Lifeboat Foundation: Safeguarding Humanity
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Category: information science

Standard utopias and standard dystopias are each perfect after their own particular fashion. We live somewhere queasier—a world in which technology is developing in ways that make it increasingly hard to distinguish human beings from artificial things. The world that the Internet and social media have created is less a system than an ecology, a proliferation of unexpected niches, and entities created and adapted to exploit them in deceptive ways. Vast commercial architectures are being colonized by quasi-autonomous parasites. Scammers have built algorithms to write fake books from scratch to sell on Amazon, compiling and modifying text from other books and online sources such as Wikipedia, to fool buyers or to take advantage of loopholes in Amazon’s compensation structure. Much of the world’s financial system is made out of bots—automated systems designed to continually probe markets for fleeting arbitrage opportunities. Less sophisticated programs plague online commerce systems such as eBay and Amazon, occasionally with extraordinary consequences, as when two warring bots bid the price of a biology book up to $23,698,655.93 (plus $3.99 shipping).

In other words, we live in Philip K. Dick’s future, not George Orwell’s or Aldous Huxley’s. Dick was no better a prophet of technology than any science fiction writer, and was arguably worse than most. His imagined worlds jam together odd bits of fifties’ and sixties’ California with rocket ships, drugs, and social speculation. Dick usually wrote in a hurry and for money, and sometimes under the influence of drugs or a recent and urgent personal religious revelation.

Still, what he captured with genius was the ontological unease of a world in which the human and the abhuman, the real and the fake, blur together. As Dick described his work (in the opening essay to his 1985 collection, I Hope I Shall Arrive Soon):

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From afar, it looks like a steampunk chandelier. An intricate collection of tubes and wires that culminate in a small steel cylinder at the bottom. It is, in fact, one of the most sophisticated quantum computers ever built. The processor inside has 50 quantum bits, or qubits, that process tasks in a (potentially) revolutionary way. Normally, information is created and stored as a series of ones and zeroes. Qubits can represent both values at the same time (known as superposition), which means a quantum computer can theoretically test the two simultaneously. Add more qubits and this hard-to-believe computational power increases.

Last November, IBM unveiled the world’s first 50-qubit quantum computer. It lives in a laboratory, inside a giant white case, with pumps to keep it cool and some traditional computers to manage the tasks or algorithms being initiated. At CES this year, the company brought the innards — the wires and tubes required to send signals to the chip and keep the system cool — so reporters and attendees could better understand how it works. The biggest challenge, IBM Research Vice President Jeffrey Welser told me, is isolating the chip from unwanted “noise.” This includes electrical, magnetic and thermal noise — just the temperature of the room renders the whole machine useless.

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Today at CES, Samsung unveiled DRVLINE, a hardware and software platform that will allow car makers to create customized, technologically advanced autonomous vehicles. Many platforms are an all-or-nothing solution, which forces users to adopt the entire package en masse, without any sort of customization. DRVLINE, however, allows vendors to swap and customize individual components, building the vehicle to their specifications, as well as allowing for rapidly evolving technology.

“Building an autonomous platform requires close collaboration across industry, as one company cannot deliver on this enormous opportunity alone,” said Young Sohn, the president and chief strategy officer of Samsung. “The challenge is simply too big and too complex. Through the DRVLINE platform, we’re inviting the best and brightest from the automotive industry to join us, and help shape the future of the car of tomorrow, today.”

The first DRVLINE initiative will be a camera that features lane departure warnings, adaptive cruise control, collision warning and algorithms that can deliver warnings about pedestrians. The system will start shipping this year.

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Wirelessly powered, biomimetic spybots…

A new contest seeks flight systems inspired by Mother Nature and powered by directed-energy beams.

Tired: multi-rotor copters and fixed-wing drones. Wired: flying robots that move like living animals, are crafted of next-generation materials, and draw their power not from batteries but energy beamed from nearby aircraft.

On Wednesday, the Defense Enterprise Science Initiative, or DESI, announced a competition for basic science grants to build “new paradigms for autonomous flight, with a focus on highly-maneuverable platforms and algorithms for flight control and decision making.” An accompanying Broad Agency Announcement gets more specific: basically, they’re looking for bat-like drones that can be powered with directed-energy beams.

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December was a big month for advocates of regulating artificial intelligence. First, a bipartisan group of senators and representatives introduced the Future of A.I. Act, the first federal bill solely focused on A.It would create an advisory committee to make recommendations about A.I. — on topics including the technology’s effect on the American work force and strategies to protect the privacy rights of those it impacts. Then the New York City Council approved a first-of-its-kind bill that once signed into law will create a task force to examine its own use of automated decision systems, with the ultimate goal of making its use of algorithms fairer and more transparent.

Sure, the technology poses risks. But the current approach to regulating it is a mistake.

