The Quiet Enabler: AI-Amplified Discovery

Multi-agent systems are quietly transforming scientific inquiry by orchestrating literature analysis, experiment design and data interpretation in parallel. This session outlines the system-level principles needed to successfully integrate AI in real research settings.

What You’ll Learn: - How multi-agent architectures coordinate scientific reasoning - Real-world examples of AI completing end-to-end discovery loops - How to structure your own pipelines for fast, reproducible iteration - The infrastructure traits that support high-tempo scientific workflows