Computing’s next revolution

Q&A: Adam Frank, astrophysicist

By Christie Nicholson

It’s almost as if we’re taking quantum mechanics down from the philosopher’s ladder and we are trying to make it practical?

Exactly. The interpretation of quantum mechanics has sort of lived for the last hundred years in the interstitial domain between physics and philosophy.
The paradox of quantum mechanics is we’ve had this theory for a hundred years, and we still don’t know how to visualize the world it’s describing. And that’s stunning to me.
Einstein had always hoped that underneath all the quantum weirdness we’d find that if you set the variables that would make all the weirdness of quantum mechanics go away.
So now where we’re headed is the possibility that quantum information theory will be able to probe deeper into these weirdnesses and tell us what’s going on.

Can you describe the practical and currently useful implications of quantum information for our day-to-day lives? This of course alludes to quantum computing and its possibilities.

Well first we need to know that the idea of superposition that we talked about earlier is one of the key pieces to making quantum computing work.
A computer functions with bits, that are either zero or one. [This is how information is translated within a computer’s operating system.] But with quantum computing, you’re using the inherent weirdness of quantum mechanics and using those superpositions. So now instead of a bit that’s a zero or one you have a so-called qubit, which can be both zero and one. That simple change leads to an enormous increase in computing power. One way of looking at a superposition is that you have possible worlds. And so what quantum computing does is that we can use those qubits [which can be both a zero and a one] and do calculations in all of the potentially possible worlds.

Wow, so it’s almost like super parallel processing.

Exactly. People have described it that way. It’s sort of like parallel processing in the other possible world.

But on a massive, massive scale.

Right. With quantum computing they can do huge calculations that would be literally be impossible even if you took the fastest computer today and waited the entire age of the universe, thirteen billion years, to solve a difficult problem. A quantum computer might be able to take a problem like that and compute it in a few days.

What will that mean for us?

In some sense quantum computing is the difference between an early computer game in 1982 and what we have today, and then multiply that by a trillion trillion trillion.

SmartPlanet

Robotic Arm Controlled by Thought

by Addy Dugdal | December 17, 2012

The project, funded in part by DARPA, allowed a tetraplegic woman to grasp and move objects around with the arm after she had two sensors implanted in her brain.

 A tetraplegic woman has successfully operated a robotic arm using her own brain power. Within two days of having a pair of sensors implanted in the motor cortex of her brain, reports The Lancet, 53-year-old Jan Scheuermann was able to move and grasp a number of objects using just her thoughts to control the arm. The breakthrough was made possibe by Professor Andrew B. Schwartz of the University of Pittsburgh's Neurobiology department, with help and funding from the Defense Advanced Research Projects Agency (DARPA), the Department of Veterans Affairs, the National Institutes of Health, and the UPMC Rehabilitation Institute.


The sensors, which measure 4 millimeters square, have 100 tiny needles on them to pick up the electrical activity from around 200 individual brain cells. These electrical pulses are then translated into commands to move the arm, described as "highly intuitive and probably responsible for the unprecedented performance of the brain-machine interface." Although the study was lab-based, researchers are trying to work out how to fix the arm to Ms Scheuerman's wheelchair in order for her to use it everyday.

Fast Company

A US Apple Factory May Be Robot City

dcblogs writes

First, a robot loads the aluminum block into the robo-machine that has a range of tools for cutting and drilling shapes to produce the complex chassis as a single precision part. A robot then unloads the chassis and sends it down a production line where a series of small, high-precision, high-speed robots insert parts, secured either with snap fit, adhesive bonds, solder, and a few fasteners, such as screws. At the end, layers, such as the display and glass, are added on top and sealed in another automated operation. Finally, the product is packaged and packed into cases for shipping, again with robots. "One of the potentially significant things about the Apple announcement is it could send a message to American companies — you can do this — you can make this work here," said Robert Atkinson, president of The Information Technology & Innovation Foundation."

Robots for iPad App

Robots for iPad is an app featuring the world's coolest robots. If you want to know how robotics is going to change the world, this app is for you.

The app, which is now available in Apple's App Store, includes 126 robots from 19 countries. I could go on and describe the main features, but I think the best way to see what the app is about is to watch this video.

Scientists See Promise in Deep-Learning Programs

By JOHN MARKOFF

Published: November 23, 2012 

 

The advances have led to widespread enthusiasm among researchers who design software to perform human activities like seeing, listening and thinking. They offer the promise of machines that converse with humans and perform tasks like driving cars and working in factories, raising the specter of automated robots that could replace human workers.

The technology, called deep learning, has already been put to use in services like Apple’s Siri virtual personal assistant, which is based on Nuance Communications’ speech recognition service, and in Google’s Street View, which uses machine vision to identify specific addresses.

But what is new in recent months is the growing speed and accuracy of deep-learning programs, often called artificial neural networks or just “neural nets” for their resemblance to the neural connections in the brain.

“There has been a number of stunning new results with deep-learning methods,” said Yann LeCun, a computer scientist at New York University who did pioneering research in handwriting recognition at Bell Laboratories. “The kind of jump we are seeing in the accuracy of these systems is very rare indeed.”

