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I wonder if this would qualify as a turing test.
Lalith Polepeddi, a (human) teaching assistant and researcher on the Jill Watson project at the Georgia Institute of Technology.
Photo:
Lalith Polepeddi.
Continue reading “Imagine Discovering That Your Teaching Assistant Really Is a Robot” »
Great article about a mad-scientist whose vision caused the world to look cross-eyed. Many of us have been there before some time in our lives.
In 1981, Richard Feynman urged the world to build a quantum computer. In his own words.
“Nature isn’t classical, dammit, and if you want to make a simulation of nature, you’d better make it quantum mechanical, and by golly it’s a wonderful problem, because it doesn’t look so easy.”
Continue reading “The Quantum Experience: Feynman’s vision comes into focus” »
I personally can confirm that QC is not being worked on and advance by just a couple groups such as D-Wave and IBM. The questions/bumps in the road that we will all face is threefold:
1) how do we standardize the QC? right now (like most innovation) is done in siloes and limited cross-collaboration across government, labs & universities, and commercial companies. 2) governance and compliance; how will these need to change across multiple areas 3) id & mitigate all impacts instead of after deployment (don’t be reactive) because we will not have that luxury due to hackers.
There is a temptation to lump quantum computing in with technologies such as fusion power in the sense that both have been proposed for decades with the promise of tremendous leaps in performance.
Continue reading “Researchers Making Progress With Quantum Computing” »
I know that I reported on this a few weeks ago; however, this article shares some additional insights on how this new method will enable more efficient smaller devices including promoting stabilization in Quantum Computing (QC)…
A multi-institutional team of researchers has discovered novel magnetic behavior on the surface of a specialized material that holds promise for smaller, more efficient devices and other advanced technology.
Researchers at the Department of Energy’s Oak Ridge National Laboratory, Massachusetts Institute of Technology and their collaborators used neutron scattering to reveal magnetic moments in hybrid topological insulator (TI) materials at room temperature, hundreds of degrees Fahrenheit warmer than the extreme sub-zero cold where the properties are expected to occur.
Continue reading “Neutrons tap into magnetism in topological insulators at high temperatures” »
Movidius’ Myriad 2 vision processing chip (Photo: Movidius)
The branch of artificial intelligence called deep learning has given us new wonders such as self-driving cars and instant language translation on our phones. Now it’s about to injects smarts into every other object imaginable.
That’s because makers of silicon processors from giants such as Intel Corp. and Qualcomm Technologies Inc. as well as a raft of smaller companies are starting to embed deep learning software into their chips, particularly for mobile vision applications. In fairly short order, that’s likely to lead to much smarter phones, drones, robots, cameras, wearables and more.
Continue reading “AI-On-A-Chip Soon Will Make Phones, Drones And More A Lot Smarter” »
Google’s Project Soli was one of the highlights of the company’s developer conference last year, but there’s been little news about it since then.
The technology uses special radar-sensors packed in a tiny chip to detect a person’s physical movements (such as rubbing two fingers together), letting a person do things like turn the volume up on a radio without actual touching anything.
The recent news that Regina Dugan, the head of the Advanced Technology and Projects lab at Google that oversaw Soli, jumped ship to go work at rival Facebook, did not seem like a good sign for the future of Soli. And with Microsoft’s recent unveiling of similar technology, Google’s impressive product demo last year seemed like it might not make it out of the lab.
Continue reading “Google is quietly making progress on one of its most jaw-dropping tech projects” »
Harold Cohen, an abstract painter who developed Aaron, one of the first and eventually one of the most complex computer software programs for generating works of art, died on April 27 at his home in Encinitas, Calif. He was 87.
The cause was congestive heart failure, his son, Paul, said.
Mr. Cohen was a painter growing weary with the traditional practice of art in the late 1960s when he taught himself, out of curiosity, how to program a computer.
Continue reading “Harold Cohen, a Pioneer of Computer-Generated Art, Dies at 87” »
By David Glance Director of UWA Centre for Software Practice, University of Western Australia
Pharmaceutical companies typically develop new drugs with thousands of staff and budgets that run into the billions of dollars. One estimate puts the cost of bringing a new drug to market at $2.6 billion with others suggesting that it could be double that cost at $5 billion.
