Explore the hidden trade-offs of reinforcement learning in AI and why base models might hold the key to true intelligence.

He also discussed the "education" of such machines "by means of rewards and punishments." Turing's ideas ultimately led to the development of reinforcement learning, a branch of artificial ...

Let’s move on to temporal difference learning (TD learning), which is a subset of reinforcement learning that was the focus ...

Read more about Deep reinforcement learning could redefine insulin delivery for diabetes patients on Devdiscourse ...

Turing Award recipients Richard Sutton and Andrew Barto believe reinforcement learning will play a role in artificial general ...

Researchers from Stanford University and Google DeepMind have unveiled Step-Wise Reinforcement Learning (SWiRL), a technique designed to enhance the ability of large language models (LLMs) to tackle ...

By categorizing and filtering user input, you can better focus on driving AI improvement. This iterative process—blending automation with human review—ensures AI learns from high-quality data, leading ...

Abstract Investigating flat minima on loss surfaces in parameter space is well-documented in the supervised learning context, highlighting its ...

Third-year doctoral student, Jiaheng Hu is one of two recipients selected for a Ph.D. fellowship with Two Sigma, a New ...