AI"s inability to continually learn remains one of the biggest problems standing in the way to truly general purpose models.

HybridLeg robots Olaf and Snogie use impact-safe design and self-recovery to enable scalable, real-world hardware ...

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

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

Scientists are trying to tame the chaos of modern artificial intelligence by doing something very old fashioned: drawing a table. Instead of chemical elements, the new chart arranges learning ...

AI agents are reshaping software development, from writing code to carrying out complex instructions. Yet LLM-based agents are prone to errors and often perform poorly on complicated, multi-step tasks ...

Career and technical education programs are on the rise and appear poised for greater expansion. Well over half (61%) of educators report their districts have increased their CTE offerings over the ...

According to God of Prompt on Twitter, DeepMind has published groundbreaking research in Nature led by David Silver, introducing an AI meta-learning system capable of autonomously discovering entirely ...

W4S operates in turns. The state contains task instructions, the current workflow program, and feedback from prior executions. An action has 2 components, an analysis of what to change, and new Python ...

Abstract: A common approach to code optimization is to insert compiler hints in the source code using annotations. Two major challenges with using annotations effectively are their complexity and lack ...

In a college-entrance-exam landscape long dominated by the SAT and the ACT, a relative newcomer has started to gain traction—especially in red states. The Classic Learning Test, first unveiled a ...