Intended tone was humorous, as in the ‘you guys have [X]s?’ meme, not to deny that Russia has such executives, although I haven’t seen anything notable from Sberbank. I’ve certainly kept an eye on Mistral and SSI if no one else.
However right now I think I’d list at least 5 American labs and 4 Chinese labs as substantially ahead of anyone anywhere else until proven otherwise, excluding SSI which is impossible to get a read on.
:-) Yes, well, Kandinsky AI series of text-to-image and text-to-video models is made by the Sber AI team (that’s Sberbank) :-) When bloggers from Russia generate AI visual art, that’s what they usually use :-) I don’t keep close track on them, but I see that they have progressed to Kandinsky 4.0 a year ago which is supposed to generate all multimedia, “New multimedia generation model for video in HD resolution and audio”...
There are a lot of small places which are difficult to keep track of (e.g. the most adventurous part of Liquid AI has recently split and formed Radical Numerics, whose approach is declared to be to “unlock recursive self-improvement”; their work in neural architecture search done while at Liquid AI has been pretty remarkable and more than just theoretical, so I understand why they want to make a straight play at recursive self-improvement, although I doubt they are giving enough thought on how to handle “true success”, which is unfortunate to say the least (they presumably still expect saturation of self-improvement, just at notably higher levels, and so they might not expect to encounter “true danger” soon)).
The better the coding models are, the more possibilities are there for small players with non-standard algorithmic ideas and desire for semi-automation of AI research, so the situation is becoming more fluid...
Intended tone was humorous, as in the ‘you guys have [X]s?’ meme, not to deny that Russia has such executives, although I haven’t seen anything notable from Sberbank. I’ve certainly kept an eye on Mistral and SSI if no one else.
However right now I think I’d list at least 5 American labs and 4 Chinese labs as substantially ahead of anyone anywhere else until proven otherwise, excluding SSI which is impossible to get a read on.
:-) Yes, well, Kandinsky AI series of text-to-image and text-to-video models is made by the Sber AI team (that’s Sberbank) :-) When bloggers from Russia generate AI visual art, that’s what they usually use :-) I don’t keep close track on them, but I see that they have progressed to Kandinsky 4.0 a year ago which is supposed to generate all multimedia, “New multimedia generation model for video in HD resolution and audio”...
EDIT: Ah, they just released a series of 5.0 models: https://arxiv.org/abs/2511.14993 and https://github.com/kandinskylab/kandinsky-5. So one can check where they are.
There are a lot of small places which are difficult to keep track of (e.g. the most adventurous part of Liquid AI has recently split and formed Radical Numerics, whose approach is declared to be to “unlock recursive self-improvement”; their work in neural architecture search done while at Liquid AI has been pretty remarkable and more than just theoretical, so I understand why they want to make a straight play at recursive self-improvement, although I doubt they are giving enough thought on how to handle “true success”, which is unfortunate to say the least (they presumably still expect saturation of self-improvement, just at notably higher levels, and so they might not expect to encounter “true danger” soon)).
The better the coding models are, the more possibilities are there for small players with non-standard algorithmic ideas and desire for semi-automation of AI research, so the situation is becoming more fluid...