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Archive for the ‘big data’ category: Page 2

Sep 14, 2016

This Company’s Business is Opening Up Government Data — By Paul Bennett | Techonomy

Posted by in categories: big data, governance, government

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“What do Boston, Mass., and Barcelona, Spain have in common with consumer internet platforms like Yelp and Zillow? They’re taking advantage of a growing open-data trend.”

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Aug 24, 2016

Steve Fuller’s Review of Homo Deus: A Brief History of Tomorrow by Yuval Noah Harari

Posted by in categories: big data, bioengineering, biological, bionic, cyborgs, disruptive technology, energy, evolution, existential risks, futurism, homo sapiens, innovation, moore's law, neuroscience, philosophy, policy, posthumanism, robotics/AI, science, singularity, theory, transhumanism

My sociology of knowledge students read Yuval Harari’s bestselling first book, Sapiens, to think about the right frame of reference for understanding the overall trajectory of the human condition. Homo Deus follows the example of Sapiens, using contemporary events to launch into what nowadays is called ‘big history’ but has been also called ‘deep history’ and ‘long history’. Whatever you call it, the orientation sees the human condition as subject to multiple overlapping rhythms of change which generate the sorts of ‘events’ that are the stuff of history lessons. But Harari’s history is nothing like the version you half remember from school.

In school historical events were explained in terms more or less recognizable to the agents involved. In contrast, Harari reaches for accounts that scientifically update the idea of ‘perennial philosophy’. Aldous Huxley popularized this phrase in his quest to seek common patterns of thought in the great world religions which could be leveraged as a global ethic in the aftermath of the Second World War. Harari similarly leverages bits of genetics, ecology, neuroscience and cognitive science to advance a broadly evolutionary narrative. But unlike Darwin’s version, Harari’s points towards the incipient apotheosis of our species; hence, the book’s title.

This invariably means that events are treated as symptoms if not omens of the shape of things to come. Harari’s central thesis is that whereas in the past we cowered in the face of impersonal natural forces beyond our control, nowadays our biggest enemy is the one that faces us in the mirror, which may or may not be able within our control. Thus, the sort of deity into which we are evolving is one whose superhuman powers may well result in self-destruction. Harari’s attitude towards this prospect is one of slightly awestruck bemusement.

Here Harari equivocates where his predecessors dared to distinguish. Writing with the bracing clarity afforded by the Existentialist horizons of the Cold War, cybernetics founder Norbert Wiener declared that humanity’s survival depends on knowing whether what we don’t know is actually trying to hurt us. If so, then any apparent advance in knowledge will always be illusory. As for Harari, he does not seem to see humanity in some never-ending diabolical chess match against an implacable foe, as in The Seventh Seal. Instead he takes refuge in the so-called law of unintended consequences. So while the shape of our ignorance does indeed shift as our knowledge advances, it does so in ways that keep Harari at a comfortable distance from passing judgement on our long term prognosis.

Continue reading “Steve Fuller's Review of Homo Deus: A Brief History of Tomorrow by Yuval Noah Harari” »

Aug 5, 2016

This startup uses machine learning and satellite imagery to predict crop yields — By Alex Brokaw | The Verge

Posted by in categories: big data, business, machine learning, satellites, space

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“Instead, Descartes relies on 4 petabytes of satellite imaging data and a machine learning algorithm to figure out how healthy the corn crop is from space.”

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Jun 11, 2016

Why Cognitive Business Operations Will Change The Way We Work — By Vijay Pandiarajan | Forbes

Posted by in categories: big data, business, computing

Cloud shaped set of icons with symbols of services and activities connecting planet Earth, floating in the outer space, surrounded by a complex network of glowing nodes linked by bright lines, extending in the deep blue space around the globe. Global business and communication technology connecting everything through cloud computing and the Internet of Things. Dark blue background.

“What does it mean for a business to get things done? How does it channel the energy and activities of all its knowledge workers as they work?”

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Apr 25, 2016

“Smart Homes?” Not Until They’re Less Dependent On The Internet — By Jared Newman | Fast Company

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

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“Buying into a smart home ecosystem is sort of like selecting a holy grail in the Temple of the Sun. Choose poorly, and everything crumbles.”

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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.”

Continue reading “Connecting The Dots to Get the Big Picture with Artificial Intelligence” »

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