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 ...

Market 32/Price Chopper employee turned love for learning into a career

BETHLEHEM — Over 23 years ago, Middletown resident Addy Jennings started her career at Market 32 and Price Chopper as a ...
IEEE

Deep Internal Learning for Single-Channel Speech Dereverberation

Abstract: Deep Internal Learning (DIL) is a paradigm with high potential in deep learning, as it reduces reliance on external training data and uses a lightweight model compared to traditional deep ...
Forbes

When Learning Meets EdTech And Finally Becomes The Work

Forbes contributors publish independent expert analyses and insights. Leadership Strategist Dan Pontefract covers leadership and culture. This voice experience is generated by AI. Learn more. This ...
Forbes

Why Lateral Career Moves Still Feel Risky—And What Leaders Can Do

Forbes contributors publish independent expert analyses and insights. Vibhas Ratanjee studies leadership and culture at Gallup Career growth inside companies still follows a narrow script—progress ...
Frontiers

Strategic HRM and SME innovation: a chain mechanism of learning-resilience pathway and nonlinear environmental dynamism

In an increasingly competitive business environment, organizational innovation has become crucial for enterprises seeking to establish and maintain a competitive advantage. This study aims to ...
marktechpost

Why Do Task Vectors Exist in Pretrained LLMs? This AI Research from MIT and Improbable AI Uncovers How Transformers Form Internal Abstractions and the Mechanisms Behind in ...

Large Language Models (LLMs) have demonstrated remarkable similarities to human cognitive processes’ ability to form abstractions and adapt to new situations. Just as humans have historically made ...
IEEE

Deep Internal Learning: Deep learning from a single input

Abstract: Deep learning, in general, focuses on training a neural network from large labeled datasets. Yet, in many cases, there is value in training a network just from the input at hand. This is ...
Psychology Today

Examples of How You Can Use State-Dependent Learning

State-dependent learning (SDL) is the phenomenon that behavior is learned better if your internal mental state is similar during practice and testing of the behavior. It is a powerful ...