The development of a new method to make non-volatile computer memory may have unlocked a problem that has been holding back machine learning and has the potential to revolutionize technologies like voice recognition, image processing and autonomous driving.
A team from Sandia National Laboratories, working with collaborators from the University of Michigan, published a paper in the peer-reviewed journal Advanced Materials that details a new method that will imbue computer chips that power machine-learning applications with more processing power by using a common material found in house paint in an analog memory device that enables highly energy-efficient machine inference operations.
Titanium oxide is one of the most commonly made materials. Every paint we buy has titanium oxide in it. It’s cheap and nontoxic.
Credit: Photo courtesy of Sandia National Laboratories
Research paper: Filament‐Free Bulk Resistive Memory Enables Deterministic Analogue Switching https://onlinelibrary.wiley.com/doi/10.1002/adma.202003984
News Source: https://share-ng.sandia.gov/news/resources/news_releases/computer_memory/
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