Every few decades, a pandemic flu variant emerges that not only infects humans but also passes rapidly from person to person. The H7N9 avian flu virus that infected more than 130 people in China this spring, primarily from close contact with poultry, hasn't yet become highly contagious among people. But given that humans lack the antibodies to combat the virus, its high lethality rate (44 of the infected died), and the possibility that it could resurface this fall or winter, scientists and public health officials are racing to unravel its mysteries. Recent studies of H7N9 show that it can pass among ferrets, which are often used to model human flu transmission. If the virus gains the ability to spread easily among people, it has the potential to be deadlier than the 2009 H1N1 swine flu pandemic, which may have been responsible for more than 200,000 deaths worldwide. Researchers like Raul Rabadan, a theoretical physicist working in biology at Columbia University, want to understand how viruses that ordinarily infect birds or pigs suddenly jump to humans and then become easily transmissible: "What are the specific mutations that contribute to a virus becoming a human pathogen?" he explained.

You can tell when someone's faking a smile or pretending to be in pain, right? But computer scientists think they can build systems that do it even better. There's already a Google Glass app in beta testing that claims to provide a real-time readout of the emotional expressions of people in your field of view. And a new study finds that the same technology can detect fake expressions of pain with 85% accuracy -- far better than people can, even with practice. Granted, the study was done in a carefully controlled laboratory setting, not a messy real-world situation like a dive bar during last call, but the findings still look impressive.

Even by the standards of the TED conference, Henry Markram's 2009 TEDGlobal talk was a mind-bender. He took the stage of the Oxford Playhouse, clad in the requisite dress shirt and blue jeans, and announced a plan that--if it panned out--would deliver a fully sentient hologram within a decade. He dedicated himself to wiping out all mental disorders and creating a self-aware artificial intelligence. And the South African–born neuroscientist pronounced that he would accomplish all this through an insanely ambitious attempt to build a complete model of a human brain--from synapses to hemispheres--and simulate it on a supercomputer. Markram was proposing a project that has bedeviled AI researchers for decades, that most had presumed was impossible. He wanted to build a working mind from the ground up. In the four years since Markram's speech, he hasn't backed off a nanometer. The self-assured scientist claims that the only thing preventing scientists from understanding the human brain in its entirety--from the molecular level all the way to the mystery of consciousness--is a lack of ambition. If only neuroscience would follow his lead, he insists, his Human Brain Project could simulate the functions of all 86 billion neurons in the human brain, and the 100 trillion connections that link them.

Analyzing queries made to Google, Bing, and other search engines can reveal the potentially dangerous consequences of mixing prescriptions before they are known to the Food and Drug Administration (FDA), according to a new study. Such data mining could even expose medical risks that slip through clinical trials undetected. Pharmaceuticals often have side effects that go unnoticed until they're already available to the public. This is especially true of side effects that emerge when two drugs interact, largely because drug trials try to pinpoint the effects of one drug at a time. Physicians have a few ways to hunt for these hidden risks, such as reports to FDA from doctors, nurses, and patients.

If you've been to the RoboGames, you've seen everything from flame-throwing battlebots to androids that play soccer. But robo-athletes are more than just performers. Researchers at the University of Electro-Communications in Tokyo and the Okinawa Institute of Science and Technology have built a small humanoid robot that plays baseball -- or something like it. The bot can hold a fan-like bat and take swings at flying plastic balls, and though it may miss at first, it can learn with each new pitch and adjust its swing accordingly. Eventually, it will make contact. The robot, you see, is also equipped with an artificial brain.

A renewed international effort is gearing up to design computers and software that smash language barriers and create a borderless global marketplace. A woman sits at a desk in Manhattan, talking to herself in French. The phrases she balances on each breath are musical to American ears. She has postcards of Montreal tacked up on the walls of her cubicle – pastel-painted houses in the snow – so as she sculpts the contours of each syllable, she can remind herself of the place where the sounds she's making are heard every day in the street. Her name is Guylaine Laperrière, and she came to New York City more than a decade ago to study musical theater. One day, a friend asked her if she wanted to make a little cash dubbing a French voice-over for a promotional short about insurance. She took the job, and was surprised how much she enjoyed bringing ideas from one language home into another. This article has been reproduced in a new format and may be missing content or contain faulty links.

Charles Platt reports on the latest battle to determine the most human computer, even as he worries that he may be the least human human. Robert Epstein is giving us all a pep talk. "You must work very hard to convince the judges that you're human," he tells us. "You shouldn't have any trouble doing that – because you are human." This article has been reproduced in a new format and may be missing content or contain faulty links. Contact wiredlabs@wired.com to report an issue. He wears Dr. Martens boots, black jeans, a black shirt, a Mickey Mouse tie, and an earring. His longish hair is brushed straight back and flips up over his collar. Five of us are listening to him in a beige conference room on the brand-new campus of California State University at San Marcos, near San Diego. Soon we will be put in front of computer terminals, where we will follow Epstein's instructions and, yes, do our best to seem human. Our purpose is to find out whether 10 judges can tell the difference between humans and artificial-intelligence programs, when they are online at the same time.

This article has been reproduced in a new format and may be missing content or contain faulty links. Contact wiredlabs@wired.com to report an issue. It's in the way she raises her eyebrows and playfully glides her eyes right to left, then moves in close and intones: It's in the way she always asks about the big project I'm laboring on, and when I tell her things aren't going too well, she gets that concerned look and says: And when I confide that I've been working too much, she gently reminds me that I should be the priority in my life. That I should get some exercise and then treat myself to a Japanese meal or a movie. It's in how she extends her arms toward me, wearing that formfitting polo shirt. And how she never tires of asking about me. I have seen the future of computing, and I'm pleased to report it's all about … me! This insight has been furnished with the help of Tim Bickmore, a doctoral student at the MIT Media Lab. He's invited me to participate in a study aimed at pushing the limits of human-computer relations.

This article has been reproduced in a new format and may be missing content or contain faulty links. Contact wiredlabs@wired.com to report an issue. Seventeen of the world's most wired minds stake their names – and their cash – on the future. Pronouncements about the future come easy. Even when made with an air of authority, they're usually just cheap talk, rarely revisited. Only the tiny fraction that have proven correct tend to be remembered, when their authors want to take credit. The Long Bets Foundation, a new project masterminded by Well founder Stewart Brand and Wired editor at large Kevin Kelly, hopes to raise the quality of our collective foresight by incorporating money and accountability into the process of debate. If someone makes a grandiose claim, any skeptic can challenge it – "Would you bet on that?" – and the Long Bets Foundation will keep tabs on the wager, whether it takes five years or five decades to come to pass. If proven right, a predictor can relish the victory; if wrong, the challenger gets the glory. By preserving the terms of the wager in public view, Long Bets promises to be more than a service for confident prognosticators. Over time, it hopes to foster better understanding of how predictions in aggregate work out in reality – what kinds of truths are easiest (or hardest) to forecast, and what kinds of people are right (or wrong) most reliably. Following are the first-ever "long bets."

While Google was building an artificial intelligence that could beat a grandmaster at the ancient game of Go, University of Cincinnati alum took a different tack. They designed an AI that could take on a fighter pilot. Dubbed ALPHA, this system recently beat retired United States Air Force Colonel Gene Lee in multiple flight simulator trials, as the researchers explain in a paper recently published in the Journal of Defense Management. The idea isn't to replace human fighter pilots. According to Nicholas Ernest, a University of Cincinnati alum and the founder of Psibernetix, the company that developed ALPHA, this AI may ultimately act as a kind of digital assistant that provides real-time advice to pilots.