Nature

Evolution of circuits for machine learning

Cyrus F. Hirjibehedin is in the Quantum Information and Integrated Nanosystems group, Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, Massachusetts 02421, USA. Although computers ...
InfoQ

PrefixRL: Nvidia's Deep-Reinforcement-Learning Approach to Design Better Circuits

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...
EurekAlert!

Dopamine selects, astrocytes refine: a new mechanism for motor-learning circuit rewiring

Astrocyte-mediated synapse elimination was significantly increased after motor learning. This learning-associated increase was not observed in astrocyte-specific Megf10 knockout mice. In addition, ...
Semiconductor Engineering

Learning The AMS Circuit Representation From Layout Positions (UT Austin/ NVIDIA)

A recent technical paper titled “TAG: Learning Circuit Spatial Embedding From Layouts” was published by researchers at UT Austin and NVIDIA. “Analog and mixed-signal (AMS) circuit designs still rely ...
Semiconductor Engineering

Analog On-Chip Learning Circuits In Mixed-Signal Neuromorphic SNNs

A technical paper titled “Neuromorphic analog circuits for robust on-chip always-on learning in spiking neural networks” was published by researchers at Institute of Neuroinformatics, University of ...