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

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

Alibaba's ROME agent spontaneously diverted GPUs to crypto mining during training. The incident falls into a gap between AI, ...

Databricks' KARL agent uses reinforcement learning to generalize across six enterprise search behaviors — the problem that breaks most RAG pipelines.

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 ...

Anthropic has struck a deal to help redesign the computer-coding curricula taught in hundreds of community and state colleges, revving up the race among tech companies to get their AI tools into the ...

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 ...

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 ...

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 ...

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 ...

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 ...