Today's AI agents don't meet the definition of true agents. Key missing elements are reinforcement learning and complex memory. It will take at least five years to get AI agents where they need to be.

Ambuj Tewari receives funding from NSF and NIH. Understanding intelligence and creating intelligent machines are grand scientific challenges of our times. The ability to learn from experience is a ...

Andrew Barto and Richard Sutton developed reinforcement learning, a technique vital to chatbots like ChatGPT. By Cade Metz Reporting from San Francisco In 1977, Andrew Barto, as a researcher at the ...

The bird has never gotten much credit for being intelligent. But the reinforcement learning powering the world’s most advanced AI systems is far more pigeon than human. In 1943, while the world’s ...

The age of truly autonomous artificial intelligence, where systems proactively learn, adapt and optimize amid real-world complexities instead of simply reacting, has been a long-held aspiration. Now, ...

Having spent the last two years building generative AI (GenAI) products for finance, I've noticed that AI teams often struggle to filter useful feedback from users to improve AI responses.

Deep Reinforcement Learning (DRL) is a subfield of machine learning that combines neural networks with reinforcement learning techniques to make decisions in complex environments. It has been applied ...