Chamath says AI winners may come from private data, not better models
rohanpaul_ai · x · 2026-07-29
Chamath argues that AI advantage may come less from better models and more from unique private inputs.
- If multiple large labs train on the same public data, they can end up with very similar models.
- The real differentiator is a proprietary ingredient: private workflows, transaction data, medical records, industrial logs, legal archives, design files, or user behavior.
- As more of the web becomes unavailable or reserved for internal use, this “private data arms race” could make certain models meaningfully better.
- He also suggests the next wave of M&A may target companies not for revenue or brand, but for the data streams they can feed into AI systems.
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