Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
In June 2021, scientists at the AI lab DeepMind made a controversial claim. The researchers suggested that we could reach artificial general intelligence (AGI) using one single approach: reinforcement ...
Join the event trusted by enterprise leaders for nearly two decades. VB Transform brings together the people building real enterprise AI strategy. Learn more In their decades-long chase to create ...
Reinforcement learning frames trading as a sequential decision-making problem, where an agent observes market conditions, ...
Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.
Machine learning technique teaches power-generating kites to extract energy from turbulent airflows more effectively, ...
In an RL-based control system, the turbine (or wind farm) controller is realized as an agent that observes the state of the ...
The idea of reinforcement learning—or learning based on reward—has been around for so long it’s easy to forget we don’t really know how it works. If DeepMind’s new bombshell paper in Nature is any ...
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