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.

Combining Machine Learning and Computational Chemistry for Predictive Insights Into Chemical Systems

Electronics, Free Full-Text

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

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

A Systematic Review on Intensifications of Artificial Intelligence Assisted Green Solvent Development

IEEE News - Short cycle degree in Software Development

Artificial intelligence: A powerful paradigm for scientific research - ScienceDirect

Artificial Intelligence in Drug Toxicity Prediction: Recent Advances, Challenges, and Future Perspectives

Machine learning techniques in additive manufacturing: a state of the art review on design, processes and production control

An analytical study on the identification of N-linked glycosylation sites using machine learning model [PeerJ]

10 Principles for Building a Nimble, M4.0-Ready Culture - The Manufacturing Leadership Council