In just three years, the nascent company Mercor has emerged as a significant player, now valued at $10 billion, by facilitating connections in the competitive AI data landscape. The company acts as an intermediary, linking leading AI research institutions such as OpenAI and Anthropic with former professionals from prestigious firms like Goldman Sachs, McKinsey, and top-tier law offices. These experts are compensated up to $200 per hour to lend their specialized knowledge, which is then used to refine AI models – systems that could eventually automate the very industries from which these experts hail.
This episode features a discussion with CEO Brendan Foody from this year’s Disrupt conference. Foody elaborates on why advanced AI labs necessitate highly skilled contractors rather than relying on crowdsourced talent, how challenges faced by Scale AI contributed to Mercor’s rapid expansion, and his conviction that the entire economic landscape will eventually revolve around training AI agents.
Tune into the full episode to discover more about:
- Foody’s path from offering AWS credit consultations in high school to heading a company valued at $10 billion.
- The pivotal role of the top 10-20% of contractors in driving most model enhancements, and Mercor’s methodology for identifying them.
- The ambiguous territory between individual employee expertise and confidential corporate information (and whether institutions like Goldman Sachs ought to be concerned).
- Foody’s perspective on how all forms of knowledge work are destined to become training data for AI agents.
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