Smart wind and solar power agricultural DRONES.

Introduction

Technology news is full of incremental developments, but few of them are true milestones. Here we’re citing 10 that are. These advances from the past year all solve thorny problems or create powerful new ways of using technology. They are breakthroughs that will matter for years to come

Agricultural Drones

Ultra private Smartphones

Brain Mapping

Neuromorphic Chips

Genome Editing

Microscale 3-D Printing

Mobile Collaboration

Oculus Rift

Agile Robots

Smart Wind and Solar Power

Archive of Past Lists

Agricultural Drones

Relatively cheap drones with advanced sensors and imaging capabilities are giving farmers new ways to increase yields and reduce crop damage.

Ryan Kunde is a winemaker whose family’s picture-perfect vineyard nestles in the Sonoma Valley north of San Francisco. But Kunde is not your average farmer. He’s also a drone operator—and he’s not alone. He’s part of the vanguard of farmers who are using what was once military aviation technology to grow better grapes using pictures from the air, part of a broader trend of using sensors and robotics to bring big data to precision agriculture.

Top: A drone from PrecisionHawk is equipped with multiple sensors to image fields.

Bottom: This image depicts vegetation in near-infrared light to show chlorophyll levels.

What “drones” means to Kunde and the growing number of farmers like him is simply a low-cost aerial camera platform: either miniature fixed-wing airplanes or, more commonly, quadcopters and other multibladed small helicopters. These aircraft are equipped with an autopilot using GPS and a standard point-and-shoot camera controlled by the autopilot; software on the ground can stitch aerial shots into a high-resolution mosaic map. Whereas a traditional radio-controlled aircraft needs to be flown by a pilot on the ground, in Kund's drone the autopilot (made by my company, 3D Robotics) does all the flying, from auto takeoff to landing. Its software plans the flight path, aiming for maximum coverage of the vineyards, and controls the camera to optimize the images for later analysis.

This low-altitude view (from a few meters above the plants to around 120 meters, which is the regulatory ceiling in the United States for unmanned aircraft operating without special clearance from the Federal Aviation Administration) gives a perspective that farmers have rarely had before. Compared with satellite imagery, it’s much cheaper and offers higher resolution. Because it’s taken under the clouds, it’s unobstructed and available anytime. It’s also much cheaper than crop imaging with a manned aircraft, which can run $1,000 an hour. Farmers can buy the drones outright for less than $1,000 each.

The advent of drones this small, cheap, and easy to use is due largely to remarkable advances in technology: tiny MEMS sensors (accelerometers, gyros, magnetometers, and often pressure sensors), small GPS modules, incredibly powerful processors, and a range of digital radios. All those components are now getting better and cheaper at an unprecedented rate, thanks to their use in smartphones and the extraordinary economies of scale of that industry. At the heart of a drone, the autopilot runs specialized software—often open-source programs created by communities such as DIY Drones, which I founded, rather than costly code from the aerospace industry.

Drones can provide farmers with three types of detailed views. First, seeing a crop from the air can reveal patterns that expose everything from irrigation problems to soil variation and even pest and fungal infestations that aren’t apparent at eye level. Second, airborne cameras can take multispectral images, capturing data from the infrared as well as the visual spectrum, which can be combined to create a view of the crop that highlights differences between healthy and distressed plants in a way that can’t be seen with the naked eye. Finally, a drone can survey a crop every week, every day, or even every hour. Combined to create a time-series animation, that imagery can show changes in the crop, revealing trouble spots or opportunities for better crop management.

It’s part of a trend toward increasingly data-driven agriculture. Farms today are bursting with engineering marvels, the result of years of automation and other innovations designed to grow more food with less labor. Tractors autonomously plant seeds within a few centimeters of their target locations, and GPS-guided harvesters reap the crops with equal accuracy. Extensive wireless networks backhaul data on soil hydration and environmental factors to faraway servers for analysis. But what if we could add to these capabilities the ability to more comprehensively assess the water content of soil, become more rigorous in our ability to spot irrigation and pest problems, and get a general sense of the state of the farm, every day or even every hour? The implications cannot be stressed enough. We expect 9.6 billion people to call Earth home by 2050. All of them need to be fed. Farming is an input-output problem. If we can reduce the inputs—water and pesticides—and maintain the same output, we will be overcoming a central challenge.

Agricultural drones are becoming a tool like any other consumer device, and we’re starting to talk about what we can do with them. Ryan Kunde wants to irrigate less, use less pesticide, and ultimately produce better wine. More and better data can reduce water use and lower the chemical load in our environment and our food. Seen this way, what started as a military technology may end up better known as a green-tech tool, and our kids will grow up used to flying robots buzzing over farms like tiny crop dusters.

Ultraprivate Smartphones

New models built with security and privacy in mind reflect the Zeitgeist of the Snowden era.

reakthrough

Mobile phones for the consumer market that transmit minimal personal information.

Why It Matters

Governments and advertisers gather intimate details from cell phones.

Key Players

Blackphone
CryptoPhone
Open Whisper Systems

On January 21 a text message flashed on phones held by the protesters thronging Kiev’s Independence Square. Ukraine’s president, Viktor Yanukovych, was then still clinging to power and brutalizing opponents. The message—from the number 111—read: “Dear subscriber, you are registered as a participant in a mass disturbance.” Widely presumed to have been sent from Yanukovych,s security apparatus to all phones in the protest zone, the message was a stark reminder of how mobile phones can be used for surveillance.

