An agentic AI tool for battery researchers harnesses data from previous battery designs to predict the cycle life of new ...

Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...

Discover the world of Recursive Self-Improvement (RSI) in AI. From I.J. Good's intelligence explosion to modern self-healing code and clinical applications, explore who is developing it, how it works, ...

As AI accelerates, leaders must fundamentally reimagine their digital operating model, harnessing AI as a catalyst to ...

A 'learner,' 'interpreter' and 'oracle' work together with minimal experiments to draw parallels between historical data and new battery designs A ...

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

If you’re using AI only to automate, you’re already behind. The real winners are rebuilding work itself with systems designed ...

The 'human-in-the-loop' approach manifests in three radically different ways, with profound implications for performance and skill development.

Researchers introduced AdditiveGDL, a generative deep learning method that predicts local thermal distributions across metal ...

From autonomous cars to video games, reinforcement learning (machine learning through interaction with environments) can have ...

Traditional processes used to discover new materials are complex, time-consuming, and costly, often requiring years of ...

This paper presents a novel framework for optimizing Carbon Release (CR) through an AI-driven approach to Fossil Fuel Intake (FFI) management. We propose a new training methodology for AI models to ...