it's deeply problematic because they are building on open, public results yet they don't provide information on how people may build on it - its exploitative and exclusionary - at least they are consistent

But to me it also signals (as if it didn't before!) a great need for the wider AI community to focus exclusively on researching and building AI algorithms and systems that are more humanistic: completely transparent in its workings and the representations they create, super efficient in terms of data and compute, componentised so that individual entities can plug in different bits and rapidly train on their own data, highly adaptive to individual needs, programmable in a real sense, largely independent of corporate influence, easily accessible to everyone across all social and economic strata, and enable individuals to grow/learn/reach their full potential.

Is this possible? I think so, but it will require ingenuity and bringing in ideas from (ironically enough) some of the deepest areas of modern mathematics such category theory, algebraic topology etc. which are largely about building abstractions that expose the underlying structure of complex mathematical objects and the relationships between them.

It's already happening to a degree, but the urgency has reached epic levels at this point and it needs to happen at scale.