Go By Example — a chance to replicate the experience of learning Perl or PHP, whereby you know nothing but copy and adapt other people’s code until it works and you’ve empirically acquired an intuition for what will trigger the compiler’s deathray and eventually someone points you to the docs that were opaque and suddenly a lightbulb goes off in your head and you shout “omigod I finally get it!” and the Real Engineer beside you rolls their eyes and gets back to genericising their containers for consensus or whatever it is that Real Engineers do now.
Chinese Shopping for Robotic Ventures — Amazon has drones, Facebook has VR, Google and China are fighting it out for Robots. Meanwhile, Apple is curled up in a mountain filled with gold, their paws twitching and stroking their watches as they dream of battles to come.
Robot Arm Brings Humanity Back to the Stone Age (IEEE) — Using robots to build a massive database of scrape/wear patterns for different stone-age tools. Currently, Iovita is experiencing some opposition from within his own profession. Some believe that manual experiments are closer to the past reality; others find that use-wear analysis in general does not advance archaeological theory. Iovita thinks this is mainly due to the fact that most archaeologists have a humanities background and are not familiar with the world of engineers. OH SNAP.
The Great Reversal in the Demand for Skill and Cognitive Tasks (PDF) — The only difference with more conventional models of skill-biased technological change is our modelling of the fruits of cognitive employment as creating a stock instead of a pure flow. This slight change causes technological change to generate a boom and bust cycle, as is common in most investment models. We also incorporated into this model a standard selection process whereby individuals sort into occupations based on their comparative advantage. The selection process is the key mechanism that explains why a reduction in the demand for cognitive tasks, which are predominantly filled by higher educated workers, can result in a loss of employment concentrated among lower educated workers. While we do not claim that our model is the only structure that can explain the observations we present, we believe it gives a very simple and intuitive explanation to the changes pre- and post-2000.
provinces — state and province lists for (some) countries.
Cultural Analytics — the use of computational and visualization methods for the analysis of massive cultural data sets and flows. Interesting visualisations as well as automated understandings.
The Code is Just the Symptom — The engineering culture was a three-layer cake of dysfunction, where everyone down the chain had to execute what they knew to be an impossible task, at impossible speeds, perfectly. It was like the games of Simon Says and Telephone combined to bad effect. Most engineers will have flashbacks at these descriptions. Trigger warning: candid descriptions of real immature software organisations.
Designing the Human-Robot Relationship (O’Reilly) — We can use those same principles [Jakob Nielsen’s usability heuristics] and look for implications of robots serving our higher ordered needs, as we move from serving needs related to convenience or performance to actually supporting our decision making to emerging technologies, moving from being able to do anything or be magic in terms of the user interface to being more human in the user interface.
Why Are Geospatial Databases So Hard To Build? — Algorithms in computer science, with rare exception, leverage properties unique to one-dimensional scalar data models. In other words, data types you can abstractly represent as an integer. Even when scalar data types are multidimensional, they can often be mapped to one dimension. This works well, as the majority of [what] data people care about can be represented with scalar types. If your data model is inherently non-scalar, you enter an algorithm wasteland in the computer science literature.
Future of the AI-Powered Application (Matt Turck) — we’re about to witness the emergence of a number of deeply focused AI-powered applications that will achieve commercial success by solving in a definitive manner very specific issues. (via Matt Webb)
gibber — a creative coding environment for audiovisual performance and composition. It contains features for audio synthesis and musical sequencing, 2d drawing, 3d scene construction and manipulation, and live-coding shaders. If you’re looking for more ways to interest teens in code …
Killer App for Wearables (Fortune) — While many corporations are still waiting to see what the “killer app” for wearables is, Disney invented one. The company launched the RFID-enabled MagicBands just over a year ago. Since then, they’ve given out more than 9 million of them. Disney says 75% of MagicBand users engage with the “experience”—a website called MyMagic+—before their visit to the park. Online, they can connect their wristband to a credit card, book fast passes (which let you reserve up to three rides without having to wait in line), and even order food ahead of time. […] Already, Disney says, MagicBands have led to increased spending at the park.
globalnamedata — We have collected birth record data from the United States and the United Kingdom across a number of years for all births in the two countries and are releasing the collected and cleaned up data here. We have also generated a simple gender classifier based on incidence of gender by name.
geogig — an open source tool that draws inspiration from Git, but adapts its core concepts to handle distributed versioning of geospatial data.
Wolfram Language — a broad attempt to integrate types, operations, and databases along with deployment, parallelism, and real-time I/O. The demo video is impressive, not just in execution but in ambition. Healthy skepticism still necessary.
Maury, Innovation, and Change (Cory Ondrejka) — amazing historical story of open data, analysis, visualisation, and change. In the mid-1800’s, over the course of 15 years, a disabled Lieutenant changed the US Navy and the world. He did it by finding space to maneuver (as a trouble maker exiled to the Navy Depot), demonstrating value with his early publications, and creating a massive network effect by establishing the Naval Observatory as the clearing house for Navigational data. 150 years before Web 2.0, he built a valuable service around common APIs and aggregated data by distributing it freely to the people who needed it.
Commuter Shuttle and 21-Hayes EB Bus Stop Observations (Vimeo) — timelapse of 6:15AM to 9:15AM at an SF bus stop Worth watching if you’re outside SF and wondering what they’re talking about when the locals rage against SF becoming a bedroom community for Valley workers.
A Day of Speaking Truth to Power (Quinn Norton) — It was a room that had written off privacy as an archaic structure. I tried to push back, not only by pointing out this was the opening days of networked life, and so custom hadn’t caught up yet, but also by recommending danah boyd’s new book It’s Complicated repeatedly. To claim “people trade privacy for free email therefore privacy is dead” is like 1800s sweatshop owners claiming “people trade long hours in unpleasant conditions for miserable pay therefore human rights are dead”. Report of privacy’s death are greatly exaggerated.
Making Remote Work — The reality of a remote workplace is that the connections are largely artificial constructs. People can be very, very isolated. A person’s default behavior when they go into a funk is to avoid seeking out interactions, which is effectively the same as actively withdrawing in a remote work environment. It takes a tremendous effort to get on video chats, use our text based communication tools, or even call someone during a dark time. Very good to see this addressed in a post about remote work.
Using CMOS Sensors in a Cellphone for Gamma Detection and Classification (Arxiv) — another sense in your pocket. The CMOS camera found in many cellphones is sensitive to ionized electrons. Gamma rays penetrate into the phone and produce ionized electrons that are then detected by the camera. Thermal noise and other noise needs to be removed on the phone, which requires an algorithm that has relatively low memory and computational requirements. The continuous high-delta algorithm described fits those requirements. (via Medium)