🤖 AI Summary
Mark Zuckerberg and Priscilla Chan announced that the Chan Zuckerberg Initiative (CZI) is doubling down on "AI-powered biology" by prioritizing compute over traditional lab space and head count. Speaking about their Biohub investment, they said researchers prefer access to GPUs more than more employees or benches, and CZI plans to scale its cluster from about 1,000 GPUs today to roughly 10,000 GPUs by 2028. Biohub is also partnering with EvolutionaryScale and CZI is centralizing AI capabilities with a growing AI team and several related job openings, including senior AI infrastructure roles.
The move underscores a broader shift in how biomedical research is resourced: GPUs are being treated as the new currency of modern labs because large models and data-intensive workflows are central to discovery. That has practical implications—compute is often costlier than wet lab space, it attracts talent via tooling and access rather than Big Tech salaries, and it enables networked research models across multiple sites. For the AI/ML community this signals increased funding and demand for scalable GPU infrastructure, MLOps, and domain-specific model engineering in biology, and could accelerate translation of ML-driven insights into disease research and therapeutics.
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