Microsoft Discovery is designed for science, utilizing a graph-based knowledge engine to understand nuanced scientific knowledge and facilitate research and development.

The iterative process in Microsoft Discovery allows agents to generate hypotheses and run experiments, significantly reducing the time required for scientific discoveries.

Quantum-enabled discovery could revolutionize fields like drug discovery by allowing quantum computers to predict molecular behaviors, significantly speeding up the process of synthesizing complex molecules without relying on trial and error.

Microsoft aims to create an agentic web where tools like Microsoft 365 Copilot and Foundry work together seamlessly.

The ambition at Isomorphic Labs is to develop a drug design engine that can continuously adapt and apply to new challenges across different diseases, fundamentally changing drug discovery.

We successfully synthesized a promising candidate for an immersion coolant that does not rely on harmful chemicals, demonstrating the potential of Microsoft Discovery across various domains.

Microsoft aims to create technology that not only achieves technical milestones but also addresses societal challenges, including healthcare and education.

Closed scientific robotic and AI systems are enabling hyper-acceleration in scientific discoveries by allowing AI to propose and run experiments autonomously.

The promise of AI in drug discovery lies not just in predictive power but in the ability to simulate experiments in a parallelized fashion, which could significantly reduce the time and cost involved in traditional methods.