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Archive for the ‘big data’ category: Page 3

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

Aug 21, 2015

Exotic Pentaquark Particle Discovery & CERN’s Massive Data Center

Posted by in categories: big data, engineering, particle physics, physics, science


July, 2015; as you know.. was the all systems go for the CERNs Large Hadron Collider (LHC). On a Saturday evening, proton collisions resumed at the LHC and the experiments began collecting data once again. With the observation of the Higgs already in our back pocket — It was time to turn up the dial and push the LHC into double digit (TeV) energy levels. From a personal standpoint, I didn’t blink an eye hearing that large amounts of Data was being collected at every turn. BUT, I was quite surprised to learn at the ‘Amount’ being collected and processed each day — About One Petabyte.

Approximately 600 million times per second, particles collide within the (LHC). The digitized summary is recorded as a “collision event”. Physicists must then sift through the 30 petabytes or so of data produced annually to determine if the collisions have thrown up any interesting physics. Needless to say — The Hunt is On!

The Data Center processes about one Petabyte of data every day — the equivalent of around 210,000 DVDs. The center hosts 11,000 servers with 100,000 processor cores. Some 6000 changes in the database are performed every second.

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Aug 18, 2015

Blockchain for IoT? Yes!

Posted by in categories: automation, big data, complex systems, computing, disruptive technology, engineering, hardware, science, supercomputing

Quoted: “Sometimes decentralization makes sense.

Filament is a startup that is taking two of the most overhyped ideas in the tech community—the block chain and the Internet of things—and applying them to the most boring problems the world has ever seen. Gathering data from farms, mines, oil platforms and other remote or highly secure places.

The combination could prove to be a powerful one because monitoring remote assets like oil wells or mining equipment is expensive whether you are using people driving around to manually check gear or trying to use sensitive electronic equipment and a pricey a satellite internet connection.

Instead Filament has built a rugged sensor package that it calls a Tap, and technology network that is the real secret sauce of the operation that allows its sensors to conduct business even when they aren’t actually connected to the internet. The company has attracted an array of investors who have put $5 million into the company, a graduate of the Techstars program. Bullpen Capital led the round with Verizon Ventures, Crosslink Capital, Samsung Ventures, Digital Currency Group, Haystack, Working Lab Capital, Techstars and others participating.

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Aug 14, 2015

Google’s New Alphabetical Order — By Vauhini Vara | The New Yorker

Posted by in categories: big data, business, innovation, internet

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“In one sense, Page and Brin are just formalizing an arrangement that has evidently existed at Google for the past several years—the two of them at the helm of a company largely occupied with seeking out new and strange areas of innovation. The bet, it seems, is that this arrangement will improve the chances that Page and Brin’s unconventional investments will pan out—and that, if they don’t, the rest of the company will be better insulated from its founders’ mistakes. Until then, Sundar Pichai can focus on the boring, plodding business of actually making money.”

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