In the military world, fighter pilots have long been described as the best of the best. As Tom Wolfe famously wrote, only those with the "right stuff" can handle the job. Now, it seems, the right stuff may no longer be the sole purview of human pilots.
A pilot A.I. developed by a doctoral graduate from the University of Cincinnati has shown that it can not only beat other A.I.s, but also a professional fighter pilot with decades of experience. In a series of flight combat simulations, the A.I. successfully evaded retired U.S. Air Force Colonel Gene "Geno" Lee, and shot him down every time. Lee called it "the most aggressive, responsive, dynamic and credible A.I. I've seen to date."
And "Geno" is no slouch. He's a former Air Force Battle Manager and adversary tactics instructor. He's controlled or flown in thousands of air-to-air intercepts as mission commander or pilot. In short, the guy knows what he's doing. Plus he's been fighting A.I. opponents in flight simulators for decades. But he says this one is different. "I was surprised at how aware and reactive it was. It seemed to be aware of my intentions and reacting instantly to my changes in flight and my missile deployment. It knew how to defeat the shot I was taking. It moved instantly between defensive and offensive actions as needed."
The A.I., dubbed ALPHA, was developed by Psibernetix, a company founded by University of Cincinnati doctoral graduate Nick Ernest, in collaboration with the Air Force Research Laboratory. According to the developers, ALPHA was specifically designed for research purposes in simulated air-combat missions.
The secret to ALPHA's superhuman flying skills is a decision-making system called a genetic fuzzy tree, a subtype of fuzzy logic algorithms. The system approaches complex problems much like a human would, says Ernest, breaking the larger task into smaller subtasks, which include high-level tactics, firing, evasion, and defensiveness. By considering only the most relevant variables, it can make complex decisions with extreme speed. As a result, the A.I. can calculate the best maneuvers in a complex, dynamic environment, over 250 times faster than its human opponent can blink.
After hour-long combat missions against ALPHA, Lee says, "I go home feeling washed out. I'm tired, drained and mentally exhausted. AI has superhuman reflexes and there is no way to win. This may be artificial intelligence, but it represents a real challenge."
The results of the dogfight simulations are published in the Journal of Defense Management.
One day in the future, we’ll look back in wonder at how our physical objects used to be singular, disconnected pieces of matter.
We’ll be in awe of the fact that a car used to be just a piece of metal full of gears and belts that we would drive from one place to another, that a refrigerator was a box that kept our food cold — and a phone was a piece of plastic we used to communicate to one other person at a time.
That’s because the future we’re rapidly moving towards is one where physical items become intelligent and interconnected — and as a fascinating result, their functionality changes.
There is probably no better example of this trend than the cell phone. The mobile phone used to be just that — a mobile phone. Now it’s your flashlight, your bank, your TV, and your funny, yet kind of dumb personal assistant. The cell phone — or really, more accurately, the hand-held computer — has become mostly a gateway to all the mobile services we use on it.
And those services are constantly morphing and improving, changing what our smartphones can do without requiring the physical phone itself to change all that much at all.
A team of researchers from Google, the University of the Basque Country, the University of California and IKERBASQUE, Basque Foundation for Science has devised a means for combining the two leading ideas for creating a quantum computer in one machine, offering a possible means for learning more about how to create a true quantum computer sometime in the future. They have published the details in the journal Nature.
Computer scientists would really like to figure out how to build a true quantum computer—doing so would allow for solving problems that are simply unsolvable on conventional machines. But, unfortunately, the idea behind such a computer is still mostly theoretical. To move some of the ideas from theory to reality, the researchers with this new effort have built an actual machine that is based on two of the strongest approaches to building a quantum computer.
The first approach is based on the gate model, where qubits are linked together to form primitive circuits that together form quantum logic gates. In such an arrangement, each logic gate is capable of performing one specific type of operation. Thus, to make use of such a computer, each of the logic gates must be programmed ahead of time to carry out certain tasks.
