Leadership Amid Uncertainty: CEOs Can Learn Effective Decision Making From Reinforcement Learning

Let’s look at how RL agents are trained to deal with ambiguity, and it may provide a blueprint of leadership lessons to ...
Tech Xplore on MSN

Why reinforcement learning breaks at scale, and how a new method fixes it

From autonomous cars to video games, reinforcement learning (machine learning through interaction with environments) can have ...
Semiconductor Engineering

DeepSeek: Improving Language Model Reasoning Capabilities Using Pure Reinforcement Learning

“We introduce our first-generation reasoning models, DeepSeek-R1-Zero and DeepSeek-R1. DeepSeek-R1-Zero, a model trained via large-scale reinforcement learning (RL) without supervised fine-tuning (SFT ...
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.
Forbes

The New OpenAI o1 Generative AI Model Makes An Important Right Turn When It Comes To Reinforcement Learning

Forbes contributors publish independent expert analyses and insights. Dr. Lance B. Eliot is a world-renowned AI scientist and consultant. In today’s column, I will identify and discuss an important AI ...
VentureBeat

Inside Ring-1T: Ant engineers solve reinforcement learning bottlenecks at trillion scale

China’s Ant Group, an affiliate of Alibaba, detailed technical information around its new model, Ring-1T, which the company said is “the first open-source reasoning model with one trillion total ...
International Monetary Fund

AI and Macroeconomic Modeling: Deep Reinforcement Learning in an RBC model

This study seeks to construct a basic reinforcement learning-based AI-macroeconomic simulator. We use a deep RL (DRL) approach (DDPG) in an RBC macroeconomic model. We set up two learning scenarios, ...
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 ...