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Age of RobotsAge of Robots

Age of Robots

Jul-18

Age of Robots magazine is dedicated to reporting on the technology of the Second Machine Age and how it is impacting our society and psychology. We aim to keep readers abreast of the many advances taking place in artificial intelligence, robotics, and associated fields.

Country:
Australia
Language:
English
Publisher:
This Side of the Cross Pty Ltd
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IN THIS ISSUE

access_time1 min.
the editor matthew dahlitz

Our cover this issue is of Joanne Pransky, the first robot psychiatrist. Mark Sackler, our North American correspondent got to interview Joanne and ask her about this rather unique job title. Being a registered psychotherapist myself, I was more than a little interested to find out about a real life Susan Calvin (Isaac Asimov's character who was the Robopsychologist in his short stories - you may remember Bridget Moynahan played Susan Calvin in the 2004 film I Robot). I was also surprised to find out that Joanne was dubbed the real-life Susan Calvin by Isaac Asimov himself!Also on the topic of women in tech, my friend and doctor of psychology, David Van Nuys, intervies Silja Litvin, a psychologist and founder of a company that produces digital mental health products.…

access_time1 min.
mission

Age of Robots magazine is dedicated to reporting on the technology of the Second Machine Age and how it is impacting our society and psychology. We aim to keep readers abreast of the many advances taking place in artificial intelligence, robotics, and associated fields. EDITOR-IN-CHIEF Matthew Dahlitz ASSOCIATE EDITOR Geoff Hall COPY EDITOR Tina Pentland MARKETING Vladimir Roldan VIDEO/ART Jachin Dahlitz U.S. CORRESPONDENT Mark Sackler PSYCHOLOGY David Van Nuys FORSIGHT Peter Bishop SCHOOL OF ROBOTICS Peter Corke ISSN 2208-2964Copyright © Dahlitz Media 2017 ACN: 139 064 074 Cover Image: Joanne Pransky ■…

access_time2 min.
in brief

The Right Squeeze For Quantum Computing Scientists at Hokkaido University and Kyoto University developed a theoretical approach to quantum computing that is 10 billion times more tolerant to errors than current theoretical models. Their method brings us closer to developing quantum computers that use the diverse properties of subatomic particles to transmit, process and store extremely large amounts of complex information.Scientists have been experimenting with “squeezing” light— a process that removes tiny quantum-level fluctuations (noise) from an electromagnetic field. Noise introduces a certain level of uncertainty into the amplitude and phase of the electromagnetic field. Squeezing is thus an efficient tool for the optical implementation of quantum computers, but the current usage is inadequate.This current model is ten billion times more tolerant to errors than current experimental…

access_time1 min.
simulating depression

During a depressive episode the ability of the brain to form new brain cells is reduced. Scientists of the Ruhr-Universität Bochum examined how this affects the memory with a computational model. It was previously known that people in an acute depressive episode were less likely to remember current events.The computational model however suggests that older memories were affected as well.Source: Ruhr-Universität Bochum ■…

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university of toronto ai researchers design ‘privacy filter’ for your photos that disables facial recognition systems

Researchers in U of T Engineering have designed a ‘privacy filter’ that disrupts facial recognition algorithms. The system relies on two AI-created algorithms: one performing continuous face detection, and another designed to disrupt the first. ((Credit: Avishek Bose)) As concerns over privacy and data security on social networks grow, U of T Engineering researchers led by Professor Parham Aarabi (ECE) and graduate student Avishek Bose (ECE MASc candidate) have created an algorithm to dynamically disrupt facial recognition systems.“Personal privacy is a real issue as facial recognition becomes better and better,” says Aarabi. “This is one way in which beneficial anti-facial-recognition systems can combat that ability.” Their solution leverages a deep learning technique called adversarial training, which pits two artificial intelligence algorithms against each other. Aarabi and Bose designed a…

access_time5 min.
ai-based method could speed development of specialized nanoparticles

A new technique developed by MIT physicists could someday provide a way to custom-design multilayered nanoparticles with desired properties, potentially for use in displays, cloaking systems, or biomedical devices. It may also help physicists tackle a variety of thorny research problems, in ways that could in some cases be orders of magnitude faster than existing methods.The innovation uses computational neural networks, a form of artificial intelligence, to “learn” how a nano-particle’s structure affects its behavior, in this case the way it scatters different colors of light, based on thousands of training examples. Then, having learned the relationship, the program can essentially be run backward to design a particle with a desired set of light-scattering properties — a process called inverse design.The findings are being reported in the journal Science…

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