Age of Robots


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.

This Side of the Cross Pty Ltd
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dans ce numéro

1 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. She…

1 min

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 2208-2964 Copyright © Dahlitz Media 2017 ACN: 139 064 074 Cover Image: Joanne Pransky…

2 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 methods, meaning that it…

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

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 set of two neural networks: the first working to identify faces, and the second working to disrupt the facial recognition task of the first. The two are constantly battling and learning from each other, setting up an ongoing AI arms…

5 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 Advances,…

5 min

KOMPAS was born out of a problem that my co-founders and I encountered while living abroad. We were struggling to find out what to do and where to go in a strange city, and we couldn’t find information that was relevant to our particular interests. We were never going to have the time or money to visit the hundreds if not thousands of venues advertised, when all we wanted were the hidden, more unusual and unique locations, bars, and restaurants dotted around the city The field of artificial intelligence (AI) and machine learning (ML) has developed significantly over the last five years, in part due to advances in hardware and processing power being made by companies such as Nvidia, IBM, Microsoft, and Google. We’re now in a position where this hardware…