AI is transforming biology into a fully integrated computational discipline, where discovery depends on the seamless interaction between models, compute infrastructure, and experimental systems. As foundation models for proteins, genomes, and cellular systems mature, the challenge is no longer prediction alone. It is building a unified stack that connects generative design, large-scale computation, and rapid experimental feedback into continuous learning loops. This session explores how the next generation of computational biology platforms is emerging at the intersection of cloud computing, GPU-accelerated modeling, advanced simulation, and high-throughput experimental infrastructure. Leaders across AI, biotech, and technology will discuss how tightly integrated design-build-test-learn cycles are reshaping therapeutic discovery, enabling adaptive model refinement, and accelerating the transition from in silico hypotheses to real-world biological outcomes.

As artificial intelligence and programmable biology rapidly converge, a new generation of companies, tools, and research paradigms is emerging across the life sciences. From AI-driven protein design and generative genomics to autonomous laboratories and foundation models for biology, the AIxBIO ecosystem is evolving at unprecedented speed. In this session, NVIDIA will present a high-level overview of the AIxBIO landscape, highlighting key technological breakthroughs, emerging categories of companies, and the infrastructure powering the next wave of biological discovery. The discussion will explore how advances in compute, data, and machine learning are reshaping how we design molecules, engineer cells, and accelerate drug and materials discovery. This talk will provide a strategic map of the field and help frame where the most important opportunities and bottlenecks lie as AI begins to fundamentally transform the practice of biology.