Skip to Content
Artificial intelligence

A new AI chip can perform image recognition tasks in nanoseconds

A stylized image of an artificial eye
A stylized image of an artificial eye
A stylized image of an artificial eyePixabay

The news: A new type of artificial eye, made by combining light-sensing electronics with a neural network on a single tiny chip, can make sense of what it’s seeing in just a few nanoseconds, far faster than existing image sensors.

Why it matters: Computer vision is integral to many applications of AI—from driverless cars to industrial robots to smart sensors that act as our eyes in remote locations—and machines have become very good at responding to what they see. But most image recognition needs a lot of computing power to work. Part of the problem is a bottleneck at the heart of traditional sensors, which capture a huge amount of visual data, regardless of whether or not it is useful for classifying an image. Crunching all that data slows things down.

A sensor that captures and processes an image at the same time, without converting or passing around data, makes image recognition much faster using much less power. The design, published in Nature today by researchers at the Institute of Photonics in Vienna, Austria, mimics the way animals’ eyes pre-process visual information before passing it on to the brain.

How it works: The team built the chip out of a sheet of tungsten diselenide just a few atoms thick, etched with light-sensing diodes. They then wired up the diodes to form a neural network. The material used to make the chip gives it unique electrical properties so that the photosensitivity of the diodes—the nodes in the network—can be tweaked externally. This meant that the network could be trained to classify visual information by adjusting the sensitivity of the diodes until it gave the correct responses. In this way, the smart chip was trained to recognize stylized, pixelated versions of the letters n, v, and z. 

Limited vision: This new sensor is another exciting step on the path to moving more AI into hardware, making it quicker and more efficient. But there’s a long way to go. For a start, the eye consists of only 27 detectors and cannot deal with much more than blocky 3x3 images. Still, small as it is, the chip can perform several standard supervised and unsupervised machine-learning tasks, including classifying and encoding letters. The researchers argue that scaling the neural network up to much larger sizes would be straightforward. 

Deep Dive

Artificial intelligence

chasm concept
chasm concept

Artificial intelligence is creating a new colonial world order

An MIT Technology Review series investigates how AI is enriching a powerful few by dispossessing communities that have been dispossessed before.

open sourcing language models concept
open sourcing language models concept

Meta has built a massive new language AI—and it’s giving it away for free

Facebook’s parent company is inviting researchers to pore over and pick apart the flaws in its version of GPT-3

spaceman on a horse generated by DALL-E
spaceman on a horse generated by DALL-E

This horse-riding astronaut is a milestone in AI’s journey to make sense of the world

OpenAI’s latest picture-making AI is amazing—but raises questions about what we mean by intelligence.

labor exploitation concept
labor exploitation concept

How the AI industry profits from catastrophe

As the demand for data labeling exploded, an economic catastrophe turned Venezuela into ground zero for a new model of labor exploitation.

Stay connected

Illustration by Rose WongIllustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.