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SpaceXAI Is Hemorrhaging Staff: Musk's AI Merger Is Taking Its Toll

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Over 50 researchers and engineers have left since SpaceX acquired xAI. Meta and Mira Murati's startup are the biggest beneficiaries.

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Elon Musk’s vision of an AI-space conglomerate is showing cracks: since SpaceX acquired xAI in February, more than 50 researchers and engineers have walked out the door. That’s according to The Information, with TechCrunch picking up the story on Wednesday.

Who’s leaving — and where they’re going

The departures are hitting SpaceXAI where it hurts. Key teams working on coding, world models, and Grok Voice have been affected. The pre-training team — the beating heart of any AI company — has reportedly shrunk to just a handful of people.

At least eleven former xAI employees have moved to Meta, and seven more joined Thinking Machines Lab, the startup founded by former OpenAI CTO Mira Murati. Out of roughly 200 researchers xAI had on staff, a significant portion is now gone.

Why they’re leaving

The merger changed the culture. SpaceX installed new leadership and rebranded the company. Add to that a work culture that was already considered extreme at xAI — and apparently hasn’t gotten any better under the SpaceX umbrella.

What this means

For Musk, this is a real problem. SpaceXAI is supposed to be his ace in the AI race, but you can’t build frontier models without experienced researchers. The competition is happy to help themselves: Meta is aggressively expanding its AI team, and Murati’s Thinking Machines Lab — freshly funded with $650 million — is actively poaching.

My take

This story practically writes itself. Musk merged xAI and SpaceX to unlock synergies and fully utilize the Colossus supercomputer. But synergies on paper don’t mean much when the people who train the models are heading for the exit.

It’s a pattern: Musk acquires, rebrands, installs new leadership — then seems surprised when the talent leaves. At Twitter, that worked out (sort of). In AI research, where every single senior researcher counts, it could become a serious problem.

Sources: TechCrunch · The AI Insider