Keynote: AI, Quantum, and AI + Quantum
summary
Generative AI already proposes molecule candidates and replaces some HPC simulations, and a production synthesis automation service connects model predictions to lab robotics; the community reports close to half a million registered users and roughly 4 billion API executions a day. A Python-first open source stack (kkit) exposes quantum circuits in familiar abstractions, while quantum hardware aims at useful-scale in a 5–10 year horizon. Key constraints are curated data, massive compute, reproducible ops, and modular model architectures.
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chapters (6)
- 0:00Introduction and background
- 1:25AI in accelerating science
- 7:41Quantum computing fundamentals
- 13:17Open-source AI challenges
- 17:56Addressing existential risks
- 19:51Q&A session
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