That’s great new!

The real question is, do current training methods allow one to learn this when training on enough, say, assembly, or can the weights only be achieved via hard-coding?

A fun and important thought experiment about the the space of nerual networks vs the image of current training methods.

Most discourse conflates neural networks and trainable neural networks.

No, I don’t want you to use the computer, I want you to be the whole computer. No mistakes.

Wow! I wonder if it can start programming itself soon.

This is cool but it'd be way more useful if they had made a GPU, seeing as how expensive those have gotten

It could be interesting to experiment with more complex representations in the memory/file system, i.e. vectors. Seems like the full advantage of this architecture is yet to be explored. Blending neurons with deterministic compute to fit on one GPU is a fascination concept, never considered it before!

I 100% see the potential here and am dying to see it in 30 days

Or maybe ill join your discord and hopefully we can riff it out to get there faster

i wonder if you could implement "authenticated token authorship" and self-verified running with this. the model verifies an input as signed by an authorized requester, and signs its own outputs. eventually it also authenticates its own running via e.g. snarks? :) there's lots of meta available with these toys..

This is cool and I understand the RAM emulation with gated attention but how does the CPU emulation wor? You add layers that are then trained to predict outputs while interpreting RISC instructions?

How much VRAM do I need to run DOOM?