Jebus, that is some sloppy prose. Can people not even be bothered to write the summary themselves, anymore? AI doesn't want anything, so they can never have a point of view, so their prose rambles incoherently across all the various prompts they've seen in a project. This project sounds like the ramblings of a crazy person. Even though the fact that DRAM can do any computation is interesting, nobody should have to read this mess.
"why are we still transferring data to the compute? Why not execute AI inference natively within the memory?"
You already answered that question: 47.5 seconds per token from a tiny 2B 1-bit model model.
Jebus, that is some sloppy prose. Can people not even be bothered to write the summary themselves, anymore? AI doesn't want anything, so they can never have a point of view, so their prose rambles incoherently across all the various prompts they've seen in a project. This project sounds like the ramblings of a crazy person. Even though the fact that DRAM can do any computation is interesting, nobody should have to read this mess.
"why are we still transferring data to the compute? Why not execute AI inference natively within the memory?"
You already answered that question: 47.5 seconds per token from a tiny 2B 1-bit model model.
Very interesting. Do you have any descriptions or writeups written by a human?
Very interesting. I don't see it mentioned so I'll ask:
Would being able to alter voltage levels on the fly (eg, cells x y and z get 1.25 while abc get 1.2) expand the ability here?
You are saying this is 13 times faster? More proof please. How do we set it up? I really want this to be a real thing.
Interesting project, but the slop readme made me quit reading halfway