It’s not reasoning, the hardware demo uses a 3.-something generation Llama 8B.
But it’s proven they can automate this (they didn’t etch eight billion weights by hand after all, obviously), so now the interesting question is whether they can scale it to more recent aka bigger models.
After all, there’s already very useful models even for productivity at 27 or 35B.
It's not really "instant", i.e. the text is still generated token-by-token, it's just super fast. Reasoning would work with this model without any changes to the chip but it's disabled for speed.
It’s not reasoning, the hardware demo uses a 3.-something generation Llama 8B.
But it’s proven they can automate this (they didn’t etch eight billion weights by hand after all, obviously), so now the interesting question is whether they can scale it to more recent aka bigger models.
After all, there’s already very useful models even for productivity at 27 or 35B.
My concern is that reasoning could involve some sequential steps that instant models don't.
Not sure if modern models "think" only by outputting <thinking> blocks, or there is a more complex mechanism at play.
It's not really "instant", i.e. the text is still generated token-by-token, it's just super fast. Reasoning would work with this model without any changes to the chip but it's disabled for speed.