WSJ Spotlights Priscilla Chan’s Big Bet on Beating Disease—Here’s Why This AI‑Powered Science Push Matters for Mobile

AI Supercomputing, Biohubs, and Open Science: Priscilla Chan’s Big Bet to Outsmart Disease | Rule Mobile Newsroom
Priscilla Chan in a lab setting; Rule Mobile composite cover
Rule Mobile Newsroom

AI Supercomputing, Biohubs, and Open Science: Priscilla Chan’s Big Bet to Outsmart Disease

As the Chan Zuckerberg Initiative (CZI) hits its 10-year milestone, Rule Mobile reports on a rapidly maturing strategy to accelerate biomedicine: nonprofit AI compute at scale, a U.S. Biohub network, and open tools that let labs work with tens of millions of single-cell profiles. Here’s how this effort is changing the pace of discovery—and why connectivity matters.

NVIDIA logo Chan Zuckerberg Initiative logo WSJ logo

Key Takeaways

Nonprofit AI at Scale: CZI's DGX SuperPOD, armed with 1,024 NVIDIA H100 GPUs, provides a level of compute for scientific modeling that exceeds the capacity of most universities.
The Biohub Network: A $1B+ investment in long-term research, with institutes in SF, Chicago, and NY (funded at $250M–$600M each) dedicated to solving foundational biology.
Open-Access Tools: Platforms like CZ CELLxGENE democratize research by hosting standardized datasets of over 90 million cells, enabling rapid, large-scale analysis for any lab.

Why This Story Matters Now

Priscilla Chan, M.D., is drawing renewed attention to a decade-long plan to “outsmart disease” by pairing large-scale computation with rigorous, collaborative biology. While the recognition of Chan’s leadership in WSJ. Magazine’s Innovators issue is notable, the underlying story here is technical and measurable: purpose-built compute, funded institutes, and open infrastructure that researchers already use in daily work.

Our editorial view: this is less about speeches and more about systems—silicon, storage, standards, and sustained funding—built expressly for biology.

From Instagram

Priscilla Chan shared the recognition and the mission behind the work on social media. See the original post below:

The Technical Core: Nonprofit AI Supercomputing

CZI’s AI compute program makes unusually large resources available to nonprofit researchers: a DGX SuperPOD comprising 1,024 NVIDIA H100 GPUs paired with high-throughput storage, dedicated to training models that can learn from vast imaging and molecular datasets. The goal is to develop “virtual cells”—predictive models of cell state and behavior—that can shorten the path from mechanism to medicine.

NVIDIA H100 data center GPU—angled view
NVIDIA H100 accelerators power CZI’s nonprofit DGX SuperPOD for life-science AI. Image: NVIDIA.
H100 NVL with NVLink Bridge illustration
High-bandwidth interconnects matter for multi-GPU training on large biological datasets.
NVIDIA platform features icons

Institutes Built for Hard Problems: The Biohub Network

San Francisco Biohub (2016). Seeded with a $600 million commitment, the original hub links UCSF, Stanford, and UC Berkeley to prototype tools and foundational cell science.

Chicago Biohub (2023). Backed by $250 million over a decade (with additional Illinois support), the Chicago site focuses on inflammation biology across diseases.

New York Biohub (2023). A cell-health hub formed with CZI’s $250 million commitment and public contributions from New York State and City, aiming to engineer immune cells for early detection and intervention.

Open Tools Scientists Rely On

CZ CELLxGENE. A free data platform that standardizes and serves massive single-cell datasets to the community; recent peer-reviewed work documents the portal at 90M+ unique cells with schema enforcement that enables cross-study analysis.

Imaging & napari. CZI has funded multiple cycles to strengthen the napari ecosystem—plugins, docs, and usability—for quantitative bioimage analysis in Python. It’s pragmatic support that turns cutting-edge microscopy data into something shareable and reproducible.

Why This Intersects with Networks and Mobile

  • Edge→Cloud Movement. Sequencers and microscopes stream terabytes; reliable networks and modern transport protocols keep multi-site studies in lock-step.
  • Distributed Collaboration. Biohubs coordinate universities and hospitals; standardized data + secure connectivity let AI models update across sites.
  • Point-of-Care Decision Support. As virtual-cell models mature, clinical insights can surface on handhelds in clinics and at home—where latency, security, and availability matter.

In essence, CZI’s biological revolution runs on a data-intensive network revolution, from the lab's edge to the clinical cloud and the patient's device.

What Rule Mobile is Watching Next

  • Public model checkpoints and benchmarks emerging from the nonprofit H100 cluster.
  • Biohub publications in inflammation and cell-health with clear translational paths.
  • Growth in open, standardized datasets that enable cross-lab analysis straight from the browser or notebook.

Image Credits

Photography/art: NVIDIA product renders; CZI/Rule Mobile composite (lab cover). Brand marks are property of their respective owners.

References & Further Reading

  1. CZI AI computing program (1,024 H100 GPUs, DGX SuperPOD)
  2. Virtual Cells overview
  3. San Francisco Biohub: $600M commitment
  4. Chicago Biohub: $250M & Illinois support
  5. New York Biohub: CZI $250M + state/city contributions
  6. CZ CELLxGENE platform (Nucleic Acids Research, 2025)
  7. napari ecosystem grants (CZI Imaging)
  8. WSJ. Magazine Innovators profile
© 2025 Rule Mobile. All rights reserved. NVIDIA, the NVIDIA logo, and H100 are trademarks of NVIDIA Corporation. The Chan Zuckerberg name and marks are trademarks/service marks of the Chan Zuckerberg Initiative. WSJ and Wall Street Journal are trademarks of Dow Jones & Company. Used here for reporting and reference.
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