Scientists are making remarkable progress at using brain implants to restore the freedom of movement that spinal cord injuries take away.
The French neuroscientist was watching a macaque monkey as it hunched aggressively at one end of a treadmill. His team had used a blade to slice halfway through the animal’s spinal cord, paralyzing its right leg. Now Courtine wanted to prove he could get the monkey walking again. To do it, he and colleagues had installed a recording device beneath its skull, touching its motor cortex, and sutured a pad of flexible electrodes around the animal’s spinal cord, below the injury. A wireless connection joined the two electronic devices.
The result: a system that read the monkey’s intention to move and then transmitted it immediately in the form of bursts of electrical stimulation to its spine. Soon enough, the monkey’s right leg began to move. Extend and flex. Extend and flex. It hobbled forward. “The monkey was thinking, and then boom, it was walking,” recalls an exultant Courtine, a professor with Switzerland’s École Polytechnique Fédérale de Lausanne
Tractor-trailers without a human at the wheel will soon barrel onto highways near you. What will this mean for the nation’s 1.7 million truck drivers?
At first glance, the opportunities and challenges posed by self-driving trucks might seem to merely echo those associated with self-driving cars. But trucks aren’t just long cars. For one thing, the economic rationale for self-driving trucks might be even stronger than the one for driverless cars. Autonomous trucks can coördinate their movements to platoon closely together over long stretches of highway, cutting down on wind drag and saving on fuel. And letting the truck drive itself part of the time figures to help truckers complete their routes sooner.
But the technological obstacles facing autonomous trucks are higher than the ones for self-driving cars. Otto and other companies will need to demonstrate that sensors and code can match the situational awareness of a professional trucker—skills honed by years of experience and training in piloting an easily destabilized juggernaut, with the momentum of 25 Honda Accords, in the face of confusing road hazards, poor surface conditions, and unpredictable car drivers.
Inside the cab is a custom-built, liquid-cooled, breadbox-size micro-supercomputer that, Berdinis claims, provides the most computing muscle ever crammed into so small a package. It is needed to crunch the vast stream of sensor data and shepherd it through the guidance algorithms that adjust braking and steering commands to compensate for the truck’s load weight. Rounding out the hardware lineup is a drive-by-wire box to turn the computer’s output into physical truck-control signals. It does this through electromechanical actuators mounted to the truck’s mechanical steering, throttling, and braking systems. Two big red buttons in the cab—Otto calls them the Big Red Buttons—can cut off all self-driving activity. But even without them, the system is designed to yield to any urgent tugs on the steering wheel or heavy pumps of the pedals from anyone in the driver’s seat.
Paying with Your Face
Face-detecting systems in China now authorize payments, provide access to facilities, and track down criminals. Will other countries follow?
Facial recognition has existed for decades, but only now is it accurate enough to be used in secure financial transactions. The new versions use deep learning, an artificial-intelligence technique that is especially effective for image recognition because it makes a computer zero in on the facial features that will most reliably identify a person. “The face recognition market is huge,” says Shiliang Zhang, an assistant professor at Peking University who specializes in machine learning and image processing.
One such company is Baidu, which operates China’s most popular search engine, along with other services. Baidu researchers have published papers showing that their software rivals most humans in its ability to recognize a face. In January, the company proved this by taking part in a TV show featuring people who are remarkably good at identifying adults from their baby photos. Baidu’s system outshined them.
Face++ pinpoints 83 points on a face. The distance between them provides a means of identification.
Now Baidu is developing a system that lets people pick up rail tickets by showing their face. The company is already working with the government of Wuzhen, a historic tourist destination, to provide access to many of its attractions without a ticket. This involves scanning tens of thousands of faces in a database to find a match, which Baidu says it can do with 99 percent accuracy.
Practical Quantum Computers
Advances at Google, Intel, and several research groups indicate that computers with previously unimaginable power are finally within reach.
At the heart of quantum computing is the quantum bit, or qubit, a basic unit of information analogous to the 0s and 1s represented by transistors in your computer. Qubits have much more power than classical bits because of two unique properties: they can represent both 1 and 0 at the same time, and they can affect other qubits via a phenomenon known as quantum entanglement. That lets quantum computers take shortcuts to the right answers in certain types of calculations.
Quantum computers will be particularly suited to factoring large numbers (making it easy to crack many of today’s encryption techniques and probably providing uncrackable replacements), solving complex optimization problems, and executing machine-learning algorithms. And there will be applications nobody has yet envisioned.
Soon, however, we might have a better idea of what they can do. Until now, researchers have built fully programmable five-qubit computers and more fragile 10- to 20-qubit test systems. Neither kind of machine is capable of much. But the head of Google’s quantum computing effort, Harmut Neven, says his team is on target to build a 49-qubit system by as soon as a year from now. The target of around 50 qubits isn’t an arbitrary one. It’s a threshold, known as quantum supremacy, beyond which no classical supercomputer would be capable of handling the exponential growth in memory and communications bandwidth needed to simulate its quantum counterpart. In other words, the top supercomputer systems can currently do all the same things that five- to 20-qubit quantum computers can, but at around 50 qubits this becomes physically impossible
The 360-Degree Selfie
Inexpensive cameras that make spherical images are opening a new era in photography and changing the way people share stories.
We experience the world in 360 degrees, surrounded by sights and sounds. Until recently, there were two main options for shooting photos and video that captured that context: use a rig to position multiple cameras at different angles with overlapping fields of view or pay at least $10,000 for a special camera. The production process was just as cumbersome and generally took multiple days to complete. Once you shot your footage, you had to transfer the images to a computer; wrestle with complex, pricey software to fuse them into a seamless picture; and then convert the file into a format that other people could view easily.
