Quantum technologies like quantum computers are built from quantum materials. These types of materials exhibit quantum properties when exposed to the right conditions. Curiously, engineers can also ...

Walk through enough industrial AI deployments and a pattern becomes uncomfortable to ignore. The pilot works. The model ...

Explore the Types of Machine Learning and their impact on AI. Learn how these core frameworks drive digital innovation and ...

Spotting a needle in a haystack is easy compared to Yuejie Chi's typical day.As a leading researcher on the underpinnings of large language models ...

To this day, in the known universe, only one example exists of a system capable of general-purpose intelligence. That system ...

08/27/2025: Megatron-RL is actively under development. While it is functional internally at NVIDIA, it is not yet usable by external users because not all required code has been released. The ...

Abstract: This article proposes and analyzes an accelerated reinforcement learning (RL) algorithm for discrete-time linear systems with unknown dynamics. The method achieves cubic convergence, ...

Many enterprise RAG pipelines handle one type of search well and fail silently on the rest. Databricks on March 4 released a new agent called KARL, or Knowledge Agents via Reinforcement Learning, that ...

ABSTRACT: Oracle-based quantum algorithms cannot use deep loops because quantum states exist only as mathematical amplitudes in Hilbert space with no physical substrate. Critically, quantum wave ...

Agent Lightning is an agent optimization framework that enables agents to learn from their experiences through reinforcement learning and other methods. By treating agents as first-class citizens, ...

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Abstract: The Kleinman iteration is a policy iteration method for solving Riccati equations and forms the basis of many reinforcement learning (RL) algorithms. However, its direct application to ...