Episode

Automated Design of Agentic Systems with Shengran Hu - #700

Podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Published
Sep 2, 2024
Duration seconds
3570
Processing state
failed
Canonical source
https://twimlai.com/podcast/twimlai/automated-design-of-agentic-systems/
Audio
https://pscrb.fm/rss/p/traffic.megaphone.fm/MLN6045931233.mp3?updated=1725394223
JSON
/v1/public/podcasts/twiml-ai-podcast/episodes/automated-design-of-agentic-systems-with-shengran-hu-700
Markdown
/podcast/twiml-ai-podcast/automated-design-of-agentic-systems-with-shengran-hu-700.md

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Summary

Today, we're joined by Shengran Hu, a PhD student at the University of British Columbia, to discuss Automated Design of Agentic Systems (ADAS), an approach focused on automatically creating agentic system designs. We explore the spectrum of agentic behaviors, the motivation for learning all aspects of agentic system design, the key components of the ADAS approach, and how it uses LLMs to design novel agent architectures in code. We also cover the iterative process of ADAS, its potential to shed light on the behavior of foundation models, the higher-level meta-behaviors that emerge in agentic systems, and how ADAS uncovers novel design patterns through emergent behaviors, particularly in complex tasks like the ARC challenge. Finally, we touch on the practical applications of ADAS and its potential use in system optimization for real-world tasks. The complete show notes for this episode can be found at https://twimlai.com/go/700.