protein-design

Introduction The insight behind inference-time scaling is simple: generating one candidate and hoping it’s good is rarely optimal. A model with a fixed set of weights can produce dramatically better outputs if, at inference, you spend compute exploring the output space and selecting against a reward signal.

Introduction The intersection of artificial intelligence and molecular biology has witnessed a transformative breakthrough with the emergence of protein language models (PLMs). These sophisticated deep learning architectures have fundamentally altered our approach to understanding protein sequence-structure-function relationships, offering unprecedented capabilities in protein property prediction, design, and engineering.