Comments by "Mikko Rantalainen" (@MikkoRantalainen) on "This New Stanford AI Chip is a Game-Changer! 🔥" video.

It currently seems that training the network is much harder problem than the inference and if this new chip can do that with less energy, great. However, it seems that the chip area required is pretty big so I would guess this doesn't yet make sense economically.
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@thomasmaiden3356 Yes, for currently existing systems that's unfortunately the case. For an AGI, that's not good enough. And if you are designing and planning to build new chips for AI systems, you should be shooting for AGI level performance already.
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@Johnithinuioian I'd define AGI as an AI system that can learn on the field and has no difference between learning and inference parts. We don't have any such systems currently. And we don't yet have a clear idea how to create one because our existing AI technologies do not even try to implement that part. But we know for sure that there are no learning and inference phases for human brain but both systems are concurrently running so if we want something equally adaptive, we need an artificial system emulating that part, too.
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