Today, anyone can buy a decent 360° camera for less than $500, record a video within minutes, and upload it to Facebook or YouTube. Much of this amateur 360° content is blurry; some of it captures 360 degrees horizontally but not vertically; and most of it is mundane. Watching footage of a stranger’s vacation is almost as boring in spherical view as it is in regular mode. But the best user-generated 360° photos and videos—such as the Virtual Forest—deepen the viewer’s appreciation of a place or an event.
Hot Solar Cells
By converting heat to focused beams of light, a new solar device could create cheap and continuous power.
scientists has built a different sort of solar energy device that uses inventive engineering and advances in materials science to capture far more of the sun’s energy. The trick is to first turn sunlight into heat and then convert it back into light, but now focused within the spectrum that solar cells can use. While various researchers have been working for years on so-called solar thermophotovoltaics, the MIT device is the first one to absorb more energy than its photovoltaic cell alone, demonstrating that the approach could dramatically increase efficiency.
Gene Therapy 2.0
Scientists have solved fundamental problems that were holding back cures for rare hereditary disorders. Next we’ll see if the same approach can take on cancer, heart disease, and other common illnesses.
crucial puzzles have been solved and gene therapies are on the verge of curing devastating genetic disorders. Two gene therapies for inherited diseases—Strimvelis for a form of SCID and Glybera for a disorder that makes fat build up in the bloodstream—have won regulatory approval in Europe. In the United States, Spark Therapeutics could be the first to market; it has a treatment for a progressive form of blindness. Other gene therapies in development point to a cure for hemophilia and relief from an incapacitating skin disorder called epidermolysis bullosa.
Fixing rare diseases, impressive in its own right, could be just the start. Researchers are studying gene therapy in clinical trials for about 40 to 50 different diseases, says Maria-Grazia Roncarolo, a pediatrician and scientist at Stanford University who led early gene-therapy experiments in Italy that laid the foundation for Strimvelis. That’s up from just a few conditions 10 years ago. And in addition to treating disorders caused by malfunctions in single genes, researchers are looking to engineer these therapies for more common diseases, like Alzheimer’s, diabetes, heart failure, and cancer. Harvard geneticist George Church has said that someday, everyone may be able to take gene therapy to combat the effects of aging.
The Cell Atlas
Biology’s next mega-project will find out what we’re really made of.
Three technologies are coming together to make this new type of mapping possible. The first is known as “cellular microfluidics.” Individual cells are separated, tagged with tiny beads, and manipulated in droplets of oil that are shunted like cars down the narrow, one-way streets of artificial capillaries etched into a tiny chip, so they can be corralled, cracked open, and studied one by one.
The second is the ability to identify the genes active in single cells by decoding them in superfast and efficient sequencing machines at a cost of just a few cents per cell. One scientist can now process 10,000 cells in a single day.
The third technology uses novel labeling and staining techniques that can locate each type of cell—on the basis of its gene activity—at a specific zip code in a human organ or tissue.
Botnets of Things
The relentless push to add connectivity to home gadgets is creating dangerous side effects that figure to get even worse.
Botnets are used to commit click fraud. Click fraud is a scheme to fool advertisers into thinking that people are clicking on, or viewing, their ads. There are lots of ways to commit click fraud, but the easiest is probably for the attacker to embed a Google ad in a Web page he owns. Google ads pay a site owner according to the number of people who click on them. The attacker instructs all the computers on his botnet to repeatedly visit the Web page and click on the ad. Dot, dot, dot, PROFIT! If the botnet makers figure out more effective ways to siphon revenue from big companies online, we could see the whole advertising model of the Internet crumble.
Similarly, botnets can be used to evade spam filters, which work partly by knowing which computers are sending millions of e-mails. They can speed up password guessing to break into online accounts, mine bitcoins, and do anything else that requires a large network of computers. This is why botnets are big businesses. Criminal organizations rent time on them.
But the botnet activities that most often make headlines are denial-of-service attacks. Dyn seems to have been the victim of some angry hackers, but more financially motivated groups use these attacks as a form of extortion. Political groups use them to silence websites they don’t like. Such attacks will certainly be a tactic in any future cyberwar.
By experimenting, computers are figuring out how to do things that no programmer could teach them.
Reinforcement learning copies a very simple principle from nature. The psychologist Edward Thorndike documented it more than 100 years ago. Thorndike placed cats inside boxes from which they could escape only by pressing a lever. After a considerable amount of pacing around and meowing, the animals would eventually step on the lever by chance. After they learned to associate this behavior with the desired outcome, they eventually escaped with increasing speed.
What’s most amazing is that the software governing the cars’ behavior wasn’t programmed in the conventional sense at all. It learned how to merge, slickly and safely, simply by practicing. During training, the control software performed the maneuver over and over, altering its instructions a little with each attempt. Most of the time the merging happened way too slowly and cars interfered with each other. But whenever the merge went smoothly, the system would learn to favor the behavior that led up to it. This approach, known as reinforcement learning, is largely how AlphaGo, a computer developed by a subsidiary of Alphabet called DeepMind, mastered the impossibly complex board game Go and beat one of the best human players in the world in a high-profile match last year. Now reinforcement learning may soon inject greater intelligence into much more than games. In addition to improving self-driving cars, the technology can get a robot to grasp objects it has never seen before, and it can figure out the optimal configuration for the equipment in a data center.