Yian Yin teamed up with economists at Northwestern University to look at the impact of researchers who had shifted their ...

Learn how the Reinforcement Learned Teacher model slashes AI training costs, accelerates timelines, and democratizes ...

Karthik Mani is a technology architect and applied researcher whose twenty-year career spans cloud-native infrastructure, ...

Reinforcement Pre-Training (RPT) is a new method for training large language models (LLMs) by reframing the standard task of predicting the next token in a ...

The ventral tegmental area (VTA) plays a key role in motivation and the brain’s reward circuit. The main source of dopamine, this small cluster of neurons sends this neuromodulator to other brain ...

In recent years, Large Language Models (LLMs) have significantly redefined the field of artificial intelligence (AI), enabling machines to understand and generate human-like text with remarkable ...

Reinforcement learning is a subtype of machine learning in which a virtual agent, functioning within a set of predefined rules, aims to maximise a specified outcome or reward. This agent can consider ...

Reinforcement learning techniques could be the keys to integrating robots — who use machine learning to output more than words — into the real world.

They revisited the foundations of reinforcement learning in the context of human feedback, specifically evaluating the efficiency of REINFORCE-style optimization variants against the traditional PPO ...

Deep Learning and Reinforcement Learning are two of the most popular subsets of Artificial intelligence. The AI market was about $120 billion in 2022 and is increasing at a mind-boggling CAGR above 38 ...

In all, reinforcement learning suffers from the same limitations as regular machine learning. It’s an ideal option for domains that are evolving and where some data is unavailable at the start.