But the grand work-changing projects of A.I., like self-driving cars and humanoid robots, are not yet commercial products. A more humble version of the technology, instead, is making its presence felt in a less glamorous place: the back office.
Artificial intelligence software is making its presence felt in subtle ways, in an unglamorous place: the back office.
Researchers at the National Institute of Standards and Technology (NIST) have made a silicon chip that distributes optical signals precisely across a miniature brain-like grid, showcasing a potential new design for neural networks.
The human brain has billions of neurons (nerve cells), each with thousands of connections to other neurons. Many computing research projects aim to emulate the brain by creating circuits of artificial neural networks. But conventional electronics, including the electrical wiring of semiconductor circuits, often impedes the extremely complex routing required for useful neural networks.
The NIST team proposes to use light instead of electricity as a signaling medium. Neural networks already have demonstrated remarkable power in solving complex problems, including rapid pattern recognition and data analysis. The use of light would eliminate interference due to electrical charge, and the signals would travel faster and farther.
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Artificial intelligence has been a topic of growing prominence in the media and mainstream culture since 2015, as well as in the investment world, with start-ups that even mention the word in their business model, gaining massive amounts of funding.
While to many, the hype around AI may appear sudden, the concepts of modern artificial intelligence have been around for over a century and extending further, the concept of artificial intelligence and artificial beings have been in the minds of humans for thousands of years.
To better understand and appreciate this technology and those who brought it to us as well as to gain insight into where it will take us: sit back, relax and join me in an exploration on the history of artificial intelligence.
Engineers at Caltech have developed a new control algorithm that enables a single drone to herd an entire flock of birds away from the airspace of an airport. The algorithm is presented in a study in IEEE Transactions on Robotics.
The project was inspired by the 2009 “Miracle on the Hudson,” when US Airways Flight 1549 struck a flock of geese shortly after takeoff and pilots Chesley Sullenberger and Jeffrey Skiles were forced to land in the Hudson River off Manhattan.
“The passengers on Flight 1549 were only saved because the pilots were so skilled,” says Soon-Jo Chung, an associate professor of aerospace and Bren Scholar in the Division of Engineering and Applied Science as well as a JPL research scientist, and the principal investigator on the drone herding project. “It made me think that next time might not have such a happy ending. So I started looking into ways to protect airspace from birds by leveraging my research areas in autonomy and robotics.”
Here on Earth, electromagnetic waves around the planet are typically pretty calm. When the Sun fires a burst of charged particles at the Earth we are treated to an aurora (often called Northern Lights), but rarely are they a cause for concern. If you were to head to Jupiter, however, things would change dramatically.
In a new study published in Nature Communications, researchers describe the incredible electromagnetic field structure around two of Jupiter’s moons: Europa and Ganymede. The invisible magnetic fields around these bodies is being powered by Jupiter’s own magnetic field, and the result is an ultra-powerful particle accelerator of sorts, which might be capable of seriously damaging or even destroying a spacecraft.
“Chorus waves” are low-frequency electromagnetic waves that occur naturally around planets, including Earth. Near our planet they’re mostly harmless, but they do have the capability to produce extremely fast-moving “killer” particles that could cause damage to manmade technology if we happened to be in the wrong place at the wrong time.
NEC has announced that it will be providing a large-scale facial recognition system for the 2020 Summer Olympic and Paralympic Games in Tokyo. The system will be used to identify over 300,000 people at the Games, including athletes, volunteers, media, and other staff. It’s the first time that facial recognition technology will ever be used for this purpose at an Olympic Games.
NEC’s system is built around an AI engine called NeoFace, which is part of the company’s overarching Bio-IDiom line of biometric authentication technology. The Tokyo 2020 implementation will involve linking photo data with an IC card to be carried by accredited people. NEC says that it has the world’s leading face recognition tech based on benchmark tests from the US’ National Institute of Standards and Technology.
Roboticists are envisioning a future in which soft, animal-inspired robots can be safely deployed in difficult-to-access environments, such as inside the human body or in spaces that are too dangerous for humans to work, in which rigid robots cannot currently be used. Centimeter-sized soft robots have been created, but thus far it has not been possible to fabricate multifunctional flexible robots that can move and operate at smaller size scales.
A team of researchers at Harvard’s Wyss Institute for Biologically Inspired Engineering, Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS), and Boston University now has overcome this challenge by developing an integrated fabrication process that enables the design of soft robots on the millimeter scale with micrometer-scale features. To demonstrate the capabilities of their new technology, they created a robotic soft spider – inspired by the millimeter-sized colorful Australian peacock spider – from a single elastic material with body-shaping, motion, and color features. The study is published in Advanced Materials.
“The smallest soft robotic systems still tend to be very simple, with usually only one degree of freedom, which means that they can only actuate one particular change in shape or type of movement,” said Sheila Russo, Ph.D., co-author of the study. Russo helped initiate the project as a Postdoctoral Fellow in Robert Wood’s group at the Wyss Institute and SEAS and now is Assistant Professor at Boston University. “By developing a new hybrid technology that merges three different fabrication techniques, we created a soft robotic spider made only of silicone rubber with 18 degrees of freedom, encompassing changes in structure, motion, and color, and with tiny features in the micrometer range.”
Researchers from the University of Pittsburgh have recently developed a conditional variational autoencoder that can produce unique faces for advertisements. Their study is grounded on their previous work, which explored automated methods of better understanding advertisement.
“In our past project, we wanted to see whether machines could decode the complex visual rhetoric found in ads,” Christopher Thomas, one of the researchers who carried out the study, told Tech Xplore. “Ads contain puns, metaphors, and other persuasive rhetorical devices that are hard for machines to understand. In this paper, we didn’t only want to understand ads, but we wanted to see whether such persuasive content could be automatically generated by computers.”
The primary mission of the advertising industry is to promote products or convey ideas using persuasive language and images. Faces, a key aspect of ads, are often portrayed differently depending on the product advertised and message communicated.