Soon after, a Ukrainian man walked into a nondescript office in National Harbor, Maryland, and sought help from a man named Phil Zimmermann.

Zimmermann is a cryptologist. His company, Silent Circle, encrypts voice calls, text messages, and any file attachments. If you use Silent Circle, your calls to other users are sent through the company’s servers and decrypted on the other phone. The service won’t stop the delivery of ominous messages in range of certain base stations. But it can block eavesdropping and prevent the snooper from knowing the number of the person you are calling or texting. Soon, access codes for Silent Circle were making their way to protest organizers in the heart of Kiev. “Those are the kinds of environments where you need widespread deployment of crypto technology,” Zimmermann says, with evident satisfaction.

In the past year, it’s become clearer that places like Kiev are not the only environments where people might want the privacy Zimmermann can provide. Documents brought to light by former U.S. National Security Agency contractor Edward Snowden suggest that the NSA gathers huge amounts of information from cloud computing platforms and wireless carriers, including the numbers ordinary people called and the times they called them. Not only could the government be watching you: so could websites, advertisers, and even retailers trying to track your movements within stores. Modern smartphones and the apps running on them are engineered to collect and disseminate enormous amounts of user data—such as location, Web browsing histories, search terms, and contact lists.

By summer Zimmermann will be delivering a new way to fight back: a highly secure smartphone, called Black phone. Now being manufactured by a joint venture that includes Silent Circle, it uses Zimmermann,s encryption tools and adds other protections. It runs a special version of the Android operating system—PrivatOS—that blocks many of the ways phones leak data about your activities. While custom security phones have long been in the hands of military and government leaders, this effort may signal a shift toward mass-market phones that are far more private and secure.

Black phone, which sells for $629 with subscriptions to privacy-protecting services, is one of many measures that technologists are taking in response to the Snowden revelations. One such effort involves wider encryption of ordinary Web traffic. Stephen Farrell, a computer scientist at Trinity College Dublin who is leading that project through the Internet Engineering Task Force, says a phone that encrypts communications and seals off data leaks is a crucial part of the strategy. “Personally, I really would like to have a phone with a much more hardened and privacy-friendly configuration,” he says.

Soon after, a Ukrainian man walked into a nondescript office in National Harbor, Maryland, and sought help from a man named Phil Zimmermann.

Crypto Warrior

Growing up in Florida, Phil Zimmermann liked breaking into places and things: his youthful conquests included Disney World and the Miami Seaquarium. He studied computer science at Florida Atlantic University, and he became interested in cryptography in the 1970s, when papers on a technology called public-key cryptography emerged. Traditional crypto required the parties in an encrypted conversation to possess the same unique decoding tool (or “key”). The new approach was fundamentally different: it involved two mathematically linked keys, one private, the other public. Suddenly, applications such as digital signatures became possible. You could use a private key to “sign” a document; later, anyone else could use the public key to verify that you were indeed the author.

Privacy software from Zimmermann is key to Black phone. “Like Steve Jobs said, if you want to do good software you want to build the computer, too,” he says.

Zimmermann,s fascination with this new tool dovetailed with an activist streak. In the 1980s, while laboring as a software engineer by day, he was a peace activist by night, working on the nuclear weapons freeze movement and getting arrested at the Nevada nuclear test site. (He tells of seeing actor Martin Sheen and the celebrity scientist Carl Sagan in jail.) He viewed the Reagan White House as a threat to peace and human rights as it battled socialist movements and governments. He soon started putting his interests together. “I wanted to make crypto software to protect the grassroots community, for the people of El Salvador, for human-rights groups,” he says.

He eventually came up with something new for applications like e-mail. Now known as PGP, for “pretty good privacy,” it built on public-key cryptography with a few new tricks, using speedier algorithms and binding things like usernames and e-mail addresses to public keys. PGP quickly became the most popular way to encrypt e-mail. It also made Zimmermann a combatant in the so-called crypto wars of the 1990s. At the time, the U.S. government was worried about the prospect of strong encryption technologies slipping out of the country and making it harder to snoop on other countries. So after Zimmermann published his code on the Internet in 1991, the Justice Department opened a criminal investigation. It wasn’t dropped until 1996. By then, any fears that foreign governments would use cryptography to hide their activities from the U.S. were overshadowed by the great potential the technology had for American companies in the globalized business environment that emerged after the Cold War. Businesses were opening offices and factories in cheap labor markets, “which tend to be in countries with aggressive wiretapping environments and low on human rights,” Zimmermann says. These businesses were now facing threats once faced only by human-rights and political activists. To better serve that market, Zimmermann began selling cryptography tools through a startup, PGP Inc.

Zimmermann always wanted to take widespread encryption to the next level: secure telephony. Until the past few years, however, voice transmissions did not generally take the digital form required by cryptographic technologies. In the 1990s he’d built a prototype, but it required using modems tethered to PCs. “That product was never going to get any traction,” he says. Today, telephone companies and carriers do encrypt calls—but they hold the crypto keys in their servers, and “phone companies have historically been very cooperative with wiretapping,” he says. Zimmermann,s protocols instead kept the keys only at endpoints—preventing the carriers and even his own servers from decrypting the content of a call.

