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August 18 2022

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New hardware from MIT with analog synapses: 1 million faster than the human brain

New hardware in inorganic material reaches frightening speeds: analog synapses will revolutionize artificial intelligence.

Gianluca Ricciodi Gianluca Riccio
in Technology
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New hardware from MIT with analog synapses: 1 million faster than the human brain
August 3 2022
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The Massachusetts Institute of Technology (MIT) has developed new hardware based on analog synapses: it is a million times faster than the human brain. The new technology aims to focus on deep learning for a variety of purposes, while providing all users with great processing power.

An MIT research called "Nanosecond Proton Programmable Resistors for Deep Analog Learning" (I link it to you here) focuses on a new analog synapse designed for deep learning. The results, as mentioned, are insane. The hardware has enormous capabilities, and in addition to providing more computing power for the AI, it consumes less power for its needs.

synapsi
MIT's 'analog super synapse' will transform supercomputers into super intelligences

Rapid Analog Synapse, the cornerstone of the near future

To develop a super-fast and extremely energy-efficient programmable resistor, scientists considered completely different materials for the electrolyte. MIT's analog synapse is based on inorganic phosphosilicate glass, which gives it tremendous speed, low power consumption, and unprecedented capacity for machine learning.

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Machine learning with schemes inspired by the functioning of the brain human is growing everywhere. This research by the MIT group is just one of many focuses available around the world. The applications are almost endless, and at the service of the scientific community they will drive many new discoveries in the coming years, revolutionizing the old concept of 'supercomputer', which will now be more and more a 'super intelligence'.

Apparently equipped with its own synapses

With deep learning, products and services will increasingly focus on responses and results: from climate models that help us understand how the planet changes to 'virtual twins' that allow us to test virtual urban solutions before applying them to reality.

“With hardware like this you can train networks with unprecedented complexity that no one else can afford and, as a result, far surpass them all. In other words, this isn't a previous car, it's a spaceship, ”he says Murat Onen, MIT lead and postdoctoral author.

I can't wait for the world to start piloting it.

tags: computerinformaticsartificial intelligenceMIT
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