Good morning dear readers of Tecnogalaxy, today we will talk about a new AI chip (artifical intelligence) of MIT, which is faster than a synapse of a human brain.

A team of researchers from the Massachusetts Institute of Technology (MIT) has worked to push the speed limits a type of analog synapse created earlier, which is cheaper to build and is more energy efficient and promises faster computing.


This latest development could help scientists develop learning models for artificial intelligence much faster, which could then be applied in uses such as self-driving cars, DeepFake detection, and medical analysis.

The multidisciplinary team used programmable resistors, which are the backbone of analog learning, just as transistors are the key elements in building digital processors.

The resistors are integrated into repeated arrays to create a complex, layered network of artificial “neurons” and “synapses” that perform calculations just like a digital neural network. This network can then be trained to perform complex artificial intelligence tasks such as image recognition and natural language processing.

The researchers used a practical inorganic material in the manufacturing process that allows their devices to operate 1 million times faster than previous versions. The study also stated that it is about 1 thousand times faster than synapses in the human brain.

This organic material makes the resistor extremely energy efficient, unlike the materials used in the previous version of the device, the newly developed material is compatible with silicon fabrication techniques and could pave the way for integration into commercial computer hardware for learning applications of an AI.

“With this key insight and the very powerful nanofabrication techniques we have at MIT.nano, we were able to put these pieces together and prove that these devices are very fast and work with reasonable voltages, that are therefore thinkable in a classic work environment” said Jesús A., Professor at the Department of Electrical and Computer Engineering (EECS) of MIT.

“The mechanism of operation of the device is the electrochemical insertion of the smallest ion, that is of the proton, in an insulating oxide to modulate its electronic conductivity. Because we are working with very small devices, we could accelerate the movement of this ion using a strong electric field and push these ionic devices to the nanosecond operating regime,” explained Bilge Yildiz, Professor of Breene M. Kerr in the departments of Nuclear Science and Engineering and Materials Science and Engineering. “The action potential in biological cells increases and decreases with a time scale of milliseconds as the voltage difference of about 0.1 volts is constrained by water stability,” he added. “Here we applied for experiments up to 10 volts on a special nanometer thick solid glass film that conducts the protons, without damaging it permanently; being the strongest field will also be the field and therefore the faster the ion devices will be”The professor of the Nuclear Science and Engineering Departments has also stated.

“Once you have an analog processor, you no longer have to train the networks that everyone is working on right now to ensure that we continue to develop exponentially in the world of technology. Networks will be formed with unprecedented complexity that no one else can afford, and therefore with these future sketches you will be able to surpass any computing magnitude. In other words, this is not a faster car, this is comparable to a spaceship,” he adds during MIT postdoctorate Murat Onen.

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