NVIDIA GTC
Using Agentic AI to Transform Science: From Molecules to Materials
Wednesday, March 18 | 3:00 p.m. – 3:40 p.m.
AI is accelerating breakthroughs across scientific domains, transforming complex data into actionable insights for discovery and design. This session explores how agentic AI systems are being engineered to drive innovation—from decoding biological mechanisms for therapeutic science to modeling quantum matter for next-generation materials.
Visionary thought leaders Eun-Ah Kim (Professor of Physics, Cornell University) and Marinka Zitnik (Associate Professor of Biomedical Informatics, Harvard Medical School) will share how their research teams are applying robust, domain-specific AI frameworks to reshape the future of their fields.
Key Takeaways:
- AI as a Hypothesis Generator: AI agents can move beyond pattern recognition to generate novel, testable hypotheses in complex biological systems.
- Teaching AI to “Think” Like a Physicist: Pioneering methods to instill the fundamental principles of physics into AI models, enabling them to analyze complex quantum data and identify previously hidden patterns in exotic materials.
- Power of Foundational Models in Science: Learn how large-scale, pre-trained AI models can be adapted to understand the intricate language of biology.
- From Data Overload to Insight: Learn how use of AI is solving a critical challenge: making sense of the enormous datasets generated by modern experimental techniques and facilities.
- A New Moore’s Law for Materials: The synergy between AI, data accumulated from generations of research, chemistry, and physics creates an exponential acceleration in materials discovery, heralding a new era of technological advancement driven by purpose-designed quantum materials.
More Information at: nvidia.com/gtc
