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The top row shows images that our participants viewed in the fMRI scanner. The bottom row shows neural reconstructions from the participants' brain activity that predict where people will direct their eyes, overlaid on top of the images. Note that just the colored overlay predicting eye movements is reconstructed from brain activity and not the image underlay. The brighter white and pink areas in the reconstructions show where people directed their attention. CREDIT Chun Lab Yale

Mountain splendor? Scientists know where your eyes will look

A new discovery by Yale University could advance understanding the human visual system to improve a host of artificial intelligence efforts. By using precise brain measurements,...
HEART PATIENT

New algorithm may help heart patients in remote areas

There is some good news for heart patients in remote places. Scientists at the Indian Institute of Technology, Hyderabad (IIT-Hyderabad) have developed a new...
MIT computer scientists have developed a system that learns to identify objects within an image, based on a spoken description of the image

Machine-learning system tackles speech and object recognition

MIT computer scientists have built up a system that figures out how to distinguish protests inside an image, in view of a spoken description...
neuralnetwork

Scientists developed a neural network that operates on light

A group of scientists at the University of California has recently devised a new type of neural network that operates on light instead of...
Volcanic ash under the microscope comprises thousands of tiny particles with complex shapes

AI to help understanding volcanic eruption from tiny ash

Volcanic eruptions come in a wide range of structures, from the unstable emissions of Iceland's Eyjafjallajökull in 2010, which upset European air travel for...
The self-driving artificially intelligent wheelchair

Self-driving AI wheelchair to aiding people with disabilities

The research team at Imperial College London has won $50k. The prize was announced as part of Mobility Unlimited Challenge Discovery Award, which is funded by Toyota...
Called R1, Skydio's drone is equipped with 13 cameras that capture omnidirectional video. It launches and lands through an app — or by itself. On the app, the R1 can also be preset to certain filming and flying conditions or be controlled manually.

Autonomous video-capturing drone “selfie drone”

Skydio, a San Francisco-based startup founded by three MIT alumni has recently developed an autonomous video capturing drone also called 'selfie drone' that tracks and...
PhD student Adriana Schulz was co-lead on AutoSaw, which lets nonexperts customize different items that can then be constructed with the help of robots

AutoSaw: a robot that helps in custom carpentry

According to an estimate, one out of every 200 workers in the cohort suffered a hand injury that is serious enough to support a...
MIT researchers have developed a special-purpose chip that increases the speed of neural-network computations by three to seven times over its predecessors, while reducing power consumption 93 to 96 percent. That could make it practical to run neural networks locally on smartphones or even to embed them in household appliances

New chip to reduce neural networks’ power consumption

Advances in artificial-intelligence systems have come courtesy of neural networks as they are closely interconnected meshes of data processors. Neural networks are large and, their...