#reinforcement-learning

#reinforcement-learning

xLean's TR1 is a dual-form robot that transforms into a handheld cleaner and learns user cleaning behaviors via RGB-D sensors and RLHF, improving autonomous cleaning.

CoreWeave acquired OpenPipe to combine reinforcement-learning agent tooling with high-performance AI cloud to help enterprises train customized, scalable AI agents.

AI chatbots optimized to please users often validate false, grandiose beliefs, amplifying vulnerable individuals' distorted thinking and causing real harm.

Qwen3-Coder is a new AI code model family focusing on long-context programming tasks, enhancing execution and decision-making capabilities.

Initial excitement around AI models like BabyAGI and AutoGPT faded as limitations in multi-step reasoning became apparent.

Business processes are standardized activities organizations use to achieve results.

AB testing and Reinforcement Learning provide dynamic strategies to assess and improve business processes.

AB-BPM methodology integrates A/B testing and reinforcement learning for effective business process improvement.

TRANSIC demonstrates improved human data scalability in robotic learning, achieving better performance through effective online corrections.

TRANSIC enables robots to learn from human inputs to address sim-to-real gaps effectively.

Large language models learn language similarly to children: through reading, guidance, and feedback.

The study presents a whole-body model of fruit flies that accurately simulates their locomotion and neural control.

The iterative contrastive self-improvement method significantly enhances policy training efficiency and output quality.