Artificial intelligence researchers are acutely aware of the dangers of being overly optimistic. Their field has long been plagued by outbursts of misplaced enthusiasm followed by equally striking declines.

In the 1960s, some computer scientists believed that a workable artificial intelligence system was just 10 years away. In the 1980s, a wave of commercial start-ups collapsed, leading to what some people called the “A.I. winter.”

But recent achievements have impressed a wide spectrum of computer experts. In October, for example, a team of graduate students studying with the University of Toronto computer scientist Geoffrey E. Hinton won the top prize in a contest sponsored by Merck to design software to help find molecules that might lead to new drugs.

From a data set describing the chemical structure of 15 different molecules, they used deep-learning software to determine which molecule was most likely to be an effective drug agent.

The achievement was particularly impressive because the team decided to enter the contest at the last minute and designed its software with no specific knowledge about how the molecules bind to their targets. The students were also working with a relatively small set of data; neural nets typically perform well only with very large ones.

“This is a really breathtaking result because it is the first time that deep learning won, and more significantly it won on a data set that it wouldn’t have been expected to win at,” said Anthony Goldbloom, chief executive and founder of Kaggle, a company that organizes data science competitions, including the Merck contest.

 WP

IBM supercomputer simulates 530 billion neurons

By Mat Smith posted Nov 20th, 2012 

IBM Research, in collaboration with DARPA's Systems of Neuromorphic Adaptive Plastic Scalable Electronics (SyNAPSE) program, has reached another brain simulation milestone. Powered by its new TrueNorth system on the world's second faster supercomputer, IBM was capable of crafting a 2.084 billion neurosynaptic cores and 100 trillion synapses -- all at a speed "only" 1,542 times slower than real life. The abstract explains that this isn't a biologically realistic simulation of the human brain, but rather mathematically abstracted -- and little more dour -- versions steered towards maximizing function and minimizing cost. DARPA's SyNAPSE project aims to tie together supercomputing, neuroscience and neurotech for a future cognitive computing architecture far beyond what's running behind your PC screen at the moment.

engadget

 

US Patent Office Issues FractoGene Patent

 
Happy for my friend Andras Pellionisz, who was granted a patent this week for his pioneering work in genetics.

His tensor network theory became a touchstone for a generation of people in neuroscience, and is fundamental to my own efforts. (PDF)

Andras has made a career of being ahead of his time. Developments from the last few years have vindicated his views on 'Junk' DNA and fractal genetics.

Here's an excerpt from the press release:

Sunnyvale, CA (PRWEB) October 02, 2012 

US Patent Office Issues FractoGene Patent 8,280,641

Recognizes breakthrough research; validates business model.

This method and system is critical to the application of industrial genomics in clinical settings, most especially in the fight against cancer. The computation of genomic fractal defects can parse individual diversity from pathology, and thus represents a quantum leap in early diagnosis, personal therapy, and genome-based drug development.

Pursuant to decades of research in applying mathematics to neuroscience and genomics, Pellionisz, who has three doctoral degrees, submitted his provisional application on August 1st, 2002. Recognition by the US government may well have been delayed due to its cross-disciplinary nature. The greatest hurdle was most likely the required paradigm shift — moving from the “Junk DNA” model to a fractal iterative recursion paradigm, which was initially perceived by many as a “lucid heresy.”

The status quo began to give way a few years ago, beginning with the results from the ENCODE Project, when in 2007 its leader Francis Collins urged the scientific community to “re-think long held fundamentals.” Such progress was made in Pellionisz’s presentation at George Church’s meeting in Cold Spring Harbor, Sept. 16, 2009. Another landmark was the publication by Eric Lander et al. in the Oct. 9, 2009 of Science, featuring the Hilbert-fractal of a genome on the cover.

“A protracted period of examination was costly and occasionally painful, but the issue could not be better timed for deployment,” said Pellionisz. He was delighted that legal recognition arrived via an “Issue Notification,” dated September 12, 2012. It was a heady time. The notice came less than a week after the release of 30+ papers from ENCODE on September 6th, 2012 — again concluding that “Junk DNA” was a myth.

Press release

The Human Connectome Project

Navigate the brain in a way that was never before possible; fly through major brain pathways, compare essential circuits, zoom into a region to explore the cells that comprise it, and the functions that depend on it.

The Human Connectome Project aims to provide an unparalleled compilation of neural data, an interface to graphically navigate this data and the opportunity to achieve never before realized conclusions about the living human brain.

New front in "open access" science publishing row

By Chris Wickham

LONDON (Reuters) - The genteel but lucrative world of academic publishing is being stirred up by a dispute over who pays for and who profits from scientific research funded largely by taxpayers.
Scientists' careers are made, and broken, by the quality and volume of articles describing new discoveries that they publish in top journals like Nature, Science and Cell.
And it's big business, with the market in academic journals worth about $8 billion a year globally, according to analyst estimates.
A new low-cost scientific journal unveiled on Tuesday with an unusual business model will add to the pressure on publishers like Reed Elsevier and Axel Springer and stoke the debate over free access to research.
The founders of the new journal, called PeerJ, come with a pedigree. Peter Binfield previously worked for PLoS One, the most successful part of the not-for-profit Public Library of Science, which has pioneered open access to scientific papers, and Jason Hoyt comes from the research database group Mendeley.
It is backed by venture capitalist Tim O'Reilly and will publish research in biological and medical sciences using a revenue model based on a one-off payment ranging from $99 to $259 for lifetime membership per researcher, rather than payment per paper or subscription by readers.

