This leads me to believe that the training data won’t be made publicly available in full, but merely be “reproducible”. This might mean that they’ll provide references like a list of URLs of the pages they trained on, but not their contents.
We'll find out in September if it's true?
“ Open LLMs are increasingly viewed as credible alternatives to commercial systems, most of which are developed behind closed doors in the United States or China”
It is obvious that the companies producing big LLMs today have the incentive to try to enshitify them. Trying to get subscriptions at the same time as trying to do product placement ads etc. Worse, some already have political biases they promote.
It would be wonderful if a partnership between academia and government in Europe can do a public good search and AI that endeavours to serve the user over the company.
They missed an opportunity though. They should have called their machine the AIps (AI Petaflops Supercomputer).
OLMo is fully open
Ai2 believes in the power of openness to build a future where AI is accessible to all. Open weights alone aren’t enough – true openness requires models to be trained in the open with fully open access to data, models, and code.
Disclaimer: I’m Swiss and studied at ETH. We’ve got the brainpower, but not much large-scale training experience yet. And IMHO, a lot of the “magic” in LLMs is infrastructure-driven.
I agree with everything you say about getting the experience, the infrastructure is very important and is probably the most critical part of a sovereign LLM supply chain. I would hope there will also be enough focus on the data, early on, that the model will be useful.
But it's good to have more and more players in this space.
k__•3h ago
Great to read that!
Onavo•2h ago
esafak•2h ago
How are you going to serve users if web site owners decide to wall their content? You can't ignore one side of the market.
Onavo•1h ago
diggan•26m ago
It is a fair point, but how strong of a point it is remains to be seen, some architectures are better than others, even with the same training data, so not impossible we could at one point see some innovative architectures beating current proprietary ones. It would probably be short-lived though, as the proprietary ones would obviously improve in their next release after that.