Most AI progress still happens by training a model from scratch.
This research points at a stranger path: ask a model to inspect another model’s raw weights and directly repair a weakness.
It is early, and the results need replication. But if it holds up, improving a model may start to look less like building a factory and more like debugging software. rikiyat.github.io/blog/weight-sp…
This research points at a stranger path: ask a model to inspect another model’s raw weights and directly repair a weakness.
It is early, and the results need replication. But if it holds up, improving a model may start to look less like building a factory and more like debugging software. rikiyat.github.io/blog/weight-sp…
rikiyat.github.io Sparks of Weight-Space Programming: LLMs can natively read & write neural network weights We find that frontier LLMs are surprisingly good at natively reading and writing neural network weights, using a variety of recent tools and algorithms or even via direct weight editing. 
