Microsoft Discovery aims to revolutionize the scientific process by applying advanced agents for research and development, enabling continuous iterative cycles for generating and validating hypotheses.

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

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.

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.

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.

In science, significant discoveries often arise from chance or hard work, emphasizing the importance of time spent in the lab.

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.

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

Building a culture of experimentation makes product management scientific, allowing you to validate ideas quickly.