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Explore the cutting-edge topic of Elastic Decision Transformer in this 53-minute video that combines transformers and reinforcement learning. Delve into the innovative Elastic Decision Transformer (EDT) concept, which enhances traditional Decision Transformers by adaptively modifying the historical context used during inference. Learn how EDT maintains a longer history for optimal trajectories while shortening it for sub-optimal ones. Discover the research behind this advancement, including the work of Yueh-Hua Wu, Xiaolong Wang, and Masashi Hamaya. Gain insights into the latest AI research and industry trends through additional resources such as "The Deep Dive" newsletter and Unify's blog posts. Access valuable links to further explore the topic, including the original research paper, Unify's website, GitHub repository, Discord community, and Twitter account.