Thomas Sohmers, co-founder of Positron AI, argues that four decades of computing hardware development over-indexed on raw FLOPS instead of memory bandwidth scaling.
Opinion
Sohmers: Hardening silicon for specific AI models is obsolete in months
“Doing any of that, like, hardening for specific Model things. I don't think lasts more than, you know, two or three months at the rate that the industry moves at.”
Insight
Sohmers: AI hardware over-indexes on raw FLOPS instead of memory bandwidth
“Everyone else was focusing on the wrong things. They were just trying to have more and more flops when memory bandwidth, memory capacity were the real, real bottlenecks.”
Prediction Didn’t hold up
Sohmers: NVIDIA Blackwell memory bandwidth efficiency will be lower than Hopper
“All indications are, even though they, you know, more than doubled the theoretical memory bandwidth going from Hopper to Blackwell, the actual percentage of theoretical that you can achieve is, again, going to be less than the previous generation”
Assertion Open · timeframe Aug 2026
Sohmers: Positron hardware achieves 70% higher performance than NVIDIA at lower power
“So, you know, what that actually results in is like today, we're you know, able to achieve about you know, 70% higher performance than NVIDIA with the cards that we're shipping today. Significantly lower power and price point.”
Insight
Sohmers: Requiring workload recompilation creates fatal friction for AI chip adoption
“If you are requiring a user or having yourself as the company needing to actually recompile a workload, that's already one step too far, even if you assume it works perfectly.”
Assertion Supported
Sohmers: Positron AI requires zero compilers to run Hugging Face models
“So rather than having like, we don't have a compiler whatsoever. There's no compiler. There's no translator, no tooling that's involved in actually taking those and getting that to, you know, for your common, you know, Huggy Face Transform models to be able to…”