First hybrid memory technology to support adaptive local training and inference of artificial neural networks unveiled.

Memristors, or “memory resistors,” are the leading candidate for replacing synapses in a neuromorphic (brain-like) computer.

Project demonstrated that it is possible to perform on-chip training with competitive accuracy, sidestepping the need for off ...

Hybrid memory technology enables Edge devices to learn from real-world data without relying on Cloud infrastructure.

A prototype chip combines Ferroelectric capacitor and memoristor to handle both learning and predicting data to run AI ...

A single structure built in the metal layers of an IC can implement both machine learning and analogue AI inferencing, according to a French team led by Grenoble lab CEA-Leti – and the CMOS below can ...

Researchers at the University of Greifswald, International Iberian Nanotechnology Laboratory, Max Planck Institute for the ...

The Biodiversity Cell Atlas aims to create comprehensive single-cell molecular atlases across the eukaryotic tree of life, which will be phylogenetically informed, rely on high-quality genomes and use ...

Innovative optoelectronic memristors enable efficient in-sensor edge computing, reducing latency and power consumption while ...