Automated Design of Agentic Systems with Shengran Hu - #700
2024-09-02 · 60 min · episode 700 · 13 entities
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→ appeared on The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence podcast0.68
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Automated Design of Agentic Systems with Shengran Hu - #700
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Automated Design of Agentic Systems with Shengran Hu - #700
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evidence rules-v4
Feed author/publisher: Sam Charrington
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evidence rules-v4
Feed author/publisher: Sam Charrington
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appeared on The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence podcast0.68
evidence rules-v4
Automated Design of Agentic Systems with Shengran Hu - #700
Episode description as stored
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.