AI data trainer roles have moved from obscure contractor gigs to a visible career path with clear pay bands and defined ...

Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...

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.

This study presents SynaptoGen, a differentiable extension of connectome models that links gene expression, protein-protein interaction probabilities, synaptic multiplicity, and synaptic weights, and ...

In an effort to teach self-management to students identified as impulsive, Meichenbaum found that he could help students control and manage their impulsive behaviors.

Researchers at Google Cloud and UCLA have proposed a new reinforcement learning framework that significantly improves the ability of language models to learn very challenging multi-step reasoning ...

Speaking multiple languages could slow down brain ageing and help to prevent cognitive decline, a study of more than 80,000 people has found. The work, published in Nature Aging on 10 November, ...

Abstract: Evolutionary reinforcement learning (ERL), which integrates the evolutionary algorithms (EAs) and reinforcement learning (RL) for optimization, has demonstrated remarkable performance ...

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 ...

Companies investing millions in generative AI may soon find themselves stalled—not by the technology’s limits, but by their people’s. As generative AI becomes more ubiquitous, a paradox has emerged: ...

At UC Berkeley, researchers in Sergey Levine’s Robotic AI and Learning Lab eyed a table where a tower of 39 Jenga blocks stood perfectly stacked. Then a white-and-black robot, its single limb doubled ...