State of Data — Sean Cai, Independent / State of Data

GPT 5.5 and Opus 4.8 landed within three points on the same finance benchmark while failing in opposite directions. GPT got the arithmetic right. Opus got the methodology right. One leaderboard number flattened both failures into a single noisy sample, exactly what happens when benchmarks reward one scaffold and vendors sell the data used to climb the tests they designed. The scarce asset is no longer another isolated answer. It is process data: the reasoning trace, sequence of decisions, state changes, failures, recoveries, and verified outcomes that turn general competence into real expertise. Static datasets depreciate as models improve, so the durable moat is a live pipeline into real work plus the infrastructure to retrain when the base model changes. Speaker info: - https://x.com/SeanZCai - https://www.linkedin.com/in/sean-z-cai - https://www.seancai.com/philosophy/state_of_data_jan_2026 Timestamps: 0:00 - The data market nobody sees 1:15 - Data as industrial fuel 2:31 - Type one and type two data 3:23 - Compute, data, and talent 4:24 - State data versus process data 5:54 - The three axes of verifiability 8:14 - When benchmarks become snake oil 10:08 - Three finance benchmark tests 12:04 - Predicting the next AI domain 13:21 - The robotics counterexample 14:22 - Where the economic value lives 16:02 - Why data companies move enterprise 17:09 - The durable moat --- Watch along with the corrected transcript, summary, timestamps and resources on this talk's official AIE page: https://ai.engineer/talks/ZyIoTOAbRfs-state-of-data Join our upcoming AI Engineer conferences (see https://ai.engineer landing page): - AIE New York, October 12–14 — the first AI Engineer Finance mainstage summit - AIEi Shanghai, November 5–6 — the first for meeting top Chinese labs and engineers - AIE CODE in SF, November 10–12 — the top AI Coding conference returns - AIEi Sydney, December 7–8 — the first AIEi run alongside NeurIPS 2026 in Sydney ---