Thinking Machines Lab Co-Founder Andrew Tulloch Joins Meta

Oct 12, 2025
Andrew Tulloch, co-founder of Mira Murati’s AI startup Thinking Machines Lab, has left the company to join Meta. The move follows earlier reports of Meta’s efforts to recruit top AI talent from the startup.

Andrew Tulloch, co-founder of Mira Murati’s AI startup Thinking Machines Lab, has left the company to join Meta. Tulloch informed employees of his departure in a message on Friday. A company spokesperson confirmed the news, stating that he chose to pursue a different path for personal reasons.

Tulloch previously worked at Meta for over a decade before joining OpenAI and later co-founding Thinking Machines Lab earlier this year. His move marks another high-profile addition to Meta’s growing AI research division.

Meta has been actively recruiting AI researchers and engineers in recent months, reportedly offering substantial compensation packages to attract top talent. Earlier reports indicated that Meta had approached Thinking Machines Lab with an acquisition offer that was declined.

A spokesperson for Thinking Machines Lab said Tulloch’s contributions were instrumental in shaping the startup’s early progress and that the company remains committed to advancing its AI initiatives.

We hope you enjoyed this article

Consider subscribing to one of our newsletters like Enterprise AI Brief or Daily AI Brief.

Also, consider following us on social media:

Enterprise AI AI Brief AI Brief (X)
Free newsletter

Enterprise AI Brief

Weekly report on AI business applications, enterprise software releases, automation tools, and industry implementations.

AI Token Webinar

Whitepaper

Tensordyne Napier: What If One Rack Could Do the Work of Nine?

Tensordyne

This Tensordyne whitepaper presents Napier, an inference-focused AI processor and rack-scale system based on the company’s TDN Math logarithmic number system. It examines infrastructure requirements for large mixture-of-experts and agentic models, compares major inference architecture approaches, and details the TDN AIP processor, TDN72 pod, TDN Link fabric, and Napier Ultra configuration. The paper reports simulation-based performance, cost, and accuracy-validation results, including Tensordyne’s projected comparison of one Napier rack with a nine-rack Nvidia Rubin plus Groq deployment; the chip is reported as taped out and in fabrication.

Read more

You may also like

Free, six days a week

Daily AI Brief: the AI news that matters, in your inbox.