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Archive for the ‘big data’ category: Page 3

Apr 14, 2016

Website Seeks to Make Government Data Easier to Sift Through — By Steve Lohr | The New York Times

Posted by in categories: big data, government

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“This abundance of data can be a gold mine for discovery and insights, but finding the nuggets can be arduous, requiring special skills.

A project coming out of the M.I.T. Media Lab on Monday seeks to ease that challenge and to make the value of government data available to a wider audience. The project, called Data USA, bills itself as “the most comprehensive visualization of U.S. public data.” It is free, and its software code is open source, meaning that developers can build custom applications by adding other data.”

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Apr 7, 2016

Imperial ambitions | The Economist

Posted by in categories: augmented reality, big data, business, drones, internet, Mark Zuckerberg, robotics/AI, virtual reality

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“The scale of Facebook’s ambition, and the rivalries it faces, reflect a consensus that these technologies will transform how people interact with each other, with data and with their surroundings.”

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Mar 31, 2016

An Update on fast Transit Routing with Transfer Patterns | Google Research Blog

Posted by in categories: automation, big data, business, complex systems, computing, economics, engineering, environmental, transportation

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“What is the best way to get from A to B by public transit? Google Maps is answering such queries for over 20,000 cities and towns in over 70 countries around the world, including large metro areas like New York, São Paulo or Moscow, and some complete countries, such as Japan or Great Britain.”

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Feb 23, 2016

Play nice! How the internet is trying to design out toxic behavior — By Gaby Hinsliff | The Guardian

Posted by in categories: big data, computing, education, ethics, information science, internet

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“Online abuse can be cruel – but for some tech companies it is an existential threat. Can giants such as Facebook use behavioural psychology and persuasive design to tame the trolls?”

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Jan 19, 2016

Connecting The Dots to Get the Big Picture with Artificial Intelligence

Posted by in categories: big data, disruptive technology, economics, information science, machine learning

Ask the average passerby on the street to describe artificial intelligence and you’re apt to get answers like C-3PO and Apple’s Siri. But for those who follow AI developments on a regular basis and swim just below the surface of the broad field , the idea that the foreseeable AI future might be driven more by Big Data rather than big discoveries is probably not a huge surprise. In a recent interview with Data Scientist and Entrepreneur Eyal Amir, we discussed how companies are using AI to connect the dots between data and innovation.

Image credit: Startup Leadership Program Chicago

Image credit: Startup Leadership Program Chicago

According to Amir, the ability to make connections between big data together has quietly become a strong force in a number of industries. In advertising for example, companies can now tease apart data to discern the basics of who you are, what you’re doing, and where you’re going, and tailor ads to you based on that information.

“What we need to understand is that, most of the time, the data is not actually available out there in the way we think that it is. So, for example I don’t know if a user is a man or woman. I don’t know what amounts of money she’s making every year. I don’t know where she’s working,” said Eyal. “There are a bunch of pieces of data out there, but they are all suggestive. (But) we can connect the dots and say, ‘she’s likely working in banking based on her contacts and friends.’ It’s big machines that are crunching this.”

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Dec 23, 2015

Airborne innovation | The Economist

Posted by in categories: big data, business, drones, governance, satellites

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“The most successful drone firms could be those that do not make them”

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Sep 28, 2015

Intelligent machines: Making AI work in the real world — By Eric Schmidt | BBC News

Posted by in categories: big data, computing, innovation, machine learning, robotics/AI, software

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“As part of the BBC’s Intelligent Machines season, Google’s Eric Schmidt has penned an exclusive article on how he sees artificial intelligence developing, why it is experiencing such a renaissance and where it will go next.”

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Sep 28, 2015

Artificial Intelligence Must Answer to Its Creators

Posted by in categories: big data, computing, driverless cars, existential risks

Although it was made in 1968, to many people, the renegade HAL 9000 computer in the film 2001: A Space Odyssey still represents the potential danger of real-life artificial intelligence. However, according to Mathematician, Computer Visionary and Author Dr. John MacCormick, the scenario of computers run amok depicted in the film – and in just about every other genre of science fiction – will never happen.

“Right from the start of computing, people realized these things were not just going to be crunching numbers, but could solve other types of problems,” MacCormick said during a recent interview with TechEmergence. “They quickly discovered computers couldn’t do things as easily as they thought.”

While MacCormick is quick to acknowledge modern advances in artificial intelligence, he’s also very conscious of its ongoing limitations, specifically replicating human vision. “The sub-field where we try to emulate the human visual system turned out to be one of the toughest nuts to crack in the whole field of AI,” he said. “Object recognition systems today are phenomenally good compared to what they were 20 years ago, but they’re still far, far inferior to the capabilities of a human.”

To compensate for its limitations, MacCormick notes that other technologies have been developed that, while they’re considered by many to be artificially intelligent, don’t rely on AI. As an example, he pointed to Google’s self-driving car. “If you look at the Google self-driving car, the AI vision systems are there, but they don’t rely on them,” MacCormick said. “In terms of recognizing lane markings on the road or obstructions, they’re going to rely on other sensors that are more reliable, such as GPS, to get an exact location.”

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Sep 15, 2015

Latest issue of the Proceedings of the Very Large Data Base Endowment | VLDB

Posted by in category: big data

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Aug 28, 2015

Messaging As the Interface to Everything | Andreessen Horowitz

Posted by in category: big data

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