601–610 of 936 posts
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This is bending the definition to the other extreme. Linux doesn't ship you the compiler you need to build the binaries either, that doesn't mean it's closed source. LLMs are fundamentally different to software and using terms from software just muddies the waters.
Then what is the "source"? If we are to use the term "source" then what does that mean here, as distinct from it merely being free?
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"Open weights" means you can use the weights for free (as in beer). "Open source" means you get the training dataset and the methodology. ~Nobody does open source LLMs.
Why is the dataset required for it to be open source? If I self host a project that is open sourced rather than paying for a hosted version, like Sentry.io for example, I don't expect data to come along with the code. Licensing rights are always up for debate in open source, but I wouldn't expect more than the code to be available and reviewable for anything needed to build and run the project. In the case of an LLM…
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Even if everything was released how you described, what good would that really do for an individual without access to heaps of compute? Functionally there seems to be no difference between open weights and open compute because nobody could train a facsimile model. Furthermore, all frontier models are inscrutable due to their construction. It’s wild to me seeing people complain semantics when meta dropped their model…
That's not the discussion. We're talking about what open source is, and it's having the weights and the method to recreate the model. If someone gives me an executable that I can run for free, and then says "eh why do you want the source, it would take you a long time to compile", that doesn't make it open source, it just makes it gratis.
Ok one notable difference: did the linux researchers of yore warn about adversarial giants getting this tech? Or is this unique to the current moment? That for me is the largest question when considering the logical progression on "linux open is better therefore ai open is better".
We can't open source Linux because bad people might run servers? Can you imagine the disinformation they could spread with those? With enough of them you could have a massively global site made entirely for spreading it. God what if such a thing got into the hands of an egocentric billionaire?
The FTC also recently put out a statement that is fairly pro-open source: https://www.ftc.gov/policy/advocacy-research/tech-at-ftc/202... I think it's interesting to think about this question of open source, benefits, risk, and even competition, without all of the baggage that Meta brings. I agree with the FTC, that the benefits of open-weight models are significant for competition. The challenge is in distinguishing…
making food that people want to buy is good actually i am not down with this concept of the chattering class deciding what are good markets and what are bad, unless it is due to broad-based and obvious moral judgements.
Still huge props to them for doing what they do.
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You can fine tune the models, and you can modify binaries. However, there is no human readable "source" to open in either case. The act of "fine tuning" is essentially brute forcing the system to gradually alter the weights such that loss is reduced against a new training set. This limits what you can actually do with the model vs an actual open source system where you can understand how the system is working and mod…
> vs an actual open source system where you can understand how the system is working and modify specific functionality. No one on the planet understands how the model weights work exactly, nor can they modify them specifically (i.e. hand modifying the weights to get the result they want). This is an impossible standard. The source code is open (sorta, it does have some restrictions). The weights are open. The trainin…
Which is my point. These models aren't open source because there is no source code to open. Maybe one day we will have strong enough interpretability to generate source from these models, and then we could have open source models. But today its not possible, and changing the meaning of open source such that it is possible probably isn't a great idea.
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Either you port Tensorflow (Apple)[1] or PyTorch to your platform or you allow CUDA to run on your hardware (AMD) [2]. Companies are incentives to not have NVIDIA having a monopoly but the thing is that CUDA is a huge moat due to compatibility of all frameworks and everyone knows it. Also, all of the cloud or on premises providers use NVIDIA regardless. [1] https://developer.apple.com/metal/tensorflow-plugin/ [2] htt…
>> Either you port Tensorflow (Apple)[1] or PyTorch to your platform or you allow CUDA to run on your hardware (AMD) [2]. Companies are incentives to not have NVIDIA having a monopoly but the thing is that CUDA is a huge moat due to compatibility of all frameworks and everyone knows it. Also, all of the cloud or on premises providers use NVIDIA regardless. This never made sense to me -- Apple could easily hire top ta…
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They don't "[allow] developers to modify its code however they want", which is a critical component of "open source", and one that Meta is clearly trying to leverage in branding around its products. I would like them to start calling these "public weight models", because what they're doing now is muddying the waters so much that "open source" now just means providing an enormous binary and an open source harness to r…
My central point is this: "are available for most people to use for a lot of stuff, and this is way way better than what competitors like OpenAI offer." I presume you agree with it. > rather than serving access Its not the same access though. I am sure that you are creative enough to think of many questions that you could ask llama3, that would instead get you kicked off of OpenAI. > They don't "[allow] developers to…
The limitations here are technical, not legal. (Though I am aware of the legal restrictions as well, and I think its worth noting that no other project would get by calling themselves open source while imposing a restriction which prevents competitors from using the system to build their competing systems.) There isn't any source code to read and modify. Yes, you can fine tune a model just like you can modify a binary but this isn't source code. Source code is a human readable specification that a computer can use to transform into executable code. This allows the human to directly modify functionality in the specification. We simply don't have that, and it will not be possible unless we make a lot of strides in interpretability research.
> Its not the same access though.
> I am sure that you are creative enough to think of many questions that you could ask llama3, that would instead get you kicked off of OpenAI.
I'm not saying that systems that are provided as SaaS don't tend to be more restrictive in terms of what they let you do through the API they expose vs what is possible if you run the same system locally. That may not always be true, but sure, as a general rule it is. I mean, it can't be less restrictive. However, that doesn't mean that being able to run code on your own machine makes the code open source. I wouldn't consider Windows open source, for example. Why? Because they haven't released the source code for Windows. Likewise, I wouldn't consider these models open source because their creators haven't released source code for them. Being technically infeasible to do doesn't mean that the definition changes such that its no longer technically infeasible. It is simply infeasible, and if we want to change that, we need to do work in interpretability, not pretend like the problem is already solved.