Time-slip in AI sepsis models may inflate results, risking under- or overtreatment

AI is already boosting positive outcomes in health care and holds promise for delivering many more. It is important, however, ...
Ars Technica

Exploration-focused training lets robotics AI immediately handle new tasks

Reinforcement-learning algorithms in systems like ChatGPT or Google’s Gemini can work wonders, but they usually need hundreds of thousands of shots at a task before they get good at it. That’s why ...
TMCnet

WiMi Deploys Quantum Computing Optimization Based on Multi-Objective Deep Reinforcement Learning

WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ("WiMi" or the "Company"), a leading global Hologram Augmented Reality ("AR") Technology provider, is researching quantum computing optimization based on ...
ZDNet

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

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.
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 ...
VentureBeat

MIT's new fine-tuning method lets LLMs learn new skills without losing old ones

When enterprises fine-tune LLMs for new tasks, they risk breaking everything the models already know. This forces companies to maintain separate models for every skill. Researchers at MIT, the ...