Reinforcement learning frames trading as a sequential decision-making problem, where an agent observes market conditions, ...

Researchers in the US developed bipedal robots with a new design, the HybridLeg platform, ...

The Google PhD Fellowship programme supports outstanding graduate students pursuing innovative research in fields relevant to ...

What makes Vivek Shah's story resonate so deeply is that his commitment to quality and alignment extends far beyond the realm of algorithms. Alongside his demanding role steering Gauge AI, he is the ...

FPMCO decomposes multi-constraint RL into KL-projection sub-problems, achieving higher reward with lower computing than second-order rivals on the new SCIG robotics benchmark.

Today's AI agents don't meet the definition of true agents. Key missing elements are reinforcement learning and complex memory. It will take at least five years to get AI agents where they need to be.

Watch an AI agent learn how to balance a stick—completely from scratch—using reinforcement learning! This project walks you through how an algorithm interacts with an environment, learns through trial ...

The ability of computers to learn on their own by using data is known as machine learning. It is closely related to ...

Uber is turning its fleet scale into a data product to solve the autonomous vehicle industry’s most persistent bottleneck: ...

AI is helping scientists make sense of messy dinosaur footprints, offering new clues about how dinosaurs moved, evolved, and ...

The application, called the Strategic Grid Planner, extends the company’s Intelligent Grid Platform (IGP) and focuses on ...

Google researchers introduce ‘Internal RL,’ a technique that steers an models' hidden activations to solve long-horizon tasks ...