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The key to this all working is the design of the nanostructures. If you just have a laser in free space, the particle will just oscillate back and forth, pushing it one way and then the other. It won’t ever gain in total energy. So you need some kind of structure that channels or modulates the fields in such a way that the particle will travel along mainly the peaks of the electromagnetic wave and not into the troughs so that it gets kicks but not deceleration.

In all of the experiments done so far, England explains that the particles are basically filling the whole wave, occupying and seeing both the peaks and troughs. This results in some particles being accelerated while others get decelerated.

“In the future, as one of the next experimental steps what we want is to bunch the particles to make very short little packets of particles that are spaced at exactly the right distance between the peaks so that they will ride only on the peaks,” says England. “So you can think of it as like… ocean waves, and you want your surfers to be positioned only on the peaks of the waves and not in the troughs.”

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The US wants to stay in front of China with hypersonic weapons able to travel at five-times the speed of sound and destroy targets with a “kinetic energy” warhead.

Air Force weapons developers expect to operate hypersonic intelligence, reconnaissance and surveillance drones by the 2040s, once scientific progress with autonomy and propulsion technology matures to a new level.

The advent of using a recoverable drone platform able to travel at high altitudes, faster than Mach 5, will follow the emergence of hypersonic weapons likely to be operational in the mid-2020s, according to the Air Force Chief Scientist Geoffrey Zacharias.

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For the first time ever, a single flexible fiber no bigger than a human hair has successfully delivered a combination of optical, electrical, and chemical signals back and forth into the brain, putting into practice an idea first proposed two years ago. With some tweaking to further improve its biocompatibility, the new approach could provide a dramatically improved way to learn about the functions and interconnections of different brain regions.

The new fibers were developed through a collaboration among material scientists, chemists, biologists, and other specialists. The results are reported in the journal Nature Neuroscience, in a paper by Seongjun Park, an MIT graduate student; Polina Anikeeva, the Class of 1942 Career Development Professor in the Department of Materials Science and Engineering; Yoel Fink, a professor in the departments of Materials Science and Engineering, and Electrical Engineering and Computer Science; Gloria Choi, the Samuel A. Goldblith Career Development Professor in the Department of Brain and Cognitive Sciences, and 10 others at MIT and elsewhere.

The fibers are designed to mimic the softness and flexibility of brain tissue. This could make it possible to leave implants in place and have them retain their functions over much longer periods than is currently possible with typical stiff, metallic fibers, thus enabling much more extensive data collection. For example, in tests with lab mice, the researchers were able to inject viral vectors that carried genes called opsins, which sensitize neurons to light, through one of two fluid channels in the fiber. They waited for the opsins to take effect, then sent a pulse of light through the optical waveguide in the center, and recorded the resulting neuronal activity, using six electrodes to pinpoint specific reactions. All of this was done through a single flexible fiber just 200 micrometers across — comparable to the width of a human hair.

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Artificial intelligence has reached peak hype. News outlets report that companies have replaced workers with IBM Watson and that algorithms are beating doctors at diagnoses. New AI startups pop up everyday, claiming to solve all your personal and business problems with machine learning.

Ordinary objects like juicers and Wi-Fi routers suddenly advertise themselves as “powered by AI.” Not only can smart standing desks remember your height settings, they can also order you lunch.

Much of the AI hubbub is generated by reporters who’ve never trained a neural network and by startups or those hoping to be acqui-hired for engineering talent despite not having solved any real business problems. No wonder there are so many misconceptions about what AI can and cannot do.

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Thanks for your interest!

Thanks to SAP Italia for making this video available, the original video is at https://youtu.be/PLS5wGAM3R8 You can download all my slides at www.gerdcloud.net; direct link to the slides used here is gerd.fm/sapitaliagerd

In this talk, I address the opportunities and challenges of exponential transformation, the coming convergence of man and machine, the changes coming to society, work and jobs, the 10 megashifts, and what it takes to lead into this future responsible and openly.

If you enjoy my videos and talks, please take a look at my new book “Technology vs Humanity” http://www.techvshuman.com or buy it via Amazon http://gerd.fm/globalTVHamazon

What’s Watson working on today? He’s working with 1–800-Flowers to help find the perfect bouquet out of trillions of combinations. He’s working with the New York Genome Center to help doctors find treatments as personal as DNA. And he’s working with Sesame Street to make education as unique as every child.

Working with Watson, we can outthink anything. http://ibm.co/2bTJ7BY

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Watson, IBM’s cognitive computing system, exhibited phenomenal capabilities while competing on the television quiz show Jeopardy! in February 2011. The grand debut and triumph at Jeopardy! drew the world’s attention to Watson, which achieved a milestone in artificial intelligence (AI) while denoting a new era in computing – a cognitive era. Six years later, Watson today seems to be everywhere, revolutionizing diverse industries while building IBM’s cognitive future.

Cognitive Computing Explained

The future of technology is radically different from the systems that have dominated the global IT industry for decades. New generation technologies are broadly grouped together using the terms AI and cognitive technologies. At IBM, these advanced techs are referred to as cognitive and defined as “systems that learn at scale, reason with purpose and interact with humans naturally.”

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Google announced that it will be turning to machine learning to help it identify objectionable content, which caused over 250 brands to freeze their ad spend with YouTube and Google display.

In a statement provided to Business Insider, Google said the new tools will “help enforce our revised policies and identify content that may be objectionable to advertisers.”

Google said it would also be offering brand safety reporting by working with third party partners, like Integral Ad Science and comScore.

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