Today we’re joined by Kamyar Azizzadenesheli, a staff researcher at Nvidia, to continue our AI Trends 2024 series. In our conversation, Kamyar updates us on the latest developments in reinforcement learning (RL), and how the RL community is taking advantage of the abstract reasoning abilities of large language models (LLMs). Kamyar shares his insights on how LLMs are pushing RL performance forward in a variety of applications, such as ALOHA, a robot that can learn to fold clothes, and Voyager, an RL agent that uses GPT-4 to outperform prior systems at playing Minecraft. We also explore the progress being made in assessing and addressing the risks of RL-based decision-making in domains such as finance, healthcare, and agriculture. Finally, we discuss the future of deep reinforcement learning, Kamyar’s top predictions for the field, and how greater compute capabilities will be critical in achieving general intelligence.
The complete show notes for this episode can be found at twimlai.com/go/670.
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Responsible AI in the Generative Era with Michael Kearns - #662
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Data, Systems and ML for Visual Understanding with Cody Coleman - #660
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Mental Models for Advanced ChatGPT Prompting with Riley Goodside - #652
Multilingual LLMs and the Values Divide in AI with Sara Hooker - #651
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Pushing Back on AI Hype with Alex Hanna - #649
Personalization for Text-to-Image Generative AI with Nataniel Ruiz - #648
Ensuring LLM Safety for Production Applications with Shreya Rajpal - #647
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