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Meta seeks to supercharge its AI prowess by courting Nat Friedman and Daniel Gross, who could inject fresh ideas and deep industry knowledge into the social media giant's innovation efforts.
Meta Platforms Inc. is reportedly in talks to expand its artificial intelligence (AI) team by bringing on former GitHub CEO Nat Friedman and his venture capital partner, Daniel Gross. According to sources cited by The Information, the discussions also include a potential stake purchase in their investment firm, NFDG, which has backed several notable AI startups.
Nat Friedman is no stranger to the tech industry. After Microsoft acquired GitHub for $7.5 billion in June 2018, Friedman took over as CEO in October 2019. During his tenure, he played a pivotal role in transforming GitHub into a leader in AI-driven developer tools. One of his most significant contributions was the launch of GitHub Copilot, an early and highly successful coding assistant that leverages generative AI to complete lines of code and provide programming suggestions.
Friedman left GitHub in November 2021 to focus on investments at NFDG, where he continues to support and mentor AI startups.
Daniel Gross co-founded Cue, a personal assistant app, which was acquired by Apple Inc. for about $50 million in 2013. At Apple, he worked on various AI projects before leaving to co-found Safe Superintelligence, a developer tooling startup.

NFDG, co-founded by Friedman and Gross, has been instrumental in backing several promising AI startups. By potentially acquiring a stake in this venture capital firm, Meta could gain access to a pipeline of innovative technologies and talent.
Bringing in Friedman and Gross could significantly enhance Meta's AI research efforts. Here are a few potential areas of impact:
Meta's interest in Nat Friedman and Daniel Gross underscores its commitment to advancing AI technology. By combining their expertise with Meta's resources, the company could make significant strides in developing cutting-edge AI solutions and maintaining a competitive edge in the tech industry.
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About the author
Kai built ML infrastructure at a Bay Area startup before developing an obsession with transformer architectures and inference optimisation that eventually pulled him out of product work entirely. A stint at a compute research lab sharpened his instinct for what actually matters in a model release versus what is marketing. He writes from the inside — from the perspective of someone who has debugged the systems he is describing at three in the morning. He is allergic to hype and instinctively drawn to the unglamorous plumbing questions that everyone else skips over.
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19 June 2025
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