We are now at the mercy of labs to provide frontier models as open-weight. Now that even some Chinese labs are releasing their models as weight-available, what stops them from prohibiting certain internal uses of new models? What about public chatbots?

Open models we have now will become obsolete within a few years. Imagine a world where our last open models were from the GPT-2 era.

I believe we need truly sovereign models, not in the Western sense, but from a community perspective. We need a model line that stays open-source across generations.

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lisplist an hour ago | parent | next [-]

The problem is the massive amount of money, data, and talent to produce anything remotely competitive. Ideas have been floated about distributed training, but training requires insanely fast interconnect between nodes making it impossible with the current methodologies we have. Now if you mean funded at a national level, that seems more doable so long as the training runs are centralized in big DCs.

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wolttam an hour ago | parent | prev | next [-]

There's always going to be some nerds out there that want to make and release a model as open, and share their knowledge along the way. I'm not too concerned.

The fear you're sharing has been shared since day 1 of open-weight models and it has yet to come to fruition.

Further, regardless of what any of these labs license their model as, the end user who has downloaded the weights can still use them for virtually any purpose (synthetic data, classification, etc) as much as they want and there is no way to reasonably enforce a license on those outputs.

So even if you can't run a service using this model's weights (without a license), the weights still do provide utility for training new models with any other license.

*Edit, responding to the replies: Constraints give rise to ingenuity. Who knows how we'll be training models in the future. Hopefully in a distributed fashion, maybe with some kind of consensus-driven training dataset selection. Crowd funding, etc. There's too many people that want this, and the knowledge on how to do it is out there (many times by now)

	▲	crimsoneer an hour ago \| parent \| next [-]
		I think this is a quite optimistic view... releasing a SOTA model is a collosal capital investment, and unlike free software, it's not iterative - you can't make a small model and improve it one step at a time, you need to risk the whole load of cash, expertise and GPU time up front. It's only happening now because labs have bucket tons of VC cash to burn and need a big public flex to raise more cash, or because they're subsidised by the Chinese government. I'm not massively confident either of those will stay true forever.
	▲	poszlem an hour ago \| parent \| prev [-]
		Unless "some nerds" means "billionaires" - they may want to release new models as open source, but they will not have enough money to train a worthwhile model.

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wraptile 30 minutes ago | parent | prev [-]

With distillation being so effective I do wonder whether we can just crowd source open alternatives.