Reset (Rowan Simpson) — It was a bit chilling to go back over a whole years worth of tweets and discover how many of them were just junk. Visiting the water cooler is fine, but somebody who spends all day there has no right to talk of being full.
Google’s AI Brain — on the subject of Google’s AI ethics committee … Q: Will you eventually release the names? A: Potentially. That’s something also to be discussed. Q: Transparency is important in this too. A: Sure, sure. Such reassuring.
AVA is now Open Source (Laura Bell) — Assessment, Visualization and Analysis of human organisational information security risk. AVA maps the realities of your organisation, its structures and behaviors. This map of people and interconnected entities can then be tested using a unique suite of customisable, on-demand, and scheduled information security awareness tests.
Deep Learning for Torch (Facebook) — Facebook AI Research open sources faster deep learning modules for Torch, a scientific computing framework with wide support for machine learning algorithms.
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 …
Smartest Cities Rely on Citizen Cunning and Unglamorous Technology (The Guardian) — vendors like Microsoft, IBM, Siemens, Cisco and Hitachi construct the resident of the smart city as someone without agency; merely a passive consumer of municipal services – at best, perhaps, a generator of data that can later be aggregated, mined for relevant inference, and acted upon. Should he or she attempt to practise democracy in any form that spills on to the public way, the smart city has no way of accounting for this activity other than interpreting it as an untoward disruption to the orderly flow of circulation.
Introduction to the Modern Brain-Computer Interface Design (UCSD) — The lectures were first given by Christian Kothe (SCCN/UCSD) in 2012 at University of Osnabrueck within the Cognitive Science curriculum and have now been recorded in the form of an open online course. The course includes basics of EEG, BCI, signal processing, machine learning, and also contains tutorials on using BCILAB and the lab streaming layer software.
The Many Facades of DRM (PDF) — Modular software systems are designed to be broken into independent pieces. Each piece has a clear boundary and well-defined interface for ‘hooking’ into other pieces. Progress in most technologies accelerates once systems have achieved this state. But clear boundaries and well-defined interfaces also make a technology easier to attack, break, and reverse-engineer. Well-designed DRMs have very fuzzy boundaries and are designed to have very non-standard interfaces. The examples of the uglified DRM code are inspiring.
DPDK — a set of libraries and drivers for fast packet processing […] to: receive and send packets within the minimum number of CPU cycles (usually less than 80 cycles); develop fast packet capture algorithms (tcpdump-like); run third-party fast path stacks.
A Worm’s Mind in a Lego Body — the c. elegans worm’s 302 neurons has been sequenced, modelled in open source code, and now hooked up to a Lego robot. It is claimed that the robot behaved in ways that are similar to observed C. elegans. Stimulation of the nose stopped forward motion. Touching the anterior and posterior touch sensors made the robot move forward and back accordingly. Stimulating the food sensor made the robot move forward. There is video.
Apollo: Amazon’s Deployment Engine — Apollo will stripe the rolling update to simultaneously deploy to an equivalent number of hosts in each location. This keeps the fleet balanced and maximizes redundancy in the case of any unexpected events. When the fleet scales up to handle higher load, Apollo automatically installs the latest version of the software on the newly added hosts. Lust.
The Dark Market for Personal Data (NYTimes) — can buy lists of victims of sexual assault, of impulse buyers, of people with sexually transmitted disease, etc. The cost of a false-positive when those lists are used for marketing is less than the cost of false-positive when banks use the lists to decide whether you’re a credit risk. The lists fall between the cracks in privacy legislation; essentially, the compilation and use of lists of people are unregulated territory.
Collaborative Filtering at LinkedIn (PDF) — This paper presents LinkedIn’s horizontal collaborative filtering infrastructure, known as browsemaps. Great lessons learned, including context and presentation of browsemaps or any recommendation is paramount for a truly relevant user experience. That is, design and presentation represents the largest ROI, with data engineering being a second, and algorithms last. (via Greg Linden)
Engineer Sees Big Possibilities in Micro-robots, Including Programmable Bees (National Geographic) — He and fellow researchers devised novel techniques to fabricate, assemble, and manufacture the miniature machines, each with a housefly-size thorax, three-centimeter (1.2-inch) wingspan, and weight of just 80 milligrams (.0028 ounces). The latest prototype rises on a thread-thin tether, flaps its wings 120 times a second, hovers, and flies along preprogrammed paths. (via BoingBoing)
cuDNN — NVIDIA’s library of primitives for deep neural networks (on GPUS, natch). Not open source (registerware).
Analysing Trends in Silk Road 2.0 — If, indeed every sale can map to a transaction, some vendors are doing huge amounts of business through mail order drugs. While the number is small, if we sum up all the product reviews x product prices, we get a huge number of USD $20,668,330.05. REMEMBER! This is on Silk Road 2.0 with a very small subset of their entire inventory. A peek into a largely invisible economy.
Failing at Microservices — deconstructed a failed stab at microservices. Category three engineers also presented a significant problem to our implementation. In many cases, these engineers implemented services incorrectly; in one example, an engineer had literally wrapped and hosted one microservice within another because he didn’t understand how the services were supposed to communicate if they were in separate processes (or on separate machines). These engineers also had a tough time understanding how services should be tested, deployed, and monitored because they were so used to the traditional “throw the service over the fence”to an admin approach to deployment. This basically lead to huge amounts of churn and loss of productivity.