Basically - "any model trained with ~28M H100 hours, which is around $50M USD or - any cluster with 10^20 FLOPs, which is around 50,000 H100s, which only two companies currently have " - hat-tip to nearcyan on Twitter for this calculation.
Specific language below.
" (i) any model that was trained using a quantity of computing power greater than 1026 integer or floating-point operations, or using primarily biological sequence data and using a quantity of computing power greater than 1023 integer or floating-point operations; and
(ii) any computing cluster that has a set of machines physically co-located in a single datacenter, transitively connected by data center networking of over 100 Gbit/s, and having a theoretical maximum computing capacity of 1020 integer or floating-point operations per second for training AI."
Ok, as a baseline for everyone who, like me, doesn’t understand all the big words and numbers on why this is great news:
So, if I’m understanding correctly, one of our most powerful open source models is so far from this benchmark that it can’t even been seen.
Someone please correct me if I’m wrong.
They must be prepping the field for tomorrow rather than trying to introduce immediate trust market conditions.