Alibaba's Metis agent cuts redundant AI tool calls from 98% to 2% — and gets more accurate doing it

Alibaba's HDPO framework trains AI agents to skip unnecessary tool calls, cutting redundant invocations from 98% to 2% while ...
VentureBeat

Reinforcement learning competition pushes the boundaries of embodied AI

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Since the early decades of artificial intelligence, humanoid robots have ...
inc42

What Is Reinforcement Learning? Here’s All You Need to Know

Reinforcement learning is a subfield of machine learning concerned with how an intelligent agent can learn through trial and error to make optimal decisions in its ...
Seeking Alpha

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 RL. Shares of the company surged about 9% on Wednesday. The company said ...
The Next Web

Reinforcement learning could be the link between AI and human-level intelligence

Last week, I wrote an analysis of “Reward Is Enough,” a paper by scientists at DeepMind. As the title suggests, the researchers hypothesize that the right reward is all you need to create the ...
The Next Web

Debunking the mysteries of deep reinforcement learning

Deep reinforcement learning is one of the most interesting branches ofartificial intelligence. It is behind some of the most remarkable achievements of the AI community, including beating human ...
InfoWorld

What is deep reinforcement learning: The next step in AI and deep learning

Reinforcement learning is well-suited for autonomous decision-making where supervised learning or unsupervised learning techniques alone can’t do the job Reinforcement learning has traditionally ...
InfoWorld

Reinforcement learning comes into AI’s mainstream

One of the most noteworthy artificial intelligence trends in 2018 has been the maturation of reinforcement learning into a mainstream approach for building and training statistical models to do useful ...