Memristors Run AI Tasks at 1/800th Power. These brain-mimicking devices boast tiny energy budgets and hardened circuits

Memristors, or memory resistors, are essentially switches that can remember which electric state they were toggled to after their power is turned off.

researchers in Israel and China fabricated memristive devices using a standard CMOS production line. The resulting silicon synapses the team built boasted a 100 percent yield with 170- to 350-fold greater energy efficiency than a high-performance Nvidia Tesla V100 graphics processing unit when it came to multiply-accumulate operations, the most basic operation in neural networks.

The new devices displayed high endurance, operating past more than 100,000 cycles of programming and erasing using voltage pulses. In addition, they showed only moderate device-to-device variation and are projected to possess long data retention times of more than 10 years.

a team of French researchers investigated using memristors for the statistical computing technique known as Bayesian reasoning, in which prior knowledge helps compute the chances that an uncertain choice might be correct. Its results are fully explainable—unlike many nearly inscrutable AI computations—and it can perform well when there is little available data, as it can incorporate prior expert knowledge. However, “it is just not obvious how to compute Bayesian reasoning with memristors,” says study co-author Damien Querlioz, research scientist at CNRS, Université Paris-Saclay.