Mark Zuckerberg has shown up at the homes of OpenAI researchers with homemade soup as part of Meta's aggressive recruitment campaign, reported Fortune.
Mark Chen holds the position of chief research officer at OpenAI and discussed this odd recruitment approach during a podcast interview.
He said Meta approached 50% of the people reporting directly to him with offers supported by a $10 billion fund dedicated to talent acquisition. The personal soup deliveries from Zuckerberg added an unexpected twist to these recruitment efforts.
"It was shocking to me at the time," Chen said about the hand-delivered meals.
The competition for AI talent has grown fierce between the two companies. Only a small group of experts around the world can build sophisticated language models independently. Estimates from people in the field put this group at under 1,000 individuals.
This limited pool of experts has driven compensation packages to extreme levels, including contracts worth nine figures.
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Chen admitted he now uses similar tactics, though he orders from a premium Korean restaurant called Daeho rather than cooking himself. He's also planning a group cooking activity for people he wants to recruit.
This battle for talent comes at a time when AI data centers consume massive amounts of energy. Training large language models requires enormous computing power, which translates into electricity use and carbon output. The race to build stronger AI systems means more data centers, more energy demand, and more strain on electrical grids.
Companies building these systems need the small group of researchers with the right expertise. Meta has spent billions trying to attract this talent away from competitors. OpenAI has worked to keep its team intact despite the financial pressure.
Chen said many of his team members rejected Meta's offers because they believe OpenAI will reach artificial general intelligence first. He disputed reports suggesting Meta has successfully recruited large numbers of OpenAI staff.
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As these companies expand their AI operations, they're also expanding their environmental footprint. Each new hire working on more powerful models means more energy consumption, and increased energy consumption has many side effects, such as straining grids, increasing utility prices, and adding more pollution to the atmosphere, which in turn traps more heat.
AI models sometimes solve environmental challenges, but unless they can also solve their own contribution to pollution, concerns about the collateral damage from AI's version of the "space race" will continue to loom large.
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