1) reasoning capabilities in latest models are rapidly approaching superhuman levels and continue to scale with compute.

2) intelligence at a certain level is easier to achieve algorithmically when the hardware improves. There's also a larger path to intelligence and often simpler mechanisms

3) most current generation reasoning AI models leverage test time compute and RL in training--both of which can make use of more compute readily. For example RL on coding against compilers proofs against verifiers.

All of this points to compute now being basically the only bottleneck to massively superhuman AIs in domains like math and coding--rest no comment (idk what superhuman is in a domain with no objective evals)