Under the leadership of David Baker, the esteemed 2024 Nobel laureate in Chemistry and a distinguished professor at the University of Washington in the United States, a groundbreaking generative AI system named RFdiffusion3 (RFD3) has been developed. This cutting-edge system possesses the remarkable capability to design proteins and nucleic acids at the atomic level, achieving protein structure generation at a speed 10 times faster than its predecessor. As the pioneering all-atom diffusion model, RFD3 adeptly simulates all atoms within both the main and side chains of proteins, along with non-protein components that interact with them. Despite having a relatively modest 168 million parameters, its inference speed surpasses that of its forerunner by more than 10 times, while simultaneously reducing computational costs by a staggering 90%. The system excels in four key tasks: protein-protein binding, protein-DNA binding, protein-small molecule binding, and enzyme design. Its versatility makes it highly applicable across various domains, including antibody drug development, the creation of novel catalytic enzymes, the design of gene editing tools, and synthetic biology.