Forbes

How Direct Preference Optimization Can Bring User‑Driven Agility To AI

Imagine training a voice‑recognition system without hand‑transcribing thousands of hours of audio. Traditional supervised learning demands that developers label every snippet with exact text—a costly, ...
EurekAlert!

Offline model-based reinforcement learning with causal structured world models

The architecture of FOCUS. Given offline data, FOCUS learns a $p$ value matrix by KCI test and then gets the causal structure by choosing a $p$ threshold. After ...
Microsoft

With reinforcement learning, Microsoft brings a new class of AI solutions to customers

Someone looking to book a vacation online today might have very different preferences than they did before the COVID-19 pandemic. Instead of flying to an exotic beach, they might feel more comfortable ...
VentureBeat

Demystifying deep reinforcement learning

Join the event trusted by enterprise leaders for nearly two decades. VB Transform brings together the people building real enterprise AI strategy. Learn more Deep reinforcement learning is one of the ...
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 ...
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.
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 ...