Gizmochina

AgiBot Makes History: First Robot to Learn Directly on the Factory Floor

AgiBot, a robotics company focused on embodied intelligence, has achieved a major milestone by successfully deploying its Real-World Reinforcement Learning (RW-RL) system on a pilot production line ...
TMCnet

AgiBot Achieves First Real-World Deployment of Reinforcement Learning in Industrial Robotics

SHANGHAI, Nov. 3, 2025 /PRNewswire/ -- AgiBot, a robotics company specializing in embodied intelligence, announced a key milestone with the successful deployment of its Real-World Reinforcement ...

AI Agents, LLMs & Economic Growth : Karpathy’s Surprising Predictions

Discover Andrej Karpathy's insights on AI agents, LLMs, and economic growth. Insights on memory, education, and economic ...

Which Machine Learning Models Are Most Used In Crypto Signal Generation?

Machine learning is transforming how crypto traders create and understand signals. From supervised models such as Random Forests and Gradient Boosting Machines to sophisticated deep learning hybrids ...
Unite.AI

The End of Tabula Rasa: How Pre-Trained World Models are Redefining Reinforcement Learning

For a long time, the core idea in reinforcement learning (RL) was that AI agents should learn every new task from scratch, like a blank slate. This "tabula rasa" approach led to amazing achievements, ...

Inside Ring-1T: Ant engineers solve reinforcement learning bottlenecks at trillion scale

Ant Group, an affiliate of Alibaba, released Ring-1T which it says is the first trillion parameter open-source model.

Self-improving language models are becoming reality with MIT's updated SEAL technique

Researchers at the Massachusetts Institute of Technology (MIT) are gaining renewed attention for developing and open sourcing ...
IEEE

CTS: Concurrent Teacher-Student Reinforcement Learning for Legged Locomotion

Abstract: Thanks to recent explosive developments of data-driven learning methodologies, reinforcement learning (RL) emerges as a promising solution to address the legged locomotion problem in ...
IEEE

Safe Reinforcement Learning on the Constraint Manifold: Theory and Applications

Abstract: Integrating learning-based techniques, especially reinforcement learning, into robotics is promising for solving complex problems in unstructured environments. Most of the existing ...