Keep pulling the thread on Mark Zuckerberg & Priscilla Chan.
The Chan Zuckerberg Initiative established a goal to cure, prevent, and manage all diseases by the end of the 21st century.
A key strategy for the Chan Zuckerberg Initiative is to produce specific biological datasets for the purpose of training AI models to build virtual cells.
After 10 years of operation, the Chan Zuckerberg Initiative has determined its science research investments yielded the highest returns, making the Biohub the main focus of its philanthropy.
The Chan Zuckerberg Initiative directly funded only 25% of the data in the Cell by Gene atlas; the remaining 75% was contributed by the broader scientific community.
Alex Rives, the leader of Evolutionary Scale and a former Meta protein folding researcher, is joining the Chan Zuckerberg Biohub to lead its entire science program.
The Chan Zuckerberg Initiative is developing what it believes to be the first AI reasoning model for biology, designed to explain causal mechanisms rather than just correlations.
The Chan Zuckerberg Initiative's strategy for building complex biological simulations is hierarchical: first build a state-of-the-art protein model, integrate it into a cellular model, and then use that to build systems-level models like a virtual immune system.
The Chan Zuckerberg Initiative was one of the first organizations in its field to build a large-scale compute cluster for biological research, starting with 1,000 GPUs.
The Chan Zuckerberg Initiative plans to expand its compute cluster to the 10,000 GPU range.
As of 2025, biology lacks a foundational, standardized reference equivalent to chemistry's periodic table of elements, which was an inspiration for the Chan Zuckerberg Initiative's Cell Atlas project.
The Chan Zuckerberg Initiative's Cell by Gene platform was originally created as an internal tool to solve a bottleneck in annotating single-cell data.
DeepMind's AlphaFold model was trained on a public dataset of protein structures that was produced decades ago.