These days, almost all telephony is digital—not just obvious forms like Skype, but cellular and landlines, too. So when a former U.S. Navy SEAL, Mike Janke, approached Zimmermann in 2011 with an idea for providing a service to help U.S. military members make secure calls home, he was game. They joined with Jon Callas, creator of Apple’s whole-disk encryption, to found Silent Circle. (The company originally offered e-mail, too—a service called Silent Mail. But many users were opting to store keys with Silent Mail, leaving the company vulnerable to an NSA request for data. The team killed Silent Mail and is rebuilding it so it stores the keys differently.)

No Breadcrumbs

Silent Circle had a missing piece: the hardware. “Over the years, when people asked ‘How safe can I be using your crypto software?’ I had to say, ‘We think we have some good crypto here, but the computer you are running it on might be owned by a hacker, and it won’t matter,” Zimmermann says. “With Blackphone we are trying to do something about that.”

Blackphone is an amalgamation of technologies. Silent Circle provides the encrypted voice and text services; the device is being made by Geeksphone, a Spanish company that specializes in phones that run open-source operating systems. Together they created PrivatOS, which gives more control over what data apps can see, encrypts data stored on the phone, and allows you to get wireless security updates directly from Blackphone, rather than relying on carriers. The two companies also brought on other vendors of privacy and security services. For example, one blocks tracking companies from seeing the websites you visit and the searches you make.

By February, they had one carrier lined up to sell the phone (though any buyer could use it and put a SIM card in it): Netherlands-based KPN, which also serves Belgium and Germany. They were talking to other carriers, too. It would be “the unique device that nobody has dared to make yet,” said Geeksphone,s 22-year-old founder, Javier Agüera—at least, nobody who had the average user in mind.

Fast-forward to late February. Zimmermann and his team sat at a sidewalk restaurant in Barcelona, munching tapas. It was the eve of Blackphone,s launch at the largest mobile trade show, Mobile World Congress. Early versions of the phone were in their pockets. As I joined the group and learned more about the phone, I became aware of my digital nakedness. I glanced at my new iPhone 5S. Opening my Wi-Fi settings, I saw available networks called Barcelona Wi-Fi, Cbarc 1, Spyder, and several others. All were of unknown trustworthiness, but I didn’t think it mattered; after all, I wasn’t connecting with any of them. But it turns out that my phone’s automatic process of seeking such signals meant it was notifying those routers of my phone’s ID number. This is already being exploited by retailers, who use Wi-Fi probes to track customers’ habits. And because information from apps is merged with data from Web browsers, shopping sites, and other sources, dozens of companies can use that ID number to keep tabs on me.

Mike Kershaw, Blackphone,s chief architect, came over to my side of the table. He proudly explained how Blackphone would prevent any such thing. Software Kershaw developed programs the phone not to search for Wi-Fi signals unless it is in a predefined geographical area, such as one around your home or office. So as we ate tapas, I was the only person at the table leaving digital breadcrumbs. The others had tools to prevent browsing history and search terms from being tied to their identity; I didn’t. They had fine-grained control over app permissions; I didn’t.

The next morning, near a modest booth at Mobile World Congress, some 200 journalists and analysts crowded the hallways for Blackphone,s launch announcement. “We are not a phone company adding a privacy feature,” Zimmermann said. “We are a privacy company selling a phone.” But it was already clear that this was a kind of anti-phone, going against the grain of the mainstream smartphone industry. Later that day, Zimmermann walked by Samsung’s enormous installation. It was bristling with Galaxy 5 phones, loaded with Android configured largely the way Google likes it: to gather data. “They’ve got a pretty big booth,” Zimmermann deadpanned.

Not NSA-Proof

Top security experts are reserving judgment on Blackphone until they can test the phone. It won’t ship until June. But the underlying encryption Silent Circle uses—and the evident paranoia of its creators—is widely admired. “I very much like Silent Circle’s solutions,” says Bruce Schneier, a cryptologist who has been calling for more security in communication technologies and wider use of encryption.

While the phone is resistant to everyday threats like hacking and snooping by data brokers, even the company concedes that it’s not NSA-proof, and it could have an Achilles’ heel: the apps that its users will inevitably download. Xuxian Jiang, a computer scientist at North Carolina State University and an authority on Android security, says that’s how devices acquire many of their vulnerabilities. Blackphone also doesn’t protect e-mail on its own; whether your e-mail uses encryption technology such as PGP depends on your e-mail provider. Still, Jiang says of the phone: “These are certainly good privacy improvements.”

There are a few competing efforts. Open Whisper Systems has released an encryption system for Android calls. Nonetheless, Blackphone is already establishing itself: by March, Zimmermann says, hundreds of thousands of units had been ordered. The company expects to sell millions of phones in the first two years. In many ways, the NSA revelations, the growing awareness of how consumers are being tracked by commercial interests, and conflicts like the one in Ukraine have been the best possible advertising. “It used to be an uphill battle to make people believe there was a need for this kind of technology,” Zimmermann says. “Not anymore.”

Further Details

· Brain Mapping

A new map, a decade in the works, shows structures of the brain in far greater detail than ever before, providing neuroscientists with a guide to its immense complexity.

