Lifeboat Foundation

Gravitational waves captured by space-based detectors could help identify the origins of supermassive black holes, according to new computer simulations of the universe.

We now have a way to do tracibility in QC.

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Chinese scientists won a major victory recently, by proving that the Majorana fermion — a particle we’ve found tantalizing hints of for years — genuinely exists. This discovery has huge implications for quantum computing, and it might change the world. But how?

Continue reading “How The Majorana Fermion Is Going To Change The World” »

This video is worthless. I hear a person who is out of touch with the QC work and isn’t even aware all of the work going on. Frankly, QC is being worked on by big tech (Amazon, Google, Microsoft, D-Wave, IBM), governmental labs and incubators, limited set of start ups who are also (in many cases tied to big tech), and university research labs. Therefore, I don’t really find this soapbox video that informative as well as not in touch with where QC is today. It appears to me that this guy has sour grapes over not being engaged.

At least if you’re going to get on a soapbox and try to talk about QC like you’re somehow an expert or informed; at least make sure you know what has been shown, reported, and in development currently that has been publically announced so that you don’t look like you’re an un-informed consultant doing a superficial presentation and didn’t even bother doing the due diligence 1st. Otherwise, you just discredited your VC/ firm to the public and to those working on QC.

Continue reading “Quantum Computing: A Primer” »

Nice.

Quantum computing makes small, but significant progress.

A high-energy physics experiment has been completed using a simple quantum device that, if scaled up, could potentially greatly outperform a conventional computer.

Continue reading “Experimental quantum computer manages first high-energy physics simulation” »

It would seem that no one’s immune from the effects imposed by our increasingly sophisticated artificial intelligence and robotics — not even doctors. As research from Indiana University has revealed, a new computer program is doing a better job than doctors when it comes to both diagnosing and treating health conditions — and by a significant margin.

The system, which uses decision making processes similar to the Jeopardy-bot, Watson, was recently given the task of analyzing and predicting the health outcomes of 500 real individuals. After plugging in the relevant data — which mostly had to do with clinical depression and chronic diseases like high blood pressure and diabetes — researchers Kris Hauser and Casey Bennett compared the outcomes to the simulated treatment prescriptions.

A transistor, conceived of in digital terms, has two states: on and off, which can represent the 1s and 0s of binary arithmetic.

But in analog terms, the transistor has an infinite number of states, which could, in principle, represent an infinite range of mathematical values. Digital computing, for all its advantages, leaves most of transistors’ informational capacity on the table.

In recent years, analog computers have proven to be much more efficient at simulating biological systems than digital computers. But existing analog computers have to be programmed by hand, a complex process that would be prohibitively time consuming for large-scale simulations.

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.

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.

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.

Continue reading “A new form of hybrid photodetectors with quantum dots and graphene” »