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ScienceDaily's AI News

ScienceDaily's AI News
Artificial Intelligence News. Everything on AI including futuristic robots with artificial intelligence, computer models of human intelligence and more.
Updated: 13 hours 19 min ago

New AI computer vision system mimics how humans visualize and identify objects

Thu, 20/12/2018 - 16:32
Researchers have demonstrated a computer system that can discover and identify the real-world objects it 'sees' based on the same method of visual learning that humans use.

Robots with sticky feet can climb up, down, and all around

Wed, 19/12/2018 - 14:25
Researchers have created a micro-robot whose electroadhesive foot pads, inspired by the pads on a gecko's feet, allow it to climb on vertical and upside-down conductive surfaces, like the inside walls of a commercial jet engine. Groups of them could one day be used to inspect complicated machinery and detect safety issues sooner, while reducing maintenance costs.

Computer hardware designed for 3D games could hold the key to replicating human brain

Wed, 19/12/2018 - 11:56
Researchers have created the fastest and most energy efficient simulation of part of a rat brain using off-the-shelf computer hardware.

Computer chip vulnerabilities discovered

Thu, 13/12/2018 - 15:56
A research team has uncovered significant and previously unknown vulnerabilities in high-performance computer chips that could lead to failures in modern electronics.

New models sense human trust in smart machines

Tue, 11/12/2018 - 19:00
New 'classification models' sense how well humans trust intelligent machines they collaborate with, a step toward improving the quality of interactions and teamwork.

Mountain splendor? Scientists know where your eyes will look

Tue, 04/12/2018 - 09:03
Using precise brain measurements, researchers predicted how people's eyes move when viewing natural scenes, an advance in understanding the human visual system that can improve a host of artificial intelligence efforts, such as the development of driverless cars.

Computers successfully trained to identify animals in photos

Tue, 27/11/2018 - 17:14
Researchers trained a deep neural network to classify wildlife species using 3.37 million camera-trap images of 27 species of animals obtained from five states across the United States. The model then was tested on nearly 375,000 animal images at a rate of about 2,000 images per minute on a laptop computer, achieving 97.6 percent accuracy -- likely the highest accuracy to date in using machine learning for wildlife image classification.