2015 Archive
28741.
Do You Know What Your Users are Doing? A Guide to Understanding Search Behavior
(blog.constructor.io)
28742.
The Tech Model Railroad Club – Hackers at 30
(medium.com)
28743.
Animals Spy a New Enemy: Drones
(nytimes.com)
28744.
Why IoT Security Is Critical
(techcrunch.com)
28745.
28746.
An Archaeology-Inspired Database
(aosabook.org)
28747.
The Latest Intellectuals
(chronicle.com)
28748.
NFI can decrypt encrypted BlackBerry emails
(translate.googleusercontent.com)
28749.
28750.
British Startup TransferWise Raises $58M
(dealbook.nytimes.com)
28751.
Transactional memory support in the IBM POWER8 processor
(ieeexplore.ieee.org)
28752.
How to Do MVPs Right – Minimum Viable Products Made Easy
(hatchery.io)
28753.
The New French Hacker-Artist Underground (2012)
(wired.com)
28754.
Why Is America Dotted with Giant, Concrete Arrows?
(citylab.com)
28755.
MacPaint and QuickDraw Source Code
(computerhistory.org)
28756.
BorderScore for International Jobseekers
(score.teleborder.com)
28757.
An introduction to functional programming
(codewords.recurse.com)
28758.
Artificial Intelligence as Alien Intelligence
(boundary2.org)
28759.
Nobuo Okano, Book Repairman
(theparisreview.org)
28760.
Vatican: “Open source is 'only reliable way' to preserve human history”
(theinquirer.net)
28761.
Erik Meijer and Gilad Bracha: Dart, Monads, Continuations (2012)
(channel9.msdn.com)
28762.
Two commutes with Rust
(xania.org)
28763.
Letter Scam: In eighteenth-century France, a stranger asks a favor
(laphamsquarterly.org)
28764.
HiDb: A Haskell In-Memory Relational Database (2014) [pdf]
(scs.stanford.edu)
28765.
Paris Geothermal Boom Brings Deep Drilling to Crowded Suburbs
(bloomberg.com)
28766.
RLSD, the Retro Linux-libre Software Distribution
(rlsd2.dimakrasner.com)
28767.
Visit CERN Sites New to Google Street View
(home.web.cern.ch)
28768.
Show HN: JavaScript typed arrays data structures for memory intensive tasks
(chethiya.github.io)
28769.
Research: Theory, models and biology
(elifesciences.org)
28770.
Hack day report: Using Amazon Machine Learning to predict trolling
(theguardian.com)