Yes, you heard it right. This common household material can revolutionize data storage and computing. Want to know about it further? Follow the details that we have mentioned in the paragraphs below.
A very non-toxic and easy-to-obtain material found in the household paint might be beneficial for one of the most significant machine learning issues.
The latest scientific journal that got published recently by one of the teams working at Sandia National Laboratories, in collaboration with researchers from the University of Michigan, stated that the material – titanium oxide, which we can often be seen in varnishes and paints, can effectively improve the energy efficiency which would, in turn, increase the performance of computer chips.
If the computer chip will get coated with titanium oxide and then gets heated to more than 150 degrees Celsius, there are significant chances that some of the oxygen molecules will get removed, which will result in the creation of oxygen vacancies. This entire process will make the material a lot more electrically conductive, which will let it store a more significant amount of information.
This discovery is crucial, as it will undoubtedly change the way computers store and process data. This, in turn, will result in saving a significant amount of energy.
All the information gets stored in one place before computers transfer it to another location for processing in the current scenario. This constant transfer process develops a significant amount of strain on the systems in processing power and energy usage. If this unnecessary power loss can be minimized, the oxygen vacancies will handle a more significant memory that requires intensive energy.
The lead author of the journal, Yiyang Li, described that they have tried to organize the storage and processing at the same place. However, that might now be new; they succeeded in doing it in a repeatable and predictable manner. In a general aspect, too, it takes a significant amount of energy to do machine learning. This is because you move it back and forth. One of the significant barriers while machine learning is power consumption.
This latest discovery related to titanium oxide might effectively help in image processing, voice recognition, and autonomous vehicles. However, these are only early-day predictions. A lot of research is yet to be done on this subject to scale it up before there’s an employment of the oxygen vacancies in the consumer or business technology.