True agentic AI is years away - here's why and how we get there

Today's AI agents are a primitive approximation of what agents are meant to be. True agentic AI requires serious advances in reinforcement learning and complex memory.
VentureBeat

OpenAI’s CoinRun tests the adaptability of reinforcement learning agents

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More Reinforcement learning (RL) — an artificial intelligence (AI) training ...
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 ...
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 ...
The Motley Fool

What Is Reinforcement Learning?

Reinforcement learning algorithms help AI reach goals by rewarding desirable actions. Real-world applications, like healthcare, can benefit from reinforcement learning's adaptability. Initial setup ...
The Next Web

Reinforcement learning: How rewards create intelligent machines

In June 2021, scientists at the AI lab DeepMind made a controversial claim. The researchers suggested that we could reach artificial general intelligence (AGI) using one single approach: reinforcement ...
Devdiscourse

Multi-agent AI boosts safety and transparency of self-driving cars in cities

Most current autonomous driving systems rely on single-agent deep learning models or end-to-end neural networks. While ...