A reinforcement learning environment is a fail-safe digital practice room where an agent can afford to make mistakes and learn from them without real-world consequences.

A new study reveals that the next generation of blockchain defenses will not rely on fixed rules alone but on adaptive, learning-based systems capable of evolving alongside intelligent adversaries.

For children and teens, a psychologist might help them understand big feelings like worry, sadness, or anger; figure out why ...

BrainAlignNet, AutoCellLabeler, and CellDiscoveryNet—to automatically track and identify neurons in moving worms and jellyfish.

Discover Experiential Reinforcement Learning (ERL), a revolutionary AI training paradigm that allows language models to learn from their own reflections, turning failure into structured wisdom without ...

Enterprise adoption of cognitive intelligence platforms has accelerated, yet executive confidence has not kept pace. Many deployments promise ...

Nicholas Schneider of Eckert Seamans examines the surge in trade secret litigation and discusses how employee mobility, ...

Researchers from the University of Maryland, Lawrence Livermore, Columbia and TogetherAI have developed a training technique that triples LLM inference speed without auxiliary models or infrastructure ...

AI is breaking the artifact economy. But that disruption is also a kind of forced reckoning: It creates pressure to move ...

At Oak Ridge High School, an active FFA chapter teaches students leadership, public speaking and real-world skills that ...

There are three critical areas where companies most often go wrong: data preparation and training, choosing tools and specialists and timing and planning.