Breakthrough

A high-resolution map that shows structures of the human brain as small as 20 micrometers.

Why It Matters

As neuroscientists try to understand how the brain works, they need a detailed map of its anatomy.

Key Players

Katrin Amunts, Jülich Research Centre
Alan Evans, Montreal Neurological Institute
Karl Deisseroth, Stanford University

Neuroscientists have made remarkable progress in recent years toward understanding how the brain works. And in coming years, Europe’s Human Brain Project will attempt to create a computational simulation of the human brain, while the U.S. BRAIN Initiative will try to create a wide-ranging picture of brain activity. These ambitious projects will greatly benefit from a new resource: detailed and comprehensive maps of the brain’s structure and its different regions.

As part of the Human Brain Project, an international team of researchers led by German and Canadian scientists has produced a three-dimensional atlas of the brain that has 50 times the resolution of previous such maps. The atlas, which took a decade to complete, required slicing a brain into thousands of thin sections and digitally stitching them back together with the help of supercomputers. Able to show details as small as 20 micrometers, roughly the size of many human cells, it is a major step forward in understanding the brain’s three-dimensional anatomy.
To guide the brain’s digital reconstruction, researchers led by Katrin Amunts at the Jülich Research Centre in Germany initially used an MRI machine to image the postmortem brain of a 65-year-old woman. The brain was then cut into ultrathin slices. The scientists stained the sections and then imaged them one by one on a flatbed scanner. Alan Evans and his coworkers at the Montreal Neurological Institute organized the 7,404 resulting images into a data set about a terabyte in size. Slicing had bent, ripped, and torn the tissue, so Evans had to correct these defects in the images. He also aligned each one to its original position in the brain. The result is mesmerizing: a brain model that you can swim through, zooming in or out to see the arrangement of cells and tissues.
At the start of the 20th century, a German neuroanatomist named Korbinian Brodmann parceled the human cortex into nearly 50 different areas by looking at the structure and organization of sections of brain under a microscope. “That has been pretty much the reference framework that we’ve used for 100 years,” Evans says. Now he and his coworkers are redoing Brodmann,s work as they map the borders between brain regions. The result may show something more like 100 to 200 distinct areas, providing scientists with a far more accurate road map for studying the brain’s different functions.
“We would like to have in the future a reference brain that shows true cellular resolution,” says Amunts—about one or two micrometers, as opposed to 20. That’s a daunting goal, for several reasons. One is computational: Evans says such a map of the brain might contain several petabytes of data, which computers today can’t easily navigate in real time, though he’s optimistic that they will be able to in the future. Another problem is physical: a brain can be sliced only so thin.
Advances could come from new techniques that allow scientists to see the arrangement of cells and nerve fibers inside intact brain tissue at very high resolution. Amunts is developing one such technique, which uses polarized light to reconstruct three-dimensional structures of nerve fibers in brain tissue. And a technique called Clarity, developed in the lab of Karl Deisseroth, a neuroscientist and bioengineer at Stanford University, allows scientists to directly see the structures of neurons and circuitry in an intact brain. The brain, like any other tissue, is usually opaque because the fats in its cells block light. Clarity melts the lipids away, replacing them with a gel-like substance that leaves other structures intact and visible. Though Clarity can be used on a whole mouse brain, the human brain is too big to be studied fully intact with the existing version of the technology. But Deisseroth says the technique can already be used on blocks of human brain tissue thousands of times larger than a thin brain section, making 3-D reconstruction easier and less error prone. And Evans says that while Clarity and polarized-light imaging currently give fantastic resolution to pieces of brain, “in the future we hope that this can be expanded to include a whole human brain.”
for more

Neuromorphic Chips

Microprocessors configured more like brains than traditional chips could soon make computers far more astute about what’s going on around them.

Breakthrough

An alternative design for computer chips that will enhance artificial intelligence.

Why It Matters

Traditional chips are reaching fundamental performance limits.

Key Players

Qualcomm
IBM
HRL Laboratories
Human Brain Project

A pug-size robot named pioneer slowly rolls up to the Captain America action figure on the carpet. They’re facing off inside a rough model of a child’s bedroom that the wireless-chip maker Qualcomm has set up in a trailer. The robot pauses, almost as if it is evaluating the situation, and then corrals the figure with a snowplow-like implement mounted in front, turns around, and pushes it toward three squat pillars representing toy bins. Qualcomm senior engineer Ilwoo Chang sweeps both arms toward the pillar where the toy should be deposited. Pioneer spots that gesture with its camera and dutifully complies. Then it rolls back and spies another action figure, Spider-Man. This time Pioneer beelines for the toy, ignoring a chessboard nearby, and delivers it to the same pillar with no human guidance.

