Priscilla Chan's recruiting pitch? We can't pay as well as tech companies, but we've got GPUs
Priscilla Chan, Mark Zuckerberg's wife and the cofounder of the couple's philanthropic organization, the Chan Zuckerberg Initiative, spoke about the appeal of massive GPU clusters for biology researchers during a recent episode of Ashlee Vance's "Core Memory" podcast.
"The other thing researchers really care about is access to GPUs," she said. "You're not going to make the most of someone if you don't actually have the GPUs for them to work from."
Chan said, "We have that at CZI," adding that the organization has roughly 1,000 GPUs in its cluster, with plans to keep growing.
In short, Chan said the pitch is: "Come work with us because we're going to have the computing power to support the research that you want to do."
Another important factor is compensation, which she said is "obviously important," though she added that "we cannot compete with tech companies on this."
CZI has in recent years narrowed its mission to focus on its "next phase" with a "bolder, clearer identity as a science-first philanthropy." The change marks a strategic shift, as the organization previously also supported education and other causes.
"While CZI remains committed to our work in education and our local communities, we recognize that science is where our biggest investments and bets have been and will be made moving forward," Chan, a pediatrician by training, wrote in a memo to staff last year.
Zuckerberg made a similar point about the importance of GPUs in recruiting on a recent episode of The Information's TITV show. Meta is spending billions to build an AI division it calls Superintelligence Labs.
"Historically, when I was recruiting people to different parts of the company, people are like, 'Okay, what's my scope going to be?'" the Meta CEO said. "Here, people say, 'I want the fewest number of people reporting to me and the most GPUs.'"
Meta, of course, has significantly more GPUs than CZI. Zuckerberg has said the company will have 1.3 million GPUs for AI by the end of 2025.
"Having basically the most compute per researcher is definitely a strategic advantage, not just for doing the work but for attracting the best people," he said.
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