I am just wondering why not we are building new AI/ML to completely build silicone scheme from images of it ? I mean we can ptychography of any chipset. And there is many Open IP so AI can interpret the circuits.
As you know producing the chip not to much, we can accept to pay the engineering and advertising of them however monopoly of GPU/CPU is not acceptable.
Lets talk and create road map or trash this idea.
Backdoors such as Intel Management Engine are unacceptable. https://en.m.wikipedia.org/wiki/Intel_Management_Engine
Training models on higher resolution would become exponentially more expensive, while still not being that likely to succeed.
And even if you had the schematics, a foundry would still cost millions to setup, + you wouldn't even know if they were any good before trying them out, it would probably be an unpredictable black box.
Many part of the chip is actually replication of same compenent or library like DRAM, ROM, Arithmetic operations so always there should be a pattern. Scanning should also work from low resolution to high resolution part by part to find pattern.
And also foundry is not as much as you think, most of the cost is R&D not the production.
https://www.granitefirm.com/blog/us/2023/04/29/cost-of-chip-... https://www.tomshardware.com/news/tsmc-reportedly-adds-advan...
"60-ish A100/H100 GPUs per wafer" and 7nm Waffer cost is $10k
https://www.reddit.com/r/ECE/comments/7hjlpg/for_anyone_curi...
You are right for production, I was meaning for verification. MPW is around about 20-30k for 7nm.
In full production even with tapeout cost which is $15M for 7nm chipset cost $1500 per die after sell 10k. Best price for A100 is around $6k in monopoly now.
Even before production, after interpreting images, AI can also collect IP cores and produce new ones in the next steps.