Why Hasn't One AI Lab Run Away With the Lead?

John Collison recalls the 2023 story that one AI lab would get ahead, start recursive self-improvement, and pull away from everyone else. He says that has not happened. Several labs are still at the frontier, Muse Wonder is arriving as Meta's frontier-class model, and open-source models have kept up.

Alexandr Wang gives three reasons. Execution moves around. Every frontier lab has strong stretches and weak ones, and those average out. If a lab in the lead had executed perfectly the whole time, he thinks it would probably have stayed ahead. Distillation is the second reason. He calls it an anti-hegemonic force in the technology, not a plan anyone chose. It packs strong capability into smaller models, so really small models today are much more powerful than the biggest models a year or two ago. The third is that many people, and many companies putting money behind this, do not want one final company.