Updated 9/16/14 10:15am: Clarified calculations and added footnote
We humans like to think ourselves pretty advanced – and with no other technology-bearing beings to compare ourselves to, our back-patting doesn’t have to take context into account. After all, we harnessed fire, invented stone tools and the wheel, developed agriculture and writing, built cities, and learned to use metals.
Then, a mere few moments ago from the perspective of cosmic time, we advanced even more rapidly, developing telescopes and steam power; discovering gravity and electromagnetism and the forces that hold the nuclei of atoms together.
Meanwhile, the age of electricity was transforming human civilization. You could light up a building at night, speak with somebody in another city, or ride in a vehicle that needed no horse to pull it, and humans were very proud of themselves for achieving all of this. In fact, by the year 1899, purportedly, these developments prompted U.S. patent office commissioner Charles H. Duell to remark, “Everything that can be invented has been invented.”
We really have come a long way from the cave, but how far can we still go? Is there a limit to our technological progress? Put another way, if Duell was dead wrong in the year 1899, might his words be prophetic for the year 2099, or 2199? And what does that mean for humanity’s distant future?
In 1971—16 years after Einstein’s death—the definitive experiment to test Einstein’s relativity was finally carried out. It required not a rocket launch but eight round-the-world plane tickets that cost the United States Naval Observatory, funded by taxpayers, a total of $7,600.
The brainchild of Joseph Hafele (Washington University in St. Louis) and Richard Keating (United States Naval Observatory) were “Mr. Clocks,” passengers on four round-the-world flights. (Since the Mr. Clocks were quite large, they were required to purchase two tickets per flight. The accompanying humans, however, took up only one seat each as they sat next to their attention-getting companions.)
The Mr. Clocks had all been synchronized with the atomic clock standards at the Naval Observatory before flight. They were, in effect, the “twins” (or quadruplets, in this case) from Einstein’s famous twin paradox, wherein one twin leaves Earth and travels nearly at the speed of light. Upon returning home, the traveling twin finds that she is much younger than her earthbound counterpart.
In fact, a twin traveling at 80 percent the speed of light on a round-trip journey to the Sun’s nearest stellar neighbor, Proxima Centauri, would arrive home fully four years younger than her sister. Although it was impossible to make the Mr. Clocks travel at any decent percentage of the speed of light for such a long time, physicists could get them going at jet speeds—about 300 meters (0.2 mile) per second, or a millionth the speed of light—for a couple of days. In addition, they could get the Mr. Clocks out of Earth’s gravitational pit by about ten kilometers (six miles) relative to sea level. And with the accuracy that the Mr. Clocks were known to be capable of, the time differences should be easy to measure.
This article was originally published on The Conversation.
One of the problems with using passwords to prove identity is that passwords that are easy to remember are also easy for an attacker to guess, and vice versa.
Nevertheless, passwords are cheap to implement and well understood, so despite the mounting evidence that they are often not very secure, until something better comes along they are likely to remain the main mechanism for proving identity.
But maybe something better has come along. In research published in PeerJ, Rob Jenkins from University of York and colleagues propose a new system based on the psychology of face recognition called Facelock. But how does it stack up against existing authentication systems?
This article was originally published on The Conversation.
After years of trying, it looks like a chatbot has finally passed the Turing Test. Eugene Goostman, a computer program posing as a 13-year old Ukrainian boy, managed to convince 33% of judges that he was a human after having a series of brief conversations with them. (Try the program yourself here.)
Most people misunderstand the Turing test, though. When Alan Turing wrote his famous paper on computing intelligence, the idea that machines could think in any way was totally alien to most people. Thinking – and hence intelligence – could only occur in human minds.
Turing’s point was that we do not need to think about what is inside a system to judge whether it behaves intelligently. In his paper he explores how broadly a clever interlocutor can test the mind on the other side of a conversation by talking about anything from maths to chess, politics to puns, Shakespeare’s poetry or childhood memories. In order to reliably imitate a human, the machine needs to be flexible and knowledgeable: for all practical purposes, intelligent.
