Intelligence + Continual Learning = Expertise — Yu Su, NeoCognition
Aug 12, 2026 · 19:43
Yu Su, professor at Ohio State and CEO of NeoCognition, argues that the AI field conflates intelligence with expertise, and that scaling raw intelligence alone yields the 'world's smartest novice'—brilliant at isolated problems but accumulating nothing between them. He explains why coding agents succeed while other digital work remains brittle: code is a language-native, symbolic world with tests as rewards, whereas modern society is 'millions of micro worlds' with idiosyncratic local physics too heterogeneous for a static model to compress. Expertise, he contends, is accumulated, situated competence that compresses search space through learned shortcuts, and continual learning—defined as 'adaptive compression of experience into reusable structures'—is the bridge from intelligence to expertise. He presents a figure plotting raw intelligence against expertise as largely orthogonal, and proposes the goal of 'unbounded expertise from bounded intelligence': once intelligence crosses a…
