In Moltbook hysteria, former top Facebook researcher sees echoes of 2017 panic over bots building a ‘secret language’

If any of this induces a weird sense of déjà vu, it may be because we’ve actually been here before—at least in terms of press ...
IEEE

RNAF: ResilienceNet Adversarial Framework Using Deep Reinforcement Learning for Adversarial Attacks on Digital Images

Abstract: Adversarial attack is a key concern for state-of-the-art artificial intelligence (AI), especially those used in image classification and computer vision. These attacks exploit minute changes ...
IEEE

A Deep Reinforcement Learning Approach for Synchronization Between Two Memristor Chaotic Systems and Application for Image Encryption

Abstract: This study proposes a novel synchronization framework for memristive chaotic systems (MCSs) through an enhanced deep reinforcement learning (DRL) approach, featuring an improved proximal ...

Reinforcement learning and organizational management

Artificial reinforcement learning is just one lens to evaluate organizations. However, this thought experiment taught me that ...

Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025)

Why reinforcement learning plateaus without representation depth (and other key takeaways from NeurIPS 2025) ...
GitHub

VLAC: A Vision-Language-Action-Critic Model for Robotic Real-World Reinforcement Learning

VLAC is a general-purpose pair-wise critic and manipulation model which designed for real world robot reinforcement learning and data refinement. It provides robust evaluation capabilities for task ...
marktechpost

Google AI Unveils Supervised Reinforcement Learning (SRL): A Step Wise Framework with Expert Trajectories to Teach Small Language Models to Reason through Hard Problems

How can a small model learn to solve tasks it currently fails at, without rote imitation or relying on a correct rollout? A team of researchers from Google Cloud AI Research and UCLA have released a ...
Forbes

The Autonomous Advantage: Reinforcement Learning’s Role In The Next Era Of AI

The age of truly autonomous artificial intelligence, where systems proactively learn, adapt and optimize amid real-world complexities instead of simply reacting, has been a long-held aspiration. Now, ...