The problem is that many people see the test as a measurement of a machine’s ability to think. They miss that Turing was treating the test as a thought experiment: actually doing it might not reveal very useful information, while philosophizing about it does tell us interesting things about intelligence and the way we see machines.
Excerpted from You Are Here by Hiawatha Bray
These days new smartphone apps all seem to want the same thing from us—our latitude and longitude. According to a 2012 report from the Pew Research Center’s Internet and American Life Project, three-quarters of America’s smartphone owners use their devices to retrieve information related to their location—driving directions, dining suggestions, weather updates, the nearest ATM. Such location data is a boon to advertisers, who use information on our movements to discern our habits and interests, and then target ads to us.
With location-aware smartphones, advertisers can transcend the merely local. They can begin beaming us hyperlocal advertising, tailored not just to the city, but to a particular city block. The idea is called “geofencing,” an unfortunate name choice that evokes the ankle bracelets sometimes worn by accused criminals under constant surveillance. The earliest such devices fenced in the user by transmitting a radio signal to a box connected to his home telephone line. If the suspect left the building, the radio signal would fade, and the box would place an automated phone call to the cops.
With the addition of GPS and cellular technology, later versions of ankle bracelet technology allowed a greater measure of mobility. A judge might grant a criminal suspect permission to go to her job, her church, and her local supermarket, with each approved location plugged into the court’s computer system. Data from the ankle-strapped GPS could confirm that the suspect was staying out of mischief or send a warning to police when she paid an unauthorized visit to the local dive bar.
Geofencing also has uses for the law abiding. A company called Life360 uses it to help parents keep tabs on their kids. The service homes in on location data from a child’s phone and sends a digital message whenever the kid arrives at home or at school—and whenever he leaves. Stroll off campus at ten in the morning, and the parents instantly know. As of late 2012, Life360 had signed up about 25 million users.
It’s long been known that blind people are able to compensate for their loss of sight by using other senses, relying on sound and touch to help them “see” the world. Neuroimaging studies have backed this up, showing that in blind people brain regions devoted to sight become rewired to process touch and sound as visual information.
Now, in the age of Google Glass, smartphones and self-driving cars, new technology offers ever more advanced ways of substituting one sensory experience for another. These exciting new devices can restore sight to the blind in ways never before thought possible.
One approach is to use sound as a stand-in for vision. In a study published in Current Biology, neuroscientists at the Hebrew University of Jerusalem used a “sensory substitution device” dubbed “the vOICe” (Oh, I See!) to enable congenitally blind patients to see using sound. The device translates visual images into brief bursts of music, which the participants then learn to decode.
Over a series of training sessions they learn, for example, that a short, loud synthesizer sound signifies a vertical line, while a longer burst equates to a horizontal one. Ascending and descending tones reflect the corresponding directions, and pitch and volume relay details about elevation and brightness. Layering these sound qualities and playing several in sequence (each burst lasts about one second) thus gradually builds an image as simple as a basic shape or as complex as a landscape.
The concept has tried and true analogs in the animal world, says Dr. Amir Amedi, the lead researcher on the study. “The idea is to replace information from a missing sense by using input from a different sense. It’s just like bats and dolphins use sounds and echolocation to ‘see’ using their ears.”
The Sochi Olympics are churning out dramatic victories – but athletes aren’t the only ones who fine-tuned their craft to get here. As U.S. bobsledders, skaters and lugers compete during these Games, they’re doing so with cutting-edge technology that’s gone through an equally exhaustive testing process.
These technological upgrades, which look to bolster their respective sports with faster times and improved features, will help athletes stand their best chance yet at scoring the gold this year. Here we take a look at three notable improvements.
With speed skating, the difference between scoring a gold medal and walking home empty-handed is determined by a fraction of a second. To help put U.S. Olympic speed skaters on the winning side of that difference, sporting goods manufacturer
Under Armour and defense contractor Lockheed Martin created the Mach 39 speed skating suit to shave off those precious nanoseconds.
