Evolutionary Scale · ESM Cambrian: Revealing the mysteries of proteins with unsupervised learning

evolutionaryscale.ai · 1,629 words · saved by 1 readers

Today we’re introducing ESM Cambrian, a next generation language model trained on protein sequences at the scale of life on Earth. ESM C models define a new state of the art for protein representation learning. ‍ AI is beginning to unlock an era of digital biology where we can use computation to go beyond the limits of experiments in the physical world. The universe of protein function is so vast and complex that we lack the ability to fully characterize it experimentally, and for many applications, we need to engineer functions that go beyond those in nature. The physical limitations of performing experiments in the real world mean that unsupervised learning—algorithms that can learn from patterns in unlabeled data—is critical to unlocking the promise of digital biology. Discovering scalable techniques that can learn directly from protein sequences can illuminate biology at a level not yet possible with experimental characterization. ‍ ESM Cambrian is a parallel model family to our fl

Evolutionary Scale · ESM Cambrian: Revealing the mysteries of proteins with unsupervised learning By using this website, you agree to the storing of cookies on your device to analyze site usage. View our Privacy Policy for more information. Deny Accept Start working with ESM Use ESM3 December 4, 2024 // Announcement ESM Cambrian: Revealing the mysteries of proteins with unsupervised learning Start with ESM C on Github Provision on SageMaker Today we’re introducing ESM Cambrian, a next generation language model trained on protein sequences at the scale of life on Earth. ESM C models define a ne

Evolutionary Scale · ESM Cambrian: Revealing the mysteries of proteins with unsupervised learning

related reading