Why New AI Labs Struggle to Compete for Talent

There are several reasons why new AI labs, despite impressive funding rounds, find it difficult to retain top researchers:

Compensation limitations: These startups often cannot offer the same high salaries—sometimes reaching seven figures—as large tech companies like Meta, Google DeepMind, and OpenAI.
Equity versus cash: While early employees may receive equity stakes with potentially high future value, this is often less attractive than immediate, substantial cash payouts at big firms.
Stock option risk: Equity in young private companies is generally riskier than stock options in public companies or established labs. For example, Google and Meta offer generous stock packages with fast vesting, allowing employees to cash out more quickly. OpenAI and Anthropic are also considering IPOs, which could provide employees with large payouts in the near future—less likely for new startups.
A former OpenAI researcher, who maintains contacts with Thinking Machines employees, suggested that the main reason for recent departures was financial incentives, as some employees were lured back to OpenAI with highly lucrative offers. This person also expressed the view that Simo’s recruiting efforts might have been aimed at complicating investment in Thinking Machines, as investors tend to be wary of the departure of founding team members.