Tech Xplore on MSN

Reinforcement learning accelerates model-free training of optical AI systems

Optical computing has emerged as a powerful approach for high-speed and energy-efficient information processing. Diffractive ...
The Next Web

Everything you need to know about model-free and model-based reinforcement learning

Reinforcement learning is one of the exciting branches of artificial intelligence. It plays an important role in game-playing AI systems, modern robots, chip-design systems, and other applications.
NextBigFuture

Reinforcement Learning Does NOT Fundamentally Improve AI Models

Reinforcement Learning does NOT make the base model more intelligent and limits the world of the base model in exchange for early pass performances. Graphs show that after pass 1000 the reasoning ...
Geeky Gadgets

Reinforcement Learning for LLMs in 2025

Imagine trying to teach a child how to solve a tricky math problem. You might start by showing them examples, guiding them step by step, and encouraging them to think critically about their approach.
EurekAlert!

Reinforcement learning world models for catalyst surface reconstruction: state-of-the-art review

This work presents an AI-based world model framework that simulates atomic-level reconstructions in catalyst surfaces under dynamic conditions. Focusing on AgPd nanoalloys, it leverages Dreamer-style ...
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 ...
VentureBeat

DeepSeek-R1’s bold bet on reinforcement learning: How it outpaced OpenAI at 3% of the cost

DeepSeek-R1's release last Monday has sent shockwaves through the AI community, disrupting assumptions about what’s required to achieve cutting-edge AI performance. Matching OpenAI’s o1 at just 3%-5% ...
Medical Xpress

New model frames human reinforcement learning in the context of memory and habits

Humans and most other animals are known to be strongly driven by expected rewards or adverse consequences. The process of acquiring new skills or adjusting behaviors in response to positive outcomes ...