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.

According to a Latest Research, Quantum Machine Learning Could Benefit From a Spooky Action That Could Allow exponential Scaling Through Mysterious Quantum Connections - MarkTechPost

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

Utilizing machine learning to expedite the fabrication and biological application of carbon dots - Materials Advances (RSC Publishing) DOI:10.1039/D3MA00443K

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

Sandia-Developed Benchmark Re-ranks Top Computers

Recent advances and applications of machine learning in solid-state materials science

Searching for the Perfect Artificial Synapse for AI - IEEE Spectrum

News - MIT-IBM Watson AI Lab

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