This demonstration at Qualcomm’s headquarters in San Diego looks modest, but it’s a glimpse of the future of computing. The robot is performing tasks that have typically needed powerful, specially programmed computers that use far more electricity. Powered by only a smartphone chip with specialized software, Pioneer can recognize objects it hasn’t seen before, sort them by their similarity to related objects, and navigate the room to deliver them to the right location—not because of laborious programming but merely by being shown once where they should go. The robot can do all that because it is simulating, albeit in a very limited fashion, the way a brain works.
Later this year, Qualcomm will begin to reveal how the technology can be embedded into the silicon chips that power every manner of electronic device. These “neuromorphic” chips—so named because they are modeled on biological brains—will be designed to process sensory data such as images and sound and to respond to changes in that data in ways not specifically programmed. They promise to accelerate decades of fitful progress in artificial intelligence and lead to machines that are able to understand and interact with the world in human like ways. Medical sensors and devices could track individuals’ vital signs and response to treatments over time, learning to adjust dosages or even catch problems early. Your smartphone could learn to anticipate what you want next, such as background on someone you’re about to meet or an alert that it’s time to leave for your next meeting. Those self-driving cars Google is experimenting with might not need your help at all, and more adept Roombas wouldn’t get stuck under your couch. “We’re blurring the boundary between silicon and biological systems,” says Qualcomm’s chief technology officer, Matthew Grob.
Qualcomm’s chips won’t become available until next year at the earliest; the company will spend 2014 signing up researchers to try out the technology. But if it delivers, the project—known as the Zeroth program—would be the first large-scale commercial platform for neuromorphic computing. That’s on top of promising efforts at universities and at corporate labs such as IBM Research and HRL Laboratories, which have each developed neuromorphic chips under a $100 million project for the Defense Advanced Research Projects Agency. Likewise, the Human Brain Project in Europe is spending roughly 100 million euros on neuromorphic projects, including efforts at Heidelberg University and the University of Manchester. Another group in Germany recently reported using a neuromorphic chip and software modeled on insects’ odor-processing systems to recognize plant species by their flowers.
Today’s computers all use the so-called von Neumann architecture, which shuttles data back and forth between a central processor and memory chips in linear sequences of calculations. That method is great for crunching numbers and executing precisely written programs, but not for processing images or sound and making sense of it all. It’s telling that in 2012, when Google demonstrated artificial-intelligence software that learned to recognize cats in videos without being told what a cat was, it needed 16,000 processors to pull it off.
Continuing to improve the performance of such processors requires their manufacturers to pack in ever more, ever faster transistors, silicon memory caches, and data pathways, but the sheer heat generated by all those components is limiting how fast chips can be operated, especially in power-stingy mobile devices. That could halt progress toward devices that effectively process images, sound, and other sensory information and then apply it to tasks such as face recognition and robot or vehicle navigation.
No one is more acutely interested in getting around those physical challenges than Qualcomm, maker of wireless chips used in many phones and tablets. Increasingly, users of mobile devices are demanding more from these machines. But today’s personal-assistant services, such as Apple’s Siri and Google Now, are limited because they must call out to the cloud for more powerful computers to answer or anticipate queries. “We’re running up against walls,” says Jeff Gehlhaar, the Qualcomm vice president of technology who heads the Zeroth engineering team.
Neuromorphic chips attempt to model in silicon the massively parallel way the brain processes information as billions of neurons and trillions of synapses respond to sensory inputs such as visual and auditory stimuli. Those neurons also change how they connect with each other in response to changing images, sounds, and the like. That is the process we call learning. The chips, which incorporate brain-inspired models called neural networks, do the same. That’s why Qualcomm’s robot—even though for now it’s merely running software that simulates a neuromorphic chip—can put Spider-Man in the same location as Captain America without having seen Spider-Man before.
Qualcomm could add a “neural processing unit” to mobile-phone chips to handle sensory data and tasks such as image recognition.
Even if neuromorphic chips are nowhere near as capable as the brain, they should be much faster than current computers at processing sensory data and learning from it. Trying to emulate the brain just by using special software on conventional processors—the way Google did in its cat experiment—is way too inefficient to be the basis of machines with still greater intelligence, says Jeff Hawkins, a leading thinker on AI who created the Palm Pilot before cofounding Numenta, a maker of brain-inspired software. “There’s no way you can build it [only] in software,” he says of effective AI. “You have to build this in silicon.”
Neural Channel
As smartphones have taken off, so has Qualcomm, whose market capitalization now tops Intel’s. That’s thanks in part to the hundreds of wireless-communications patents that Qualcomm shows off on two levels of a seven-story atrium lobby at its San Diego headquarters. Now it’s looking to break new ground again. First in coöperation with Brain Corp., a neuroscience startup it invested in and that is housed at its headquarters, and more recently with its own growing staff, it has been quietly working for the past five years on algorithms to mimic brain functions as well as hardware to execute them. The Zeroth project has initially focused on robotics applications because the way robots can interact with the real world provides broader lessons about how the brain learns—lessons that can then be applied in smartphones and other products. Its name comes from Isaac Asimov,s “Zeroth Law” of robotics: “A robot may not harm humanity, or, by inaction, allow humanity to come to harm.”
The idea of neuromorphic chips dates back decades. Carver Mead, the Caltech professor emeritus who is a legend in integrated-circuit design, coined the term in a 1990 paper, describing how analog chips—those that vary in their output, like real-world phenomena, in contrast to the binary, on-or-off nature of digital chips—could mimic the electrical activity of neurons and synapses in the brain. But he struggled to find ways to reliably build his analog chip designs. Only one arguably neuromorphic processor, a noise suppression chip made by Audience, has sold in the hundreds of millions. The chip, which is based on the human cochlea, has been used in phones from Apple, Samsung, and others.

