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Archive for the ‘information science’ category

Aug 7, 2018

Engineers teach a drone to herd birds away from airports autonomously

Posted by in categories: drones, engineering, information science, robotics/AI

Engineers at Caltech have developed a new control algorithm that enables a single drone to herd an entire flock of birds away from the airspace of an airport. The algorithm is presented in a study in IEEE Transactions on Robotics.

The project was inspired by the 2009 “Miracle on the Hudson,” when US Airways Flight 1549 struck a flock of geese shortly after takeoff and pilots Chesley Sullenberger and Jeffrey Skiles were forced to land in the Hudson River off Manhattan.

“The passengers on Flight 1549 were only saved because the pilots were so skilled,” says Soon-Jo Chung, an associate professor of aerospace and Bren Scholar in the Division of Engineering and Applied Science as well as a JPL research scientist, and the principal investigator on the drone herding project. “It made me think that next time might not have such a happy ending. So I started looking into ways to protect from birds by leveraging my research areas in autonomy and robotics.”

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Aug 6, 2018

Building the backbone of a smarter smart home

Posted by in categories: habitats, information science, robotics/AI

The state of artificial intelligence (AI) in smart homes nowadays might be likened to a smart but moody teenager: It’s starting to hit its stride and discover its talents, but it doesn’t really feel like answering any questions about what it’s up to and would really rather be left alone, OK?

William Yeoh, assistant professor of computer science and engineering in the School of Engineering & Applied Science at Washington University in St. Louis, is working to help smart-home AI to grow up.

The National Science Foundation (NSF) awarded Yeoh a $300,000 grant to assist in developing smart-home AI algorithms that can determine what a user wants by both asking questions and making smart guesses, and then plan and schedule accordingly. Beyond being smart, the system needs to be able to communicate and to explain why it is proposing the schedule it proposed to the user.

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Aug 5, 2018

Employees at Google, Amazon and Microsoft Have Threatened to Walk Off the Job Over the Use of AI

Posted by in categories: biotech/medical, ethics, information science, military, robotics/AI

There is. Our engagement with AI will transform us. Technology always does, even while we are busy using it to reinvent our world. The introduction of the machine gun by Richard Gatling during America’s Civil War, and its massive role in World War I, obliterated our ideas of military gallantry and chivalry and emblazoned in our minds Wilfred Owen’s imagery of young men who “die as Cattle.” The computer revolution beginning after World War II ushered in a way of understanding and talking about the mind in terms of hardware, wiring and rewiring that still dominates neurology. How will AI change us? How has it changed us already? For example, what does reliance on navigational aids like Waze do to our sense of adventure? What happens to our ability to make everyday practical judgments when so many of these judgments—in areas as diverse as credit worthiness, human resources, sentencing, police force allocation—are outsourced to algorithms? If our ability to make good moral judgments depends on actually making them—on developing, through practice and habit, what Aristotle called “practical wisdom”—what happens when we lose the habit? What becomes of our capacity for patience when more and more of our trivial interests and requests are predicted and immediately met by artificially intelligent assistants like Siri and Alexa? Does a child who interacts imperiously with these assistants take that habit of imperious interaction to other aspects of her life? It’s hard to know how exactly AI will alter us. Our concerns about the fairness and safety of the technology are more concrete and easier to grasp. But the abstract, philosophical question of how AI will impact what it means to be human is more fundamental and cannot be overlooked. The engineers are right to worry. But the stakes are higher than they think.

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Aug 4, 2018

On Using Hyperopt: Advanced Machine Learning

Posted by in categories: information science, robotics/AI

In Machine Learning one of the biggest problem faced by the practitioners in the process is choosing the correct set of hyper-parameters. And it takes a lot of time in tuning them accordingly, to stretch the accuracy numbers.

For instance lets take, SVC from well known library Scikit-Learn, class implements the Support Vector Machine algorithm for classification which contains more than 10 hyperparameters, now adjusting all ten to minimize the loss is very difficult just by using hit and trial. Though Scikit-Learn provides Grid Search and Random Search, but the algorithms are brute force and exhaustive, however hyperopt implements distributed asynchronous algorithm for hyperparameter optimization.

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Jul 31, 2018

Teenager Finds Classical Alternative to Quantum Recommendation Algorithm

Posted by in categories: computing, information science, quantum physics

18-year-old Ewin Tang has proven that classical computers can solve the “recommendation problem” nearly as fast as quantum computers. The result eliminates one of the best examples of quantum speedup.

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Jul 30, 2018

AI-driven robot hand spent hundred years teaching itself to rotate cube

Posted by in categories: information science, robotics/AI, virtual reality

A reinforcement learning algorithm allows Dactyl to learn physical tasks by practicing them in a virtual-reality environment.

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Jul 30, 2018

Artificial intelligence can predict your personality

Posted by in categories: information science, robotics/AI

“The eyes are the window of the soul.” Cicero said that. But it’s a bunch of baloney.

Unless you’re a state-of-the-art set of machine-learning algorithms with the ability to demonstrate links between eye movements and four of the big five personality traits.

If that’s the case, then Cicero was spot on.

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Jul 28, 2018

XTPL ultra-precise Nanometric Printer receives Honorable Mention at Display Week 2018 I-Zone

Posted by in categories: biotech/medical, information science, nanotechnology, solar power, sustainability, wearables

Closing in on molecular manufacturing…


http://xt-pl.com received an honorable mention from I-Zone judges for its innovative product that prints extremely fine film structures using nanomaterials. XTPL’s interdisciplinary team is developing and commercializing an innovative technology that enables ultra-precise printing of electrodes up to several hundred times thinner than a human hair – conducive lines as thin as 100 nm. XTPL is facilitating the production of a new generation of transparent conductive films (TCFs) that are widely used in manufacturing. XTPL’s solution has a potentially disruptive technology in the production of displays, monitors, touchscreens, printed electronics, wearable electronics, smart packaging, automotive, medical devices, photovoltaic cells, biosensors, and anti-counterfeiting. The technology is also applicable to the open-defect repair industry (the repair of broken metallic connections in thin film electronic circuits) and offers cost-effective, non-toxic, flexible industry-adapted solutions.

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Jul 27, 2018

Artificial intelligence has learned to probe the minds of other computers

Posted by in categories: information science, robotics/AI

Algorithms achieve a machine theory of mind.

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Jul 26, 2018

How artificial intelligence is changing the pharmaceutical industry

Posted by in categories: biotech/medical, information science, robotics/AI

But the great potential of artificial intelligence shall become fully clear when considering its possible applications to drug discovery. It seems an era ago since the Human Genome Project was completed in 2003; since then, sequencing capabilities and softwares for data analysis rapidly established themselves as the new paradigm for drug discovery thanks to the increasing availability of IT technologies and the institutional and governmental support to big data analytics’ policies.

The exponential growth of the market

The annual growth rate of the market of artificial intelligence for healthcare applications has been recently estimated by Global Market Insights to be 40% CAGR (Compounded Average Growth Rate) per year up to 2024, starting from a value on $ 750 million in 2016.

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