AI Chip Breakthrough: Memristors Mimic Neural Timekeeping

Artificial neural networks could soon process time-dependent data more efficiently with the development of a tunable memristor. This technology, detailed in a University of Michigan-led study, could significantly reduce AI energy consumption. Credit: SciTechDaily.com In…


The New ChatGPT Offers a Lesson in AI Hype

When OpenAI unveiled the latest version of its immensely popular ChatGPT chatbot this month, it had a new voice possessing humanlike inflections and emotions. The online demonstration also featured the bot tutoring a child on…



New Quantum Dot Technology Improves Solar Cell Efficiency

A research team has developed a novel “pulse-shaped” light method to enhance the electrical conductivity of PbS quantum dot solar cells. This new technique, which replaces the lengthy traditional heat treatment process, generates substantial energy…



Energy From the Sky: How Drones Can Generate Electricity

New research into Airborne Wind Energy Systems, funded by a substantial EPSRC grant, seeks to harness high-altitude wind energy using drones, aiming to overcome challenges in system stability and enhance commercial viability, supporting the UK’s…


The Sodium Solution: Reducing Costs and Complexity in Batteries

Research on sodium-ion batteries aims to reduce reliance on rare elements and cut costs, enhancing battery performance for broader applications. However, fast charging introduces mechanical stresses that compromise the battery’s structural integrity and longevity. Simulations…