As a commercial company, Qualcomm has opted for pragmatism over sheer performance in its design. That means the neuromorphic chips it’s developing are still digital chips, which are more predictable and easier to manufacture than analog ones. And instead of modeling the chips as closely as possible on actual brain biology, Qualcomm’s project emulates aspects of the brain’s behavior. For instance, the chips encode and transmit data in a way that mimics the electrical spikes generated in the brain as it responds to sensory information. “Even with this digital representation, we can reproduce a huge range of behaviors we see in biology,” says M. Anthony Lewis, the project engineer for Zeroth.

The chips would fit neatly into the existing business of Qualcomm, which dominates the market for mobile-phone chips but has seen revenue growth slow. Its Snapdragon mobile-phone chips include components such as graphics processing units; Qualcomm could add a “neural processing unit” to the chips to handle sensory data and tasks such as image recognition and robot navigation. And given that Qualcomm has a highly profitable business of licensing technologies to other companies, it would be in a position to sell the rights to use algorithms that run on neuromorphic chips. That could lead to sensor chips for vision, motion control, and other applications.
Cognitive Companion
Matthew Grob was startled, then annoyed, when he heard the theme to Sanford and Son start playing in the middle of a recent meeting. It turns out that on a recent trip to Spain, he had set his smartphone to issue a reminder using the tune as an alarm, and the phone thought it was time to play it again. That’s just one small example of how far our personal devices are from being intelligent. Grob dreams of a future when instead of monkeying with the settings of his misbehaving phone, as he did that day, all he would have to do is bark, “Don’t do that!” Then the phone might learn that it should switch off the alarm when he’s in a new time zone.
Qualcomm is especially interested in the possibility that neuromorphic chips could transform smartphones and other mobile devices into cognitive companions that pay attention to your actions and surroundings and learn your habits over time. “If you and your device can perceive the environment in the same way, your device will be better able to understand your intentions and anticipate your needs,” says Samir Kumar, a business development director at Qualcomm’s research lab.
Pressed for examples, Kumar ticks off a litany: If you tag your dog in a photo, your phone’s camera would recognize the pet in every subsequent photo. At a soccer game, you could tell the phone to snap a photo only when your child is near the goal. At bedtime, it would know without your telling it to send calls to voice mail. In short, says Grob, your smartphone would have a digital sixth sense.
Qualcomm executives are reluctant to embark on too many flights of fancy before their chip is even available. But neuromorphic researchers elsewhere don’t mind speculating. According to Dharmendrra Modha, a top IBM researcher in San Jose, such chips might lead to glasses for the blind that use visual and auditory sensors to recognize objects and provide audio cues; health-care systems that monitor vital signs, provide early warnings of potential problems, and suggest ways to individualize treatments; and computers that draw on wind patterns, tides, and other indicators to predict tsunamis more accurately. At HRL this summer, principal research scientist Narayan Srinivasa plans to test a neuromorphic chip in a bird-size device from AeroVironment that will be flown around a couple of rooms. It will take in data from cameras and other sensors so it can remember which room it’s in and learn to navigate that space more adeptly, which could lead to more capable drones.
It will take programmers time to figure out the best way to exploit the hardware. “It’s not too early for hardware companies to do research,” says Dileep George, cofounder of the artificial-intelligence startup Vicarious. “The commercial products could take a while.” Qualcomm executives don’t disagree. But they’re betting that the technology they expect to launch this year will bring those products a lot closer to reality

Genome Editing

The ability to create primates with intentional mutations could provide powerful new ways to study complex and genetically baffling brain disorders.

Breakthrough

The use of a genome-tool to create two monkeys with specific genetic mutations.

Why It Matters

The ability to modify targeted genes in primates is a valuable tool in the study of human diseases.

Key Players

Yunnan Key Laboratory
Jennifer Doudna, UC Berkeley
Feng Zhang, MIT
George Church, Harvard

The Experiment

By Christina Larson

Until recently, Kunming, capital of China’s southwestern Yunnan province, was known mostly for its palm trees, its blue skies, its laid-back vibe, and a steady stream of foreign backpackers bound for nearby mountains and scenic gorges. But Kunming,s reputation as a provincial backwater is rapidly changing. On a plot of land on the outskirts of the city—wilderness 10 years ago, and today home to a genomic research facility—scientists have performed a provocative experiment. They have created a pair of macaque monkeys with precise genetic mutations.

Last November, the female monkey twins, Mingming and Lingling, were born here on the sprawling research campus of Kunming Biomedical International and its affiliated Yunnan Key Laboratory of Primate Biomedical Research. The macaques had been conceived via in vitro fertilization. Then scientists used a new method of DNA engineering known as CRISPR to modify the fertilized eggs by editing three different genes, and they were implanted into a surrogate macaque mother. The twins’ healthy birth marked the first time that CRISPR has been used to make targeted genetic modifications in primates—potentially heralding a new era of biomedicine in which complex diseases can be modeled and studied in monkeys.
CRISPR, which was developed by researchers at the University of California, Berkeley, Harvard, MIT, and elsewhere over the last several years, is already transforming how scientists think about genetic engineering, because it allows them to make changes to the genome precisely and relatively easily (see “Genome Surgery,” March/April). The goal of the experiment at Kunming is to confirm that the technology can create primates with multiple mutations, explains Weizhi Ji, one of the architects of the experiment.
Ji began his career at the government-affiliated Kunming Institute of Zoology in 1982, focusing on primate reproduction. China was “a very poor country” back then, he recalls. “We did not have enough funding for research. We just did very simple work, such as studying how to improve primate nutrition.” China’s science ambitions have since changed dramatically. The campus in Kunming boasts extensive housing for monkeys: 75 covered homes, sheltering more than 4,000 primates—many of them energetically swinging on hanging ladders and scampering up and down wire mesh walls. Sixty trained animal keepers in blue scrubs tend to them full time.

