Let’s look at how RL agents are trained to deal with ambiguity, and it may provide a blueprint of leadership lessons to ...

MIT researchers unveil a new fine-tuning method that lets enterprises consolidate their "model zoos" into a single, continuously learning agent.

Imagine trying to teach a child how to solve a tricky math problem. You might start by showing them examples, guiding them step by step, and encouraging them to think critically about their approach.

Echo-2 is designed to change that dynamic. Rather than forcing all training to run inside tightly controlled clusters, the system allows reinforcement learning workloads to be spr ...

LLMs tend to lose prior skills when fine-tuned for new tasks. A new self-distillation approach aims to reduce regression and ...

DeepSeek-R1's release last Monday has sent shockwaves through the AI community, disrupting assumptions about what’s required to achieve cutting-edge AI performance. Matching OpenAI’s o1 at just 3%-5% ...

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 ...

Researchers at The Hong Kong University of Science and Technology (HKUST) School of Engineering have developed a novel reinforcement learning–based generative model to predict neural signals, creating ...

This work presents an AI-based world model framework that simulates atomic-level reconstructions in catalyst surfaces under dynamic conditions. Focusing on AgPd nanoalloys, it leverages Dreamer-style ...

The rise of large language models (LLMs) such as GPT-4, with their ability to generate highly fluent, confident text has been remarkable, as I’ve written. Sadly, so has the hype: Microsoft researchers ...