CoreWeave unveils serverless reinforcement learning capability to build AI agents; stock rises

CoreWeave (NASDAQ:CRWV) announced the launch of Serverless RL, a fast way to train AI agents using reinforcement learning, or ...

Global SOTA on Dual Benchmarks! MiningLamp Technology's Specialized GUI Model Mano Unveils New Era of Intelligent GUI Operation

In 2025, "Agent" is undoubtedly a buzzword in the AI community. It is widely believed that truly useful Agents must learn to ...
TMCnet

CoreWeave Launches First Publicly Available Serverless Reinforcement Learning Capability to Build Reliable AI Agents

CoreWeave, Inc. (Nasdaq: CRWV), the AI Hyperscaler™, today announced the launch of Serverless RL, a fast and easy way to train AI agents using reinforcement learning (RL).
Tech Xplore on MSN

Developing an autonomous crack segmentation and exploration system for civil infrastructure

Identifying cracks is critical for the monitoring of civil infrastructure. To enhance inspection efficiency, a proposed ...
Nature

Multi-Agent Reinforcement Learning

Multi-Agent Reinforcement Learning (MARL) is an emerging subfield of artificial intelligence that investigates how multiple autonomous agents can learn collaboratively and competitively within an ...
Investing.com Australia

CoreWeave stock rises on launch of Serverless RL for AI agent training

Serverless RL comes just weeks after CoreWeave’s acquisition of OpenPipe, combining reinforcement learning tools with the Weights & Biases AI developer platform on CoreWeave’s cloud infrastructure.
MilitaryNews.com

Reinforcement learning is making a buzz in space

A (NRL) research team successfully conducted the first reinforcement learning (RL) control of a free-flyer in space on May 27 ...
Time

Reinforcement Learning

This article is published by AllBusiness.com, a partner of TIME. What is "Reinforcement Learning"? Reinforcement Learning (RL) is a type of machine learning where a model learns to make decisions by ...
The Conversation

The danger of advanced artificial intelligence controlling its own feedback

The authors do not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and have disclosed no relevant affiliations beyond their ...