Keep pulling the thread on Mark Zuckerberg, Priscilla Chan, and Alex Rives.
The Chan Zuckerberg Initiative was founded with the goal to build tools to help cure, prevent, and manage all diseases by the end of the century.
Protein language models trained by the Chan Zuckerberg Initiative can learn biological structure and function as an emergent property from token prediction training tasks on protein sequences.
The Chan Zuckerberg Initiative believes it will have a bigger impact by releasing its AI models and tools as open-source projects to the scientific community rather than commercializing them.
The Chan Zuckerberg Initiative's new ESMFold is an open system and world model for protein biology based on a language model trained on billions of protein sequences.
The ESMFold model has folded over 1.1 billion proteins and predicted their structures.
The ESMFold model is achieving state-of-the-art performance across structure prediction benchmarks, particularly for protein-protein and protein-antibody interactions.
Using the ESMFold model, researchers were able to digitally design and then experimentally validate nanomolar binders, a level of activity relevant for therapeutics.
The Chan Zuckerberg Initiative believes its unique advantage is combining a frontier AI research effort with a frontier biology effort, which other major AI labs do not have.
The next major research challenge for the Chan Zuckerberg Initiative is to build a "virtual cell" model that connects the proteomic, genetic, and transcriptomic layers to phenotype.
In the last year, the Chan Zuckerberg Initiative has formalized that Biohub is the main focus of its philanthropy.
Mark Zuckerberg now believes that the goal of curing all diseases by the end of the century, which was once considered a stretch, is now too conservative.
The Chan Zuckerberg Initiative's Biohub has expanded from its original San Francisco location to include hubs in New York and Chicago.