With the second approach the qubits do not interact, instead they are kept at a ground state where they are then caused to evolve into a system capable of solving a particular problem. The result is known as an adiabatic machine—some have actually been built because they are more versatile than the gate model computers. Unfortunately, they are also not expected to be able to ever fully make use of the full power of quantum computing.
In this new effort, the researchers have attempted to gain the positive attributes of both approaches by creating a machine where they started with a standard quantum computer and then used it to simulate an adiabatic machine. It uses 9 qubits and has over 1,000 logic gates and allows for communication between qubits to be turned on and off at will. The end result, the team reports, is one that unlike an adiabatic machine, is able to tackle traditionally difficult computing problems. They expect it to be useful as a research tool, helping lead the way to the development of a truly quantum computer.
(Phys.org)—Light behaves both as a particle and as a wave. Since the days of Einstein, scientists have been trying to directly observe both of these aspects of light at the same time.
Quantum mechanics tells us that light can behave simultaneously as a particle or a wave. However, there has never been an experiment able to capture both natures of light at the same time; the closest we have come is seeing either wave or particle, but always at different times. Taking a radically different experimental approach, EPFL scientists have now been able to take the first ever snapshot of light behaving both as a wave and as a particle. The breakthrough work is published in Nature Communications.
When UV light hits a metal surface, it causes an emission of electrons. Albert Einstein explained this "photoelectric" effect by proposing that light – thought to only be a wave – is also a stream of particles. Even though a variety of experiments have successfully observed both the particle- and wave-like behaviors of light, they have never been able to observe both at the same time.
A research team led by Fabrizio Carbone at EPFL has now carried out an experiment with a clever twist: using electrons to image light. The researchers have captured, for the first time ever, a single snapshot of light behaving simultaneously as both a wave and a stream of particles.
The experiment is set up like this: A pulse of laser light is fired at a tiny metallic nanowire. The laser adds energy to the charged particles in the nanowire, causing them to vibrate. Light travels along this tiny wire in two possible directions, like cars on a highway. When waves traveling in opposite directions meet each other they form a new wave that looks like it is standing in place. Here, this standing wave becomes the source of light for the experiment, radiating around the nanowire.
Despite the fact that Einstein's unifying theory has never been supported by observations, let alone definitive mathematical proof, Einstein's work did ultimately lead many scientists to re-examine the universe in relation to a holistic theory of everything, including an amalgam of his gravitational theories and quantum gravity hypotheses. Much work leading on from his theories provided tantalizing glimpses at possible gravitational interactions, including the behavior of the smallest of all fermions yet discovered – leptons and quarks.
This research led directly to the discovery of a gauge-invariant quantum field theory of the weak force, which included an electromagnetic interaction (and produced the "electroweak" concept that now shows correlation between electromagnetic and weak nuclear fields), which was, in itself, a great breakthrough in particle physics research. Unfortunately, however, it did not progress to include an observable gravitational component.
Nevertheless, buoyed by such revelations, theoretical physicists sought out a similar quantum field theory for the strong nuclear force, and eventually found one, dubbing it quantum chromodynamics. In this case, quarks are shown to interact through the exchange of gluons. This research has led to further postulations that the electroweak and strong nuclear forces could be united in a grand unified theory, which would then incorporate three of the four known forces in the universe. Again, however, an inclusion of the influence of gravity failed to be reconciled.
So despite the successful conflation of the fields discussed above, physicists have been unable to formulate a complete particle-driven unified field theory for gravity since it seems to lack a force-carrier particle of its own.
There is, however, one contender: A contentious theoretical particle known as a "graviton". The graviton moniker was apparently coined by the Russian physicists Dmitrii Blokhintsev and F. M. Gal'perin sometime in the mid 1930s (interestingly, around the time of the Einstein-Bohr stoush), in relation to the notion that if Einstein's predicted gravity waves existed, then they must also possess a quanta of energy, as does electromagnetic energy. That is, the electromagnetic and strong and weak nuclear forces all act through a "force carrier", which is exchanged between the interacting particles. These exchange carriers are also known as field particles, or gauge bosons.
