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Category: computing – Page 837

Aging, Just Another Disease

Aging leads to diseases and ultimately death. Time for people to ditch the semantics and recognise that aging and disease are not two mysterious independent processes but are in fact one and the same.

Aging leads to the diseases of aging and the discussion is largely a matter of semantics.

“The concept of aging is undergoing a rapid transformation in medicine. The question has long been asked: Is aging a natural process that should be accepted as inevitable, or is it pathologic, a disease that should be prevented and treated? For the vast majority of medicine’s history, the former position was considered a self-evident truth. So futile was any attempt to resist the ravages of aging that the matter was relegated to works of fantasy and fiction. But today, the biomedical community is rethinking its answer to this question.

The controversy has been fanned, to a great extent, by one Aubrey de Grey, a Cambridge University–trained computer scientist and a self-taught biologist and gerontologist. Over the past decade, de Grey has undertaken an energetic campaign to reframe aging as a pathologic process, one that merits the same level of attention as, say, cancer or diabetes.”

#aging #sens

Would You Like to Be Uploaded to a Computer When You Die?

Rattling around inside a hard drive doesn’t sound like an awful lot of fun — but then, neither does death.

Both eventualities are rather difficult to imagine, but we’ll all have to give them some thought sooner rather than later. Neuroscientist and neuroengineer Randal Koene thinks it’s only going to be another 10 years before we replace parts of the brain with prosthetics.

From there, it’s just a matter of replacing each region systematically, to end up with someone whose brain is immortal and electronic. Could the last person to die have already been born?

Edmonton researchers’ tiny discovery may revolutionize computers

New method for creating smaller switches for QC identified and making smaller and more efficient QC systems possible.

Edmonton nanotechnology researchers working with atom-sized materials have made a breakthrough that could lead to smaller, ultraefficient computers.

The team, led by Robert Wolkow, together with collaborators at the Max Planck Institute in Hamburg, have developed a way to create atomic switches for electricity nearly 100 times smaller than the smallest switches, or transistors, on the market today. Their findings appeared in the Oct. 26 edition of the scientific publication Nature Communications.

“What we’re showing in this new paper is one part in a bigger scheme … that allows us to make ultralow power consuming electronic devices,” said Wolkow, a physics professor at the University of Alberta and the principal research officer at Edmonton’s National Institute for Nanotechnology. He’s also chief technology officer at spinoff company Quantum Silicon Inc.

Tiny Computer Pushes the Envelope with Micro-Memory

Talk about downsizing – researchers at the University of California in Santa Barbara have developed a design for a 50 nanometer square computer, the university announced Oct. 27.

For now, that size is entirely theoretical. It could be managed by a novel kind of logic that enables the computer to process data inside a three-dimensional structure.

“In a regular computer, data processing and memory storage are separated, which slows down computation. Processing data directly inside a three-dimensional memory structure would allow more data to be stored and processed much faster,” said Gina Adam, a postdoctoral researcher and the lead author of the paper.

Toward Handheld QCL Sensors

In the TU Wien design, quantum cascade heterostructures are arrayed within concentric ring-shaped waveguides (top; diameter of outer ring is 400 microns), and can act as both sources and detectors of light on the same chip. In the specific setup tested by the lab (bottom), one of the ring structures (on the right), acting in QCL mode, sends its light through a chamber containing the gas to be analyzed. The beam is reflected by a mirror (on the left) and sent back through the chamber, to be picked up by the other ring structure, acting in detector mode. [Image: TU Wien]

Quantum cascade lasers (QCL) excel as mid-infrared light sources, a characteristic that has made them a linchpin in many environmental and industrial gas-sensing applications. But though QCLs themselves can be quite small, actually setting up a sensor system requires other elements beyond the laser, which can make it tough to design compact devices ready for field use.

A team of scientists from the Vienna University of Technology (TU Wien), Austria, now offers a concept that the group believes could make designing handheld QCL-based sensors a lot easier. The key: a clever scheme that combines the laser and the detector on a single chip less than half a millimeter across (ACS Photon., doi: 10.1021/acsphotonics.6b00603).

A Tiny Machine: UCSB electrical and computer engineers design an infinitesimal computing device

Abstract: In 1959 renowned physicist Richard Feynman, in his talk “Plenty of Room at the Bottom,” spoke of a future in which tiny machines could perform huge feats. Like many forward-looking concepts, his molecule and atom-sized world remained for years in the realm of science fiction.

And then, scientists and other creative thinkers began to realize Feynman’s nanotechnological visions.

In the spirit of Feynman’s insight, and in response to the challenges he issued as a way to inspire scientific and engineering creativity, electrical and computer engineers at UC Santa Barbara have developed a design for a functional nanoscale computing device. The concept involves a dense, three-dimensional circuit operating on an unconventional type of logic that could, theoretically, be packed into a block no bigger than 50 nanometers on any side.

No Technology Thrives Alone: Progress Is All About Convergence

15 years ago, Ray Kurzweil published one of the most significant essays in the history of futurism: “The Law of Accelerating Returns.” This piece showcased the immense power of exponential technology versus linear technology and became a pivotal concept for anyone trying to anticipate what the future held.

The essay predicted advances in business and technology with eerie precision, including how exponential growth would ripple through any technology that became an information technology, such as computing, biotechnology, or energy.

[ Go here to learn more about the law of accelerating returns ]

Breaking into the Simulated Universe

I argued in my 2015 paper “Why it matters that you realize you’re in a Computer Simulation” that if our universe is indeed a computer simulation, then that particular discovery should be commonplace among the intelligent lifeforms throughout the universe. The simple calculus of it all being (a) if intelligence is in part equivalent to detecting the environment (b) the environment is a computer simulation © eventually nearly all intelligent lifeforms should discover that their environment is a computer simulation. I called this the Savvy Inevitability. In simple terms, if we’re really in a Matrix, we’re supposed to eventually figure that out.

Silicon Valley, tech culture, and most nerds the world over are familiar with the real world version of the question are we living in a Matrix? The paper that’s likely most frequently cited is Nick Bostrom’s Are you living in a Computer Simulation? Whether or not everyone agrees about certain simulation ideas, everyone does seem to have an opinion about them.

Recently, the Internet heated up over Elon Musk’s comments at a Vox event on hot tub musings of the simulation hypothesis. Even Bank of America published an analysis of the simulation hypothesis, and, according to Tad Friend in an October 10, 2016 article published in New Yorker, “two tech billionaires have gone so far as to secretly engage scientists to work on breaking us out of the simulation.”

Nightmare Machine at CSIRO is slowly but surely learning how to terrify humans

Story just in time for Halloween.

The prospect of artificial intelligence is scary enough for some, but Manuel Cebrian Ramos at CSIRO’s Data61 is teaching machines how to terrify humans on purpose.

Dr Cebrian and his colleagues Pinar Yanardag and Iyad Rahwan at the Massachusetts Institute of Technology have developed the Nightmare Machine.

This is an artificial intelligence algorithm that is teaching a new generation of computers not only what terrifies human beings, but also how to create new images to scare us.