Stefania Druga

This talk introduces the concept of an AI co-scientist, analogous to a pair programmer but for real-world scientific experiments. The system integrates various sensors and cameras to collect empirical data in real-time, which an AI then analyzes to provide insights, generate hypotheses, and potentially accelerate scientific discovery. The presented system is built using open-source hardware and software, demonstrating a low-cost, accessible approach to AI-assisted experimentation.

This talk explores how open-source multimodal agents can enhance learning and creativity. These agents are proactive, nudging users to explore diverse topics and approaches, while also identifying potential cognitive biases and misconceptions. Examples are provided in math and science learning, demonstrating how these agents can support or challenge existing understanding.