The graviton, if it exists, doesn't seem to act like any of the other particles in the Standard Model, as it does not exhibit these force carrier behaviors. Put simply, unlike the other forces, gravity can not be absorbed, transformed, or shielded against, and it only attracts and never repels. In effect, this theoretical particle appears to possess no discernible way to interact with any other particle. This fact by itself would prohibit its inclusion in the Standard Model, partly because no instrument of sufficient size or efficiency could possibly be built to detect the supposedly tiny energies associated with it, but mostly because the entire concept runs into enormous theoretical difficulties at energies close to the Planck scale, which are the smallest sizes and energies able to be probed with particle accelerators.
Despite this, quantum gravity and other yet-to-be-proven quantum mechanical models such as string theory are often associated with gravitons, both of which rely on its existence. And though much hope is pinned on one of these theories eventually providing a unified description of gravity and particle physics, quantum gravity may prove the best contender. This is because string theory alone is not a physical descriptor of reality, but instead a self-contained mathematical model that describes all of the fundamental forces and the various forms of matter as models, not observed phenomena.
Ahead of today's historic "in/out" vote for Britain, it has emerged the EU wants to introduce laws specific to robots that could give them civil rights regulations of they own, and see limits on how many jobs they could replace from humans.
In scenes that could have come from the sic-fi novels of Isaac Asimov nearly 70 years ago, a recommendation of the European Parliament to the EU Commission has suggested in the future sentient AI robots could need their own rights and responsibilities, and strict laws banning them from taking over too many jobs across the Continent may become necessary.
In the 1950s Asimov predicted robots would eventually have to adhere to laws, because the potential of what could develop from a combination of sophisticated mechanism, androids with human features, and artificial intelligence (AI) was too dangerous.
But, it appears Brussels bureaucrats fear this fiction will become a reality and the report has even considered including a "new robot category next to natural and lawful people: the electronic person".
The best minds in the business—Yann LeCun of Facebook, Luke Nosek of the Founders Fund, Nick Bostrom of Oxford University and Andrew Ng of Baidu—on what life will look like in the age of the machines
Via Jean-Philippe BOCQUENET
Sentient machines are a greater threat to humanity than climate change, according to Oxford philosopher Nick Bostrom You’ll find the Future of Humanity Institute down a medieval backstreet in the centre of Oxford.
An artificial nervous system could help robots avoid damaging interactions.
One of the most useful things about robots is that they don’t feel pain. Because of this, we have no problem putting them to work in dangerous environments or having them perform tasks that range between slightly unpleasant and definitely fatal to a human. And yet, a pair of German researchers believes that, in some cases, feeling and reacting to pain might be a good capability for robots to have.
The researchers, from Leibniz University of Hannover, are developing an “artificial robot nervous system to teach robots how to feel pain” and quickly respond in order to avoid potential damage to their motors, gears, and electronics. They described the project last week at the IEEE International Conference on Robotics and Automation (ICRA) in Stockholm, Sweden, and we were there to ask them what in the name of Asimov they were thinking when they came up with this concept.
Why is it a good idea for robots to feel pain? The same reason why it’s a good idea for humans to feel pain, said Johannes Kuehn, one of the researchers. “Pain is a system that protects us,” he told us. “When we evade from the source of pain, it helps us not get hurt.” Humans that don’t have the ability to feel pain get injured far more often, because their bodies don’t instinctively react to things that hurt them.
Kuehn, who worked on the project with Professor Sami Haddadin, one of the world’s foremost experts in physical human-robot interaction and safety, argues that by protecting robots from damage, their system will be protecting humans as well. That’s because a growing number of robots will be operating in close proximity to human workers, and undetected damages in robotic equipment can lead to accidents. Kuehn and Haddadin reasoned that, if our biological mechanisms to sense and respond to pain are so effective, why not devise a bio-inspired robot controller that mimics those mechanisms? Such a controller would reflexively react to protect the robot from potentially damaging interactions.
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