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Power consumption is one of the biggest reasons why you haven’t seen a brain-like computer beyond the lab: the artificial synapses you’d need tend to draw much more power than the real thing. Thankfully, realistic energy use is no longer an unattainable dream. Researchers have built nanowire synapses that consume just 1.23 femtojoules of power — for reference, a real neuron uses 10 femtojoules. They achieve that extremely low demand by using a wrap of two organic materials to release and trap ions, much like real nerve fibers.

There’s a lot of work to be done before this is practical. The scientists want to shrink their nanowires down from 200 nanometers thick to a few dozen, and they’d need new 3D printing techniques to create structures that more closely imitate real brains. Nonetheless, the concept of computers with brain-level complexity is that much more realistic — the team tells Scientific American that it could see applications in everything from smarter robots and self-driving cars through to advanced medical diagnosis.

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IBM and marketing company The Drum just announced that the AI Watson was able to edit an entire magazine on its own. This showcases the computing potential that AI has in an increasing number of fields.

IBM and a marketing company called The Drum just announced that the AI system known as Watson was able to edit an entire magazine on its own. Yep, an AI magazine editor.

According to a statement released via The Drum, the magazine edited by Watson contains different features that shows Watson’s capabilities. It has different analytical functions, as well as skills necessary to assist modern-day marketers. Also, Watson has been programmed to have the capacity to answer a series of questions about David Olgivy, the “advertising legend,” and was able to give some predictions for the winners of this year’s Cannes Lions awards.

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Glad to see others finding value in using Q-Dots with Graphene.


The development of photodetectors has been a matter of considerable interest in the past decades since their applications are essential to many different fields including cameras, medical devices, safety equipment, optical communication devices or even surveying instruments, among others.

Many efforts have been focused towards optoelectronic research in trying to create low cost photodetectors with high sensitivity, high quantum efficiency, high gain and fast photoresponse. This is of paramount importance especially in the short wave infrared which currently is addressed by very expensive III-V InGaAs photodetectors. The development of two main classes of photodetectors, photodiodes and phototransistors, have partially been able to accomplish these goals because even though they both have many outstanding properties, none seem to fulfill all of these requirements. While photodiodes are much faster than phototransistors, phototransistors have a higher gain and do not require low noise preamplifiers for their use.

To overcome these limitations, ICFO researchers Ivan Nikitskiy, Stijn Goossens, Dominik Kufer, Tania Lasanta, Gabriele Navickaite, led by ICREA professors at ICFO Frank Koppens and Gerasimos Konstantatos, have been able to develop a hybrid photodetector capable of attaining concomitantly better performance features in terms of speed, quantum efficiency and linear dynamic range, operating not only in the visible but also in the near infrared (NIR: 700-1400nm) and SWIR range (1400-3000nm). At the same time this technology is based upon materials that can be monolithically integrated with Si CMOS electronics as well as flexible electronic platforms. The results of this work have been recently published in Nature Communications.

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My new Psychology Today story on BREXIT and the EU:


Scientific innovation doesn’t just happen on its own. It takes stable economies, free societies, and open-minded governments. The best environment for science to thrive in is that of collaborating groups incentivized to communicate and cooperate with one another. This is precisely what the European Union is.

And now, more than ever, the union of Europe is needed—because we are crossing over into the transhumanist age, where radical science and technology will engulf our lives and challenge our institutions. Robots will take 75% of the jobs in the next 25 years. CRISPR gene editing technology will allow us to augment our intelligence, perhaps doubling our IQ. Bionic organs will stave off death, allowing 200 year lifespans.

The science and technology coming in just the next two decades will cause unprecedented challenges to humanity. Most of the world will get chip implants— I have one —to assist with quick payments, emergency tracking, and to replace archaic accessories like car keys. We’ll also all use genetic therapies to cure cancer, heart disease, Alzheimer’s, and even aging. And robots will be ubiquitous—driving us everywhere, homeschooling our children, and maybe even becoming preferred sexual partners.

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(Phys.org)—Inspired by natural selection and the concept of “survival of the fittest,” genetic algorithms are flexible optimization techniques that can find the best solution to a problem by repeatedly selecting for and breeding ever “fitter” generations of solutions.

Now for the first time, researchers Urtzi Las Heras et al. at the University of the Basque Country in Bilbao, Spain, have applied genetic algorithms to digital and shown that genetic algorithms can reduce quantum errors, and may even outperform existing optimization techniques. The research, which is published in a recent issue of Physical Review Letters, was led by Ikerbasque Prof. Enrique Solano and Dr. Mikel Sanz in the QUTIS group.

In general, quantum simulations can provide a clearer picture of the dynamics of systems that are impossible to understand using conventional computers due to their high degree of complexity. Whereas computers calculate the behavior of these systems, quantum simulations approximate or “simulate” the behavior.

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Forget pitching a tent when camping; soon (at this rate) we can have the 3D Printer print us a cabin.


A tiny house was built using Vesta, the 3D concrete printer. It took 24 hours to build the structure. The developer aims to shorten the construction time with the third version of the device.

Vesta, the 3D concrete printer, was just used to print a house. Though the word “house” may be a little suspect. Admittedly, given its size, the structure is more of a tool shed than a home, but one could theoretically live inside of it.

The structure took 24 hours to print and boasts a 2 × 1 square meter (7 × 4 square feet) interior. The printer is able to work at a speed of about .3 feet per second and only requires a single person to operate from a computer and feed the printer concrete.

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Excellent story and highlights how Quantum computers may provide a way to overcome the obstacles around particle physics because QC can simulate certain aspects of elementary particle physics in a well-controlled quantum system.


Physicists in Innsbruck have realized the first quantum simulation of lattice gauge theories, building a bridge between high-energy theory and atomic physics. In the journal Nature, Rainer Blatt’s and Peter Zoller’s research teams describe how they simulated the creation of elementary particle pairs out of the vacuum by using a quantum computer.

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Entanglement purification, a vital enabler for practical quantum networks, has been shown to be feasible with secluded nuclear memories in diamond.

Quantum devices can team up to perform a task collectively, but only if they share that most “spooky” of all quantum phenomena: entanglement. Remote devices have been successfully entangled in order to investigate entanglement itself [1], but the entanglement’s quality is too low for practical applications. The solution, known as entanglement purification [2], has seemed daunting to implement in a real device. Now new research [3] shows that even quite simple quantum components—nanostructures in diamond—have the potential to store and upgrade entanglement. The result relies on hiding information in almost-inaccessible nuclear memories, and may be a key step toward the era of practical quantum networks.

The concept of an interlinked network is absolutely fundamental to conventional technologies. It applies not only to distributed systems like the internet, but also to individual devices like laptops, which contain a hierarchy of interlinked components. For quantum technologies to fulfill their potential, we will want them to have the flexibility and scalability that come from embracing the network paradigm.

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Northwestern University’s Ken Forbus is closing the gap between humans and machines.

Using cognitive science theories, Forbus and his collaborators have developed a model that could give computers the ability to reason more like humans and even make moral decisions. Called the structure-mapping engine (SME), the new model is capable of analogical problem solving, including capturing the way humans spontaneously use analogies between situations to solve .

“In terms of thinking like humans, analogies are where it’s at,” said Forbus, Walter P. Murphy Professor of Electrical Engineering and Computer Science in Northwestern’s McCormick School of Engineering. “Humans use relational statements fluidly to describe things, solve problems, indicate causality, and weigh moral dilemmas.”

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