Neural architecture search (NAS) and machine learning optimisation represent rapidly advancing fields that are reshaping the way modern systems are designed and deployed. By automating the process of ...

A research team at Tohoku University and Future University Hakodate has demonstrated that living biological neurons can be trained to perform a supervised temporal pattern learning task previously ...

An AI-driven digital-predistortion (DPD) framework can help overcome the challenges of signal distortion and energy inefficiency in power amplifiers for next-generation wireless communication.

The network is based on a framework called the Extreme Learning Machine (ELM). In this setup, input images are duplicated and sent through several optical paths. These paths act like synapses in a ...

The ability to analyze the brain's neural connectivity is emerging as a key foundation for brain-computer interface (BCI) technologies, such as controlling artificial limbs and enhancing human ...

Scientists have created a neural network that allows for more accurate prediction of Arctic storms. It identifies errors in ...

A hunk of material bustles with electrons, one tickling another as they bop around. Quantifying how one particle jostles others in that scrum is so complicated that, beginning in the 1990s, physicists ...

A computational method combining generative AI with atomistic simulations can identify promising platinum alloy catalyst structures for hydrogen fuel cells, report researchers from Science Tokyo.

The era of AI evangelism is giving way to an era of rigorous evaluation, as 2026 sees a pivotal shift in how we measure neural network capabilities. Recent breakthroughs in stress testing, including ...