The lab where the experiment was performed includes microinjection systems, which are microscopes pointed at a petri dish and two precision needles, controlled by levers and dials. These are used both for injecting sperm into eggs and for the gene editing, which uses “guide” RNAs that direct a DNA-cutting enzyme to genes. When I visited, a young lab technician was intently focused on twisting dials to line up sperm with an egg. Injecting each sperm takes only a few seconds. About nine hours later, when an embryo is still in the one-cell stage, a technician will use the same machine to inject it with the CRISPR molecular components; again, the procedure takes just a few seconds.
During my visit in late February, the twin macaques were still only a few months old and lived in incubators, monitored closely by lab staff. Indeed, Ji and his coworkers plan to continue to closely watch the monkeys to detect any consequences of the pioneering genetic modifications.

The Impact

By Amanda Schaffer

The new genome-editing tool called CRISPR, which researchers in China used to genetically modify monkeys, is a precise and relatively easy way to alter DNA at specific locations on chromosomes. In early 2013, U.S. scientists showed it could be used to genetically engineer any type of animal cells, including human ones, in a petri dish. But the Chinese researchers were the first to demonstrate that this approach can be used in primates to create offspring with specific genetic alterations.

“The idea that we can modify primates easily with this technology is powerful,” says Jennifer Doudna, a professor of molecular and cell biology at the University of California, Berkeley, and a developer of CRISPR. The creation of primates with intentional gene alterations could lead to powerful new ways to study complex human diseases. It also poses new ethical dilemmas. From a technical perspective, the Chinese primate research suggests that scientists could probably alter fertilized human eggs with CRISPR; if monkeys are any guide, such eggs could grow to be genetically modified babies. But “whether that would be a good idea is a much harder question,” says Doudna.
The prospect of designer babies remains remote and far from the minds of most researchers developing CRISPR. Far more imminent are the potential opportunities to create animals with mutations linked to human disorders. Experimenting with primates is expensive and can raise concerns about animal welfare, says Doudna. But the demonstration that CRISPR works in monkeys has gotten “a lot of people thinking about cases where primate models may be important.”
At the top of that list is the study of brain disorders. Robert Desimone, director of MIT’s McGovern Institute for Brain Research, says that there is “quite a bit of interest” in using CRISPR to generate monkey models of diseases like autism, schizophrenia, Alzheimer’s disease, and bipolar disorder. These disorders are difficult to study in mice and other rodents; not only do the affected behaviors differ substantially between these animals and humans, but the neural circuits involved in the disorders can be different. Many experimental psychiatric drugs that appeared to work well in mice have not proved successful in human trials. As a result of such failures, many pharmaceutical companies have scaled back or abandoned their efforts to develop treatments.
Primate models could be especially helpful to researchers trying to make sense of the growing number of mutations that genetic studies have linked to brain disorders. The significance of a specific genetic variant is often unclear; it could be a cause of a disorder, or it could just be indirectly associated with the disease. CRISPR could help researchers tease out the mutations that actually cause the disorders: they would be able to systematically introduce the suspected genetic variants into monkeys and observe the results. CRISPR is also useful because it allows scientists to create animals with different combinations of mutations, in order to assess which ones—or which combinations of them—matter most in causing disease. This complex level of manipulation is nearly impossible with other methods.
Guoping Feng, a professor of neuroscience at MIT, and Feng Zhang, a colleague at the Broad Institute and McGovern Brain Institute who showed that CRISPR could be used to modify the genomes of human cells, are working with Chinese researchers to create macaques with a version of autism. They plan to mutate a gene called SHANK3 in fertilized eggs, producing monkeys that can be used to study the basic science of the disorder and test possible drug treatments. (Only a small percentage of people with autism have the SHANK3 mutation, but it is one of the few genetic variants that lead to a high probability of the disorder.)
The Chinese researchers responsible for the birth of the genetically engineered monkeys are still focusing on developing the technology, says Weizhi Ji, who helped lead the effort at the Yunnan Key Laboratory of Primate Biomedical Research in Kunming. However, his group hopes to create monkeys with Parkinson’s, among other brain disorders. The aim would be to look for early signs of the disease and study the mechanisms that allow it to progress.
The most dramatic possibility raised by the primate work, of course, would be using CRISPR to change the genetic makeup of human embryos during in vitro fertilization. But while such manipulation should be technically possible, most scientists do not seem eager to pursue it.
Indeed, the safety concerns would be daunting. When you think about “messing with a single cell that is potentially going to become a living baby,” even small errors or side effects could turn out to have enormous consequences, says Hank Greely, director of the Center for Law and the Biosciences at Stanford. And why even bother? For most diseases with simple genetic causes, it wouldn’t be worthwhile to use CRISPR; it would make more sense for couples to “choose a different embryo that doesn’t have the disease,” he says. This is already possible as part of in vitro fertilization, using a procedure called preimplantation genetic diagnosis.
It’s possible to speculate that parents might wish to alter multiple genes in order to reduce children’s risk, say, of heart disease or diabetes, which have complex genetic components. But for at least the next five to 10 years, that, says Greely, “just strikes me as borderline crazy, borderline implausible.” Many, if not most, of the traits that future parents might hope to alter in their kids may also be too complex or poorly understood to make reasonable targets for intervention. Scientists don’t understand the genetic basis, for instance, of intelligence or other higher-order brain functions—and that is unlikely to change for a long time. Ji says creating humans with CRISPR-edited genomes is “very possible,” but he concurs that “considering the safety issue, there would still be a long way to go.” In the meantime, his team hopes to use genetically modified monkeys to “establish very efficient animal models for human diseases, to improve human health in the future.”