DEBATE AND BOYCOTT
Supporters of so-called 'open access' publishing, including about 12,000 researchers who have joined a boycott of the world's biggest academic publisher Elsevier, argue the subscription publishers are profiteering.
Open access players charge the researcher but access is free and unrestricted upon publication.
Research published in top journals sits behind a pay wall. But their content is provided largely for free by scientists and peer-reviewed by unpaid academics, with the journals then sold to those same academics via their university libraries for thousands of dollars per year.

Quantum Biology

 

The mathematical machinery of quantum mechanics 

became that of spectral analysis…  ~Steen

“Leading thinkers in the emerging field of quantum biology explored the hidden hand of quantum physics on the scales of everyday life.”

This is clearly an introductory look at the subject, and so we don’t explore quantum theory to any real depth, here, but … At this date, do we really need to have Penrose dismissed with a superior smile? As though that were an argument of some kind? And not simply a not-so-subtle appeal to the hive mind? Similarly, the little joke about “consciousness” being the “C word” may have lost its bloom after several decades of repetition.

I have my differences with Sir Roger, but he did what no one else had been able to do when he argued for a quantum basis for mind — and that required balls, back then. Stapp, Lockwood, and I had made the case for a quantum approach before he came along, as had several of the founders of QM and a number of philosophers. Penrose put us on the map, however, owing to his great prestige. Moreover, he gave us a fairly clear picture to argue against — itself an important contribution, as a glance at the history of science will attest.

The smirking humor concerning consciousness is a fig leaf tasked with covering a vast ignorance. Yes, consciousness is mysterious, but science is commonly supposed to be about exploring mysteries, or so I seem to recall. How can we lift the veil?

Perception is a large part of consciousness and perception is quite mechanical. Thus, we get up in the morning and the world looks, sounds, tastes and feels the way it usually does. Where there are differences, those differences can be traced to physical causes.

Helmholtz observed that “Similar light produces, under like conditions, a like sensation of color.” Color is, of course, one of Locke’s “secondary qualities.” Generalizing with a view to Heisenberg’s formulation of quantum mechanics, we can say that:

The same state vector, acted upon by the same operators A, B, C … produces the same spectrum of secondary qualities.

On this view, our sensory organs act as projection operators when they resonate with the state vector. In the case of color vision, our photopigments act like pieces of stained glass, where red glass, e.g., appears red because it absorbs the other colors but transmits red.

The fact that the world looks, sounds, tastes and feels the way it usually does from day to day stems from the fact that the secondary qualities respect important physical symmetries of the kind embodied in gauge theory. Moreover, we know that the appearance of color and sound is reliably related to the phase behavior of the related waves/vectors.

A little thought reveals that these “secondary” variables are only “hidden” in plain sight and so solves a mystery common to “hidden variables” theories and Kaluza-Klein theories — i.e., if these extra variables or dimensions exist, why do we not “see” them? It is as Wittgenstein observed: “The aspects of things that are most important for us are hidden because of their simplicity and familiarity.”

Now, that wasn’t so hard, was it?

Whores & thieves

 Elsevier, Springer and the monstrous farce of scientific publishing

SOMETIMES it takes but a single pebble to start an avalanche. On January 21st Timothy Gowers, a mathematician at Cambridge University, wrote a blog post outlining the reasons for his longstanding boycott of research journals published by Elsevier. This firm, which is based in the Netherlands, owns more than 2,000 journals, including such top-ranking titles as Cell and the Lancet. However Dr Gowers, who won the Fields medal, mathematics’s equivalent of a Nobel prize, in 1998, is not happy with it, and he hoped his post might embolden others to do something similar.
It did. More than 2,700 researchers from around the world have so far signed an online pledge set up by Tyler Neylon, a fellow-mathematician who was inspired by Dr Gowers’s post, promising not to submit their work to Elsevier’s journals, or to referee or edit papers appearing in them. That number seems, to borrow a mathematical term, to be growing exponentially. If it really takes off, established academic publishers might find they have a revolution on their hands.

[...]

This situation has been simmering for years. In 2006, for example, the entire editorial board of Topology, a mathematics journal published by Elsevier, resigned, citing similar worries about high prices choking off access. And the board of K-theory, a maths journal owned by Springer, a German publishing firm, quit in 2007.
To many, it is surprising things have taken so long to boil over.

 Springer offered to publish my book on Quanta & Consciousness, recently. It rapidly became clear that they were bent on swindling me, however. I won't repeat my colorful reply to them here, but believe me when I say it was the kind of thing normally reserved for cleaning the hull of a battleship.