How Google’s 'internal RL' could unlock long-horizon AI agents

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

True agentic AI is years away - here's why and how we get there

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.
IEEE

From Sparse to Dense: Toddler–inspired Reward Transition in Goal–Oriented Reinforcement Learning

Abstract: Reinforcement learning (RL) agents face fundamental challenges in balancing exploration and exploitation, particularly when sparse or dense rewards bias learning toward sub–optimal behaviors ...
Frontiers

Social robot navigation: a review and benchmarking of learning-based methods

For autonomous mobile robots to operate effectively in human environments, navigation must extend beyond obstacle avoidance to incorporate social awareness. Safe and fluid interaction in shared spaces ...
Overdrive

Trucker of the Month John Penn reaps 10-mpg-plus rewards of two decades learning, growing

Owner-operator John Penn trucks with authority as J.P. Transport, headquartered in Orleans, Indiana. The owner-operator's been in business for more than a decade now, with steady improvement in ...
Geeky Gadgets

Grok 5 : The Shocking AGI Breakthrough No One’s Talking About

What if the most profound leap toward Artificial General Intelligence (AGI) wasn’t a headline-grabbing announcement, but a quiet breakthrough flying under the radar? Enter Grok 5, a development that ...
NextBigFuture

AI Legend Sutton Wrote the Bitter Lesson- Gives His Suggestions for True Continual Learning

Sutton believes Reinforcement Learning is the Path to to Intelligence via Experience. Sutton defines intelligence as the computational part of the ability to achieve goals. It is rooted in a stream of ...