Computing With Chemicals Makes Faster, Leaner AI - IEEE Spectrum

A device that draws inspiration from batteries now appears surprisingly well suited to run artificial neural networks. Called electrochemical RAM (ECRAM), it is is quickly moving toward the head of the pack in the race to develop the perfect artificial synapse.

Analog Ai - IEEE Spectrum

Artificial intelligence: A powerful paradigm for scientific research - ScienceDirect

Artificial intelligence: A powerful paradigm for scientific research - ScienceDirect

Ram Sorcerer, in a more clean lithography approach, digital : r/drawing

Frontiers Exploring alternative approaches to precision medicine through genomics and artificial intelligence – a systematic review

Electronics, Free Full-Text

PDF) The Challenges and Opportunities of Human-Centred AI for Trustworthy Robots and Autonomous Systems

Frontiers Neurorobots as a Means Toward Neuroethology and Explainable AI

PDF) A STUDY OF ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING (ML) IN POWER SECTOR: AN ANALYSIS BY

Artificial Synapses 10,000x Faster Than Real Thing - IEEE Spectrum

Artificial Intelligence Based 'Waste-to-Valuable' Algorithm for Repurposing Chemical Wastes into Useful Drugs - CBIRT

Harnessing the era of artificial intelligence in higher education: a primer for higher education stakeholders

Frontiers Computer Vision, Machine Learning, and the Promise of Phenomics in Ecology and Evolutionary Biology

Machine Learning for Perovskite Solar Cells and Component Materials: Key Technologies and Prospects - Liu - 2023 - Advanced Functional Materials - Wiley Online Library