather than source.

You can’t really modify Llama in a significant way, can you? You can’t fork it and continue improving that fork.

Isn’t the entire point of federation to be able to do what you’re describing?

Joplin itself is AGPL. Unfortunately, Joplin Server is under “JOPLIN SERVER PERSONAL USE LICENSE”.

While I really like Joplin, I’m thinking of making the switch to something fully open source.