Comment by havdvdbd on johnswentworth's Shortform · 2024-11-17T06:13:47.357Z · LW · GW

Transpiling assembly code written for one OS/kernel to assembly code for another OS/kernel while taking advantage the full speed of the processor, is a completely different task from transpiling say, java code into python.

Also, the hardware/software abstraction might break. A python developer can say hardware failures are not my problem. An assembly developer working at an AGI lab needs to consider hardware failures as lost wallclock time in their company’s race to AGI, and will try to write code so that hardware failures don’t cause the company to lose time.

GPT4 definitely can’t do this type of work and I’ll bet a lot of money GPT5 can’t do it either. ASI can do it but there’s bigger considerations than whether Nvidia makes money there, such as whether we’re still alive and whether markets and democracy continue to exist. Making a guess of N for which GPT-N can get this done requires evaluating how hard of a software task this actually is, and your comment contains no discussion of this. 

Have you looked at tinygrad’s codebase or spoken to George Hotz about this?