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China has unveiled three-year plans to increase the country’s economic competitiveness by developing “key technologies” in nine industrial sectors, from robotics to railways.

Other areas include smart cars, robotics, advanced shipbuilding and maritime equipment, modern agricultural machinery, advanced medical devices and drugs, new materials, smart manufacturing and machine tools.

The aim is “to make China a powerful manufacturing country” and upgrade the nation’s industrial power through “the internet, big data and artificial intelligence”, the commission said.

To achieve that goal, the agency has laid out specific targets to develop key technologies and guide research and the flow of funds in each sector.

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After less than eight months of development, the algorithms are helping intel analysts exploit drone video over the battlefield.

Earlier this month at an undisclosed location in the Middle East, computers using special algorithms helped intelligence analysts identify objects in a video feed from a small ScanEagle drone over the battlefield.

A few days into the trials, the computer identified objects — people, cars, types of building — correctly about 60 percent of the time. Just over a week on the job — and a handful of on-the-fly software updates later — the machine’s accuracy improved to around 80 percent. Next month, when its creators send the technology back to war with more software and hardware updates, they believe it will become even more accurate.

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Researchers have developed an easy-to-build camera that produces 3D images from a single 2D image without any lenses. In an initial application of the technology, the researchers plan to use the new camera, which they call DiffuserCam, to watch microscopic neuron activity in living mice without a microscope. Ultimately, it could prove useful for a wide range of applications involving 3D capture.

The camera is compact and inexpensive to construct because it consists of only a diffuser — essentially a bumpy piece of plastic — placed on top of an image sensor. Although the hardware is simple, the software it uses to reconstruct high resolution 3D is very complex.

“The DiffuserCam can, in a single shot, capture 3D information in a large volume with high resolution,” said the research team leader Laura Waller, University of California, Berkeley. “We think the camera could be useful for self-driving cars, where the 3D information can offer a sense of scale, or it could be used with machine learning algorithms to perform face detection, track people or automatically classify objects.”

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Brendan John Frey FRSC (born 29 August 1968) is a Canadian-born machine learning and genome biology researcher, known mainly for his work on factor graphs, the wake-sleep algorithm for deep learning, and using machine learning to model genome biology and understand genetic disorders. He founded Deep Genomics and is currently its CEO, and he is a Professor of Engineering and Medicine at the University of Toronto. He co-developed a new computational approach to identifying the genetic determinants of disease, was one of the first researchers to successfully train a deep neural network, and was a pioneer in the introduction of iterative message-passing algorithms.

Frey studied computer engineering and physics at the University of Calgary (BSc 1990) and the University of Manitoba (MSc 1993), and then studied neural networks and graphical models as a doctoral candidate at the University of Toronto under the supervision of Geoffrey Hinton (PhD 1997). He was an invited participant of the Machine Learning program at the Isaac Newton Institute for Mathematical Sciences in Cambridge, UK (1997) and was a Beckman Fellow at the University of Illinois at Urbana Champaign (1999).

Following his undergraduate studies, Frey worked as a Junior Research Scientist at Bell-Northern Research from 1990 to 1991. After completing his postdoctoral studies at the University of Illinois at Urbana-Champaign, Frey was an Assistant Professor in the Department of Computer Science at the University of Waterloo, from 1999 to 2001.

In 2001, Frey joined the Department of Electrical and Computer Engineering at the University of Toronto and was cross-appointed to the Department of Computer Science, the Banting and Best Department of Medical Research and the Terrence Donnelly Centre for Cellular and Biomolecular Research. From 2008 to 2009, he was a Visiting Researcher at Microsoft Research, Cambridge, UK, and a Visiting Professor in the Cavendish Laboratories and Darwin College at Cambridge University. Between 2001 and 2014, Frey consulted for several groups at Microsoft Research and acted as a member of its Technical Advisory Board.

In 2014, Frey co-founded Deep Genomics, a Toronto company that develops machine learning methods to model the deep biological architectures that relate genetic mutations to disease. The company’s goal is to bridge the genotype-phenotype gap, which is a pain point in genetic testing, pharmaceuticals, personalized medicine and health insurance.

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When Kumar lost his job, he became part of a wave of layoffs washing through the Indian IT industry—a term that includes, in its vastness, call centers, engineering services, business process outsourcing firms, and infrastructure management and software companies. The recent layoffs are part of the industry’s most significant period of churn since it began to boom two decades ago. Companies don’t necessarily attribute these layoffs directly to automation, but at the same time, they constantly identify automation as the spark for huge changes in the industry. Bots, machine learning, and algorithms that robotically execute processes are rendering old skills redundant, recasting the idea of work and making a smaller labor force seem likely.

Technology outsourcing has been India’s only reliable job creator in the past 30 years. Now artificial intelligence threatens to wipe out those gains.

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