A team has developed a method to 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. The material, titanium oxide, is a commonly made material used in house paint. It is an oxide, which means it already contains oxygen. Subtracting some of the oxygen creates oxygen vacancies that make the material electrically conductive. Those oxygen vacancies can now store electrical data, giving almost any device more computing power.
The team created the oxygen vacancies by heating a computer chip with a titanium oxide coating above 302 °F (150 °C), separated some of the oxygen molecules from the material using electrochemistry, and created vacancies.
Right now, computers generally work by storing data in one place and processing that data in another place. That means computers have to constantly transfer data from one place to the next, wasting energy and computing power. The new method makes the processing and the storage at the same place in a predictable and repeatable manner.
The use of oxygen vacancies could be a way to help machine learning overcome a big obstacle holding it back right now: power consumption. In autonomous vehicles, for example, making decisions about driving consumes a large amount of energy to process all the inputs. If an alternative material can be made for computer chips, the vehicles will be able to process information more efficiently, saving energy and processing more data.
In cellphones, to give a voice command, the user must be connected to a network that transfers the command to a central hub of computers that listens to the voice command and then sends a signal back telling the phone what to do. Through this process, voice recognition and other functions happen within the phone.