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Microscale 3-D Printing

Inks made from different types of materials, precisely applied, are greatly expanding the kinds of things that can be printed.

Breakthrough

3-D printing that uses multiple materials to create objects such as biological tissue with blood vessels.

Why It Matters

Making biological materials with desired functions could lead to artificial organs and novel cyborg parts.

Key Players

Jennifer Lewis, Harvard University

Michael McAlpine, Princeton University

Keith Martin, University of Cambridge

Despite the excitement that 3-D printing has generated, its capabilities remain rather limited. It can be used to make complex shapes, but most commonly only out of plastics. Even manufacturers using an advanced version of the technology known as additive manufacturing typically have expanded the material palette only to a few types of metal alloys. But what if 3-D printers could use a wide assortment of different materials, from living cells to semiconductors, mixing and matching the “inks” with precision?

Jennifer Lewis, a materials scientist at Harvard University, is developing the chemistry and machines to make that possible. She prints intricately shaped objects from “the ground up,” precisely adding materials that are useful for their mechanical properties, electrical conductivity, or optical traits. This means 3-D printing technology could make objects that sense and respond to their environment. “Integrating form and function,” she says, “is the next big thing that needs to happen in 3-D printing.”

: For the demonstration, the group formulated four polymer inks, each dyed a different color

: The different inks are placed in standard print heads.

Bottom: By sequentially and precisely depositing the inks in a process guided by the group’s software, the printer quickly produces the colorful lattice.

A group at Princeton University has printed a bionic ear, combining biological tissue and electronics (see “Cyborg Parts”), while a team of researchers at the University of Cambridge has printed retinal cells to form complex eye tissue. But even among these impressive efforts to extend the possibilities of 3-D printing, Lewis’s lab stands out for the range of materials and types of objects it can print.
Last year, Lewis and her students showed they could print the microscopic electrodes and other components needed for tiny lithium-ion batteries (see “Printing Batteries”). Other projects include printed sensors fabricated on plastic patches that athletes could one day wear to detect concussions and measure violent impacts. Most recently, her group printed biological tissue interwoven with a complex network of blood vessels. To do this, the researchers had to make inks out of various types of cells and the materials that form the matrix supporting them. The work addresses one of the lingering challenges in creating artificial organs for drug testing or, someday, for use as replacement parts: how to create a vascular system to keep the cells alive.

Top: Inks made of silver nanoparticles are used to print electrodes as small as a few micrometers.

Bottom: As in the other 3-D printing processes, the operation is controlled and monitored by computers.

: Jennifer Lewis,s goal is to print complex architectures that integrate form and function

: A glove with strain sensors is made by printing electronics into a stretchable elastomer.

In a basement lab a few hundred yards from Lewis’s office, her group has jury-rigged a 3-D printer, equipped with a microscope, that can precisely print structures with features as small as one micrometer (a human red blood cell is around 10 micrometers in diameter). Another, larger 3-D printer, using printing nozzles with multiple outlets to print multiple inks simultaneously, can fabricate a meter-sized sample with a desired microstructure in minutes.
The secret to Lewis’s creations lies in inks with properties that allow them to be printed during the same fabrication process. Each ink is a different material, but they all can be printed at room temperature. The various types of materials present different challenges; cells, for example, are delicate and easily destroyed as they are forced through the printing nozzle. In all cases, though, the inks must be formulated to flow out of the nozzle under pressure but retain their form once in place—think of toothpaste, Lewis says.

Before coming to Harvard from the University of Illinois at Urbana- Champaign last year, Lewis had spent more than a decade developing 3-D printing techniques using ceramics, metal nanoparticles, polymers, and other nonbiological materials. When she set up her new lab at Harvard and began working with biological cells and tissues for the first time, she hoped to treat them the same way as materials composed of synthetic particles. That idea might have been a bit naïve, she now acknowledges. Printing blood vessels was an encouraging step toward artificial tissues capable of the complex biological functions found in organs. But working with the cells turns out to be “really complex,” she says. “And there’s a lot more that we need to do before we can print a fully functional liver or kidney. But we’ve taken the first step.”

Monday, September 15, 2014

DRONES

Smart wind and solar power agricultural DRONES.