Conveners
Generative and Agentic AI II
- Yuewei Lin (Brookhaven National Laboratory)
This talk highlights Emergence AI's progress in three interconnected areas: agents-creating-agents (ACA), agentic memory, and self-improvement. Our ACA work builds autonomous multi-agent systems by having orchestrators that can plan, code, and spawn new agents to tackle complex workflows to analyze both structured and unstructured data at scale. In agentic memory, we've developed architectures...
Large language models have revolutionized artificial intelligence by enabling large, generalizable models trained through self-supervision. This paradigm has inspired the development of scientific foundation models (FMs). However, applying this capability to experimental particle physics is challenging due to the sparse, spatially distributed nature of detector data, which differs dramatically...
