A machine learning approach leverages nuclear microreactor symmetry to reduce training time when modeling power output ...

Tarpit Bansal, an AI researcher from OpenAI, joined Meta's Superintelligence team. His departure may significantly impact ...

Learn how the Reinforcement Learned Teacher model slashes AI training costs, accelerates timelines, and democratizes ...

Meta rested its case on Wednesday in an antitrust trial in which the U.S. government has accused the company of illegally snuffing out nascent competition by purchasing Instagram and WhatsApp.

In the world of quantum computing, the Hilbert space dimension—the measure of the number of quantum states that a quantum computer can access—is a prized possession. Having a larger Hilbert ...

Why Reinforcement Learning Matters Now The core idea behind reinforcement learning is for a system to learn in the same manner that people and animals learn—by taking actions and adjusting ...

And it’s a shame, because learning should be continual. Ultimately, I hope to move on from these early steps, which are purely supervised, and incorporate the insights into better reinforcement ...

Cooperative wind farm control is a complex problem due to wake effect, and it is hard to find the proper model. Reinforcement learning can find the optimal policy in a dynamic environment using “trial ...

That could be bad news for AI safety more broadly. Large-scale reinforcement learning is already being used to train AI agents: systems that can handle complex real-world tasks like scheduling ...

The Robotics & AI Institute deal is specifically focused on reinforcement learning, a method that operates through trial and error, similar to the way both humans and animals learn.

Reinforcement Learning-Driven Training: DeepSeek-R1 employs a unique multi-stage RL process to refine reasoning capabilities. Unlike its predecessor, DeepSeek-R1-Zero, which faced challenges like ...

This milestone underscored the power of reinforcement learning to unlock advanced reasoning capabilities without relying on traditional training methods like SFT. Source: DeepSeek-R1 paper.