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) ...

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 ...

Python libraries used in top AI and ML tools hacked

Security researchers from Palo Alto Networks have discovered vulnerabilities used in some top Artificial Intelligence (AI) ...
Daily Excelsior

Machine Learning Methods Used for Portfolio Optimization and Risk Management

Machine learning is reshaping the way portfolios are built, monitored, and adjusted. Investors are no longer limited to ...
IEEE

Reinforcement Learning With Model Predictive Control for Highway Ramp Metering

Abstract: In the backdrop of an increasingly pressing need for effective urban and highway transportation systems, this work explores the synergy between model-based and learning-based strategies to ...
InfoWorld

AI and machine learning outside of Python

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.
The Robot Report

AgiBot deploys its Real-World Reinforcement Learning system

AgiBot announced a key milestone this week with the successful deployment of its Real-World Reinforcement Learning system in a manufacturing pilot with Longcheer Technology. The pilot project marks ...
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 ...
acm.org

Rediscovering Reinforcement Learning

Reinforcement learning (RL) is machine learning (ML) in which the learning system adjusts its behavior to maximize the amount of reward and minimize the amount of punishment it receives over time ...
IEEE

Safe Reinforcement Learning on the Constraint Manifold: Theory and Applications

Abstract: Integrating learning-based techniques, especially reinforcement learning, into robotics is promising for solving complex problems in unstructured environments. Most of the existing ...
TechCrunch

The reinforcement gap — or why some AI skills improve faster than others

AI coding tools are getting better fast. If you don’t work in code, it can be hard to notice how much things are changing, but GPT-5 and Gemini 2.5 have made a whole new set of developer tricks ...