Nice. I couldn't find the part that I'm most interested in though, latency. This beats their frontier vision model for some identification tasks -- for a robotics model, I'm interested in hz. Since this is an "Embodied Reasoning" model, I'm assuming it's fairly slow - it's designed to match with on-robot faster cycle models.

Anyway, cool.

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WarmWash 8 hours ago | parent [-]

In my quick image recognition testing on AI studio, it's performance seems similar to 3.1 pro, but is much much faster. It "thinks" but only for a few seconds.

Of course this is for counting animal legs while giving coordinates and reading analog clocks. Not coding or or solving puzzles. I imagine the image performance to model weight of this model is very high.

	▲	vessenes 7 hours ago \| parent [-]
		I thought the entire discourse on how important pointing is to be super interesting. I've been told, although I don't know if this is true, that dogs are the only animal that can understand human pointing. Fascinating to think this might be fundamental to world intelligence requirements. Well, it's required, but it's interesting to think that it might be a core structure required or that learning it might force some sort of neural architecture that's helpful. And, I was disappointed to see that pointing was just giving x,y coords. I wanted to see robots pointing at stuff.