If a dataset is so good, why release it? Data is the real differentiator
yenkel · x · 2026-10-01
yenkel offers a heuristic worth applying to every newly released dataset (benchmark or not): if the data were really that valuable, why would anyone publish it openly?
His argument: assuming constant compute, data is the differentiator. So a public high-quality dataset release should prompt skepticism — either the data isn't actually that good, or there's an unspoken motive behind sharing it.
Related event: Why Publicly Released Datasets Deserve Skepticism(2 posts)→
More from AGI Musings
- a16z partner: my 2016 wallet-platform thesis is finally happening, thanks to AI — arampell · 2026-10-01
- Researcher: new models solve old problems, but learning theory lacks predictive conjectures — brianryhuang · 2026-10-01
- David Sacks slams Bill Gates' claim AI could kill 1 billion people as 'made up numbers' — DavidSacks · 2026-10-01
- AI Now Institute's People's AI Assembly on Oct 19 adds NYT labor reporter Noam Scheiber to panel — AINowInstitute · 2026-10-01
- Investor: blacklist anyone still calling AI an illusion after Q1 2024 — pwlot · 2026-10-01
- AI rollups: the moat is legacy systems and tribal knowledge, not models — curious_vii · 2026-10-01