Frontiers

Safe and Trustworthy Reinforcement Learning for Human–Robot Collaboration

Reinforcement Learning (RL) has rapidly emerged as a powerful approach for enabling robots to acquire adaptive, data-driven behaviors in real-world ...

Nvidia's Nemotron-Cascade 2 wins math and coding gold medals with 3B active parameters — and its post-training recipe is now open-source

Nvidia's Nemotron-Cascade 2 is a 30B MoE model that activates only 3B parameters at inference time, yet achieved gold medal-level performance at the 2025 IMO, IOI, and ICPC World Finals. Nvidia has ...
Tweakers

Based Model for UAV Self-separation Under Uncertainty

Master Thesis: Building an Uncertainty-Robust Reinforcement Learning-based model for UAV self-separation under Uncertainty ...
The New York Times

Coding After Coders: The End of Computer Programming as We Know It

In the era of A.I. agents, many Silicon Valley programmers are now barely programming. Instead, what they’re doing is deeply, deeply weird. Credit...Illustration by Pablo Delcan and Danielle Del Plato ...
Android Police

I'm finally learning to code, and I have NotebookLM to thank for it

Irene Okpanachi is a Features writer, covering mobile and PC guides that help you understand your devices. She has five years' experience in the Tech, E-commerce, and Food niches. Particularly, the ...
Microsoft

Experiential Reinforcement Learning

Reinforcement Learning is at the core of building and improving frontier AI models and products. Yet most state-of-the-art RL methods learn primarily from outcomes: a scalar reward signal that says ...
IEEE

GRFuzz: A Deep Reinforcement Learning Approach to Python Library Fuzzing with GRPO

In the digital realm, ensuring the security and reliability of systems and software is of paramount importance. Fuzzing has emerged as one of the most effective testing techniques for uncovering ...
marktechpost

A Coding Implementation to Train Safety-Critical Reinforcement Learning Agents Offline Using Conservative Q-Learning with d3rlpy and Fixed Historical Data

In this tutorial, we build a safety-critical reinforcement learning pipeline that learns entirely from fixed, offline data rather than live exploration. We design a custom environment, generate a ...
Bleeping Computer

Learn coding skills with 213 hours of hands-on training for $33

Breaking into tech—or leveling up within it—often starts with one big question: where do you begin? The Premium Learn to Code Certification Bundle is designed to answer that question by giving you ...
Microsoft

Argos: Multimodal reinforcement learning with agentic verifier for AI agents

Over the past few years, AI systems have become much better at discerning images, generating language, and performing tasks within physical and virtual environments. Yet they still fail in ways that ...
VentureBeat

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

Every year, NeurIPS produces hundreds of impressive papers, and a handful that subtly reset how practitioners think about scaling, evaluation and system design. In 2025, the most consequential works ...