It is kind of interesting how open machine learning already is without much explicit advocacy for it.
It’s the only field I can think of where the open version is just a few months behind SOTA in all of IT.
Open training pipelines and open data are the only aspects that could still use improvements in ML, but there are plenty of projects that are near-SOTA and fully open.
ML is extremely open compared to consumer mobile or desktop apps that are always ~10 years behind SOTA
I feel like it’s really far from being open. Besides the training data not being open, the more popular ones like llama and stable diffusion have these weird source available licenses with anti-competitive clauses, user count limits, or arbitrary morality clauses.
It is kind of interesting how open machine learning already is without much explicit advocacy for it.
It’s the only field I can think of where the open version is just a few months behind SOTA in all of IT.
Open training pipelines and open data are the only aspects that could still use improvements in ML, but there are plenty of projects that are near-SOTA and fully open.
ML is extremely open compared to consumer mobile or desktop apps that are always ~10 years behind SOTA
I feel like it’s really far from being open. Besides the training data not being open, the more popular ones like llama and stable diffusion have these weird source available licenses with anti-competitive clauses, user count limits, or arbitrary morality clauses.