This AI article has breakthroughs: How language models adapt to offline reinforcement learning with ‘LaMo’ dance ste

This AI article has breakthroughs: How language models adapt to offline reinforcement learning with ‘LaMo’ dance steps and sparse learning

11/07/2023

Researchers present Language Models for Motion Control (LaMo), a framework that uses large language models (LLM) for offline reinforcement learning. ...

Stanford and UT Austin researchers propose contrastive preference learning (CPL): a simple RL-free reinforcement learning method for RLHF that works with arbitrary MDP and off-policy data

by Technical Terrence Team

10/31/2023

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The challenge of matching human preferences to large pre-trained models has gained importance in the study as these models have ...

Integrating Generative AI and Reinforcement Learning

by Technical Terrence Team

10/22/2023

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Introduction In the ever-evolving landscape of artificial intelligence, two key players have come together to break new ground: Generative ai ...

Taiwan Semiconductor receives positive reinforcement from Wall Street after third quarter

by Technical Terrence Team

10/19/2023

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Annabelle Chih Taiwan Semiconductors (New York Stock Exchange:TSM) most recent earnings report received good reviews from several Wall Street firms. ...