The Compute Game at Frontier Labs
naval · x · 2026-07-17
Naval shared a discussion regarding frontier AI labs, with the core takeaway being that new capabilities are harder to obtain than ever, and Chinese labs might have the upper hand when it comes to data and human expert costs.
Key points include:
- Processes like invoking teacher models, distillation, and data cleaning are typically cheaper than hiring human experts, meaning data providers (like Mercor and Scale) stand to benefit.
- Many labs keep their true frontier models internal, restricting direct access for hyperscalers or API users to prevent distillation or theft.
- The post also estimates that models available to the public are generally about 6 months behind the actual frontier.
Related event: Analysis: Chinese AI Labs Leverage Distillation to Compete(3 posts)→
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