Whereas most suits try to be as slick and aerodynamic as possible, Under Armour went the opposite direction by installing “flow-molding” on the backside of the Mach 39 suits. These strategically placed dimples work like the bumps on a golf ball, cutting back drag that accumulates behind high-velocity objects. “We’re trying to disrupt that air flow before it bulks up behind a skater,” Chief of Innovation Kevin Haley said.
Along with reduced air drag, the suits also cut down on friction generated between the athlete’s thighs as they cross over one another for tight track turns. Dubbed “Armour Glide,” these textiles are strategically located on the athlete’s inner thighs, where t
he most friction—and energy waste—occurs. With the textiles, athletes see a 65% drop in the coefficient of friction between the legs, letting them redirect their strength onto the ice and “put more power into the skates,” Haley said.
By Darren Ansell, University of Central Lancashire
This article was originally published at The Conversation, an online publication covering the latest research.
Apparently keen to inject a bit of fun into its image after a damaging few weeks of press coverage, online retail giant Amazon has announced that it is experimenting with the use of drones to deliver its products.
According to chief executive Jeff Bezos, a squadron of unmanned “octocopters” could be deployed in the next five years to deliver packages of up to 5 pounds (2.3kg) to customers just 30 minutes after they place an order.
The idea of using small unmanned aerial vehicles for delivering consumer goods has been around for a few years and Amazon is unlikely to be the only company looking to the skies to expand its customer base. One company in Australia is planning to start delivering textbooks in this way as early as March. The devices have also been trialed for use in all kinds of civic projects, such as to deliver medicine, help conservation projects or spot missing people in search and rescue operations.
It is even possible to train to become a small commercial UAV pilot in just one week—so in many ways, the path towards having all your purchases dropped from the heavens into your lap appears clear.
Most of what I know isn’t in my head. It’s out there in my books. I know how to do a lot of integrals in calculus, for example. But, really, what I mean by that is that I know where my book of integrals is, and I know where in the book any particular method is. I know all that stuff in all those books in my house because I can find my way there.
Books in a bookshelf possess lots of visual cues, so I can quickly find my way to the right book — “Oh, it’s on the bottom left of the shelf by the window in the living room, just below that big blue art book.”
And once I find the book, when I open it up I can use visual cues within it to find my way to the right page. After all, it’s not as if I remember the page number. No, I remember roughly where it is in the book, roughly what the page looks like, and roughly what the surrounding pages might look like. Pages in a book might not initially seem to have a look, but they very often do. There are often figures, or tables, or unique and recognizable features to the way the paragraphs are aligned. These visuo-spatial cues guide me further and further along to the goal, the piece of my knowledge out there in my library.
Mess with my library and books, and you mess with my brain.
In a previous post I described mathematicians’ ongoing search for key properties of prime numbers. That effort may seem to belong entirely within the realm of pure mathematics; but surprisingly, the importance of primes goes far beyond the abstruse obsessions of ivory-tower mathematicians. In fact, the use of prime numbers underlies some of the most dramatic events in the news these past weeks: the story behind Edward Snowden’s revelations that the National Security Agency (NSA) is snooping on the communications of both American citizens and European diplomats.
While the Europeans have protested about their internal communications being intercepted by the NSA—ironically—the tools that one can use for protection from spying by anyone are readily accessible online, in the professional literature, and in publicly-available manuals and textbooks. These methods all rely on clever uses of prime numbers.
The essentials of these techniques are far from new. The foundations of a program to create codes so powerful that they could not be broken even if an eavesdropper were to use the entire available worldwide computing power were laid more than 35 years ago. The year 1976 saw the development of the Diffie-Hellman key exchange method (named after Whitfield Diffie and Martin Hellman; the names Ralph Merkle, James Ellis, Clifford Cocks, and Malcolm Williamson are often also associated with it); and the following, 1977, witnessed the appearance of the RSA algorithm. Both methods have advanced over the past three and a half decades, but information about their extensions is also readily available to anyone.
How do these techniques work? I will explain both methods here—necessarily in a simplified way. (Those interested in learning more can read some of the articles in the links that appear throughout this post.)