FEATURED STORY

Four short links: 21 October 2014

Data Delusions, OS Robotics, Insecure Crypto, and Free Icons

  1. The Delusions of Big Data (IEEE) — When you have large amounts of data, your appetite for hypotheses tends to get even larger. And if it’s growing faster than the statistical strength of the data, then many of your inferences are likely to be false. They are likely to be white noise.
  2. ROSCON 2014 — slides and videos of talks from Chicago open source robotics conference.
  3. Making Sure Crypto Stays Insecure (PDF) — Daniel J. Bernstein talk: This talk is actually a thought experiment: how could an attacker manipulate the ecosystem for insecurity?
  4. Material Design Icons — Google’s CC-licensed (attribution, sharealike) collection of sweet, straightforward icons.
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Four short links: 20 October 2014

Four short links: 20 October 2014

Leaky Search, Conditional Javascript, Software Proofs, and Fake Identity

  1. Fix Mac OS Xeach time you start typing in Spotlight (to open an application or search for a file on your computer), your local search terms and location are sent to Apple and third parties (including Microsoft) under default settings on Yosemite (10.10). See also Net Monitor, an open source toolkit for finding phone-home behaviour.
  2. A/B Testing at Netflix (ACM) — Using a combination of static analysis to build a dependency tree, which is then consumed at request time to resolve conditional dependencies, we’re able to build customized payloads for the millions of unique experiences across Netflix.com.
  3. Leslie Lamport Interview SummaryOne idea about formal specifications that Lamport tries to dispel is that they require mathematical capabilities that are not available to programmers: “The mathematics that you need in order to write specifications is a lot simpler than any programming language [...] Anyone who can write C code, should have no trouble understanding simple math, because C code is a hell of a lot more complicated than” first-order logic, sets, and functions. When I was at uni, profs worked on distributed data, distributed computation, and formal correctness. We have the first two, but so much flawed software that I can only dream of the third arriving.
  4. Fake Identity — generate fake identity data when testing systems.
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Use data or be data

Trina Chiasson argues that data has arrived at the same threshold as coding: code or be coded; learn to use data or be data.

Trina_Chiasson

Trina Chiasson

Arguments from all sides have surrounded the question of whether or not everyone should learn to code. Trina Chiasson, co-founder and CEO of Infoactive, says learning to code changed her life for the better. “These days I don’t spend a lot of time writing code,” she says, “but it’s incredibly helpful for me to be able to communicate with our engineers and communicate with other people in the industry.”

Though helpful for her personally, she admits that it takes quite a lot of time and commitment to learn to code to any level of proficiency, and that it might not be the best use of time for everyone. What should people commit time to learn? How to use data. Read more…

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Signals from Strata + Hadoop World New York 2014

From unique data applications to factories of the future, here are key insights from Strata + Hadoop World New York 2014.

Experts from across the data world came together in New York City for Strata + Hadoop World New York 2014. Below we’ve assembled notable keynotes, interviews, and insights from the event.

Unusual data applications and the correct way to say “Hadoop”

Hadoop creator and Cloudera chief architect Doug Cutting discusses surprising data applications — from dating sites to premature babies — and he reveals the proper (but in no way required) pronunciation of “Hadoop.”

Read more…

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What happens when fashion meets data: The O’Reilly Radar Podcast

Liza Kindred on the evolving role of data in fashion and the growing relationship between tech and fashion companies.

Editor’s note: you can subscribe to the O’Reilly Radar Podcast through iTunes, SoundCloud, or directly through our podcast’s RSS feed.

In this podcast episode, I talk with Liza Kindred, founder of Third Wave Fashion and author of the new free report “Fashioning Data: How fashion industry leaders innovate with data and what you can learn from what they know.” Kindred addresses the evolving role data and analytics are playing in the fashion industry, and the emerging connections between technology and fashion companies. “One of the things that fashion is doing better than maybe any other industry,” Kindred says, “is facilitating conversations with users.”

Gathering and analyzing user data creates opportunities for the fashion and tech industries alike. One example of this is the trend toward customization. Read more…

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The human side of Hadoop

Doug Cutting on applications of Hadoop, where "Hadoop" comes from, and the new partnership between Cloudera and O'Reilly.

Roger Magoulas, director of market research at O’Reilly and Strata co-chair, recently sat down with Doug Cutting, chief architect at Cloudera, to talk about the new partnership between Cloudera and O’Reilly, and the state of the Hadoop landscape.

Cutting shares interesting applications of Hadoop, several of which had touching human elements. For instance, he tells a story about visiting Children’s Healthcare of Atlanta and discovering the staff using Hadoop to reduce stress in babies. Read more…

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