You Can’t Destroy a Village to Save It (EFF) — EFF have a clever compromise for W3C’s proposal for DRM on the Web. [T]he W3C could have its cake and eat it, too. It could adopt a rule that requires members who help make DRM standards to promise not to sue people who report bugs in tools that conform to those standards, nor could they sue people just for making a standards-based tool that connected to theirs. They could make DRM, but only if they made sure that they took steps to stop that DRM from being used to attack the open Web. I hope the W3C take it.
Copyright Law Shouldn’t Keep Me From Fixing a Tractor (Slate) — When a farmer friend of mine wanted to know if there was a way to tweak the copyrighted software of his broken tractor, I knew it was going to be rough. The only way to get around the DMCA’s restriction on software tinkering is to ask the Copyright Office for an exemption at the Section 1201 Rulemaking, an arduous proceeding that takes place just once every three years.
License to Drive — I have difficulty viewing No Drive Day as imminent. We’re maybe 95% there, but that last 5% will be a lengthy slog.
Object Lessons — Bogost and Schaberg edit a series about the hidden lives of ordinary things, from advocates to attendants, heresies to shares. For anyone who cares about products.
A Data Programming CS1 Course (PDF) — We have found that students can be motivated to learn programming and computer science concepts in order to analyze DNA, predict the outcome of elections, detect fraudulent data, suggest friends in a social network, determine the authorship of documents, and more. The approach is more than just a collection of “nifty assignments”; rather, it affects the choice of topics and pedagogy.
Cars and the Future (Ben Thompson) — This generational pattern of adoption will, in the history books, look sudden, even as it seems to unfold ever so slowly for those of us in the here and now — especially those of us working in technology. The pace of change in the technology industry — which is young, hugely driven by Moore’s Law, and which has largely catered to change-embracing geeks — is likely the true aberration. After all, the biggest mistake consistently made by technologists is forgetting that for most people technology is a means to an end, and for all the benefits we can list when it comes to over-the-top video or a network of on-demand self-driving vehicles, change and the abandonment of long-held ideals like the open road and a bit of TV after supper is an end most would prefer to avoid.
CES 2016 Observations for Product People — The big challenge is no surprise. Software development is unable to keep up with the hardware. What is going to separate one device from another or one company from another will be the software execution, not just the choice of chipset or specs for a peripheral/sensor. It would be hard to overstate the clear opportunity to build winning products using stronger software relative to competitors. Said another way, spending too many cycles on hardware pits you against the supply chain for most products. The whole piece is solid.
Folium — makes it easy to visualize data that’s been manipulated in Python on an interactive Leaflet map. It enables both the binding of data to a map for choropleth visualizations as well as passing Vincent/Vega visualizations as markers on the map.
SEE — F-Secure’s open source Sandboxed Execution Environment (SEE) is a framework for building test automation in secured Environments.
The Problem with Self-Driving Cars: Who Controls the Code? (Cory Doctorow) — Here’s a different way of thinking about this problem: if you wanted to design a car that intentionally murdered its driver under certain circumstances, how would you make sure that the driver never altered its programming so that they could be assured that their property would never intentionally murder them?
Real-world Probabilistic Algorithms (Tyler McMullen) — This article addresses two types of probabilistic algorithms: those that explicitly introduce randomness through a rand() call, and those that convert input data into a uniform distribution to achieve a similar effect.
Class of 2016 — those whose works will, on 1st January 2016, be entering the public domain in many countries around the world. Le Corbusier, T.S. Eliot, Malcolm X, Bela Bartok, Winston Churchill, and W. Somerset Maugham among others. (Which person in which country depends on copyright term. Not for you, America. Nor us after TPP)
Distributed Reactive Programming (A Paper a Day) — this week’s focus on reactive programming has been eye-opening for me. I find the implementation details less interesting than the simple notion that we can define different consistency models for reactive programs and reason about them.
Attacking HTTP/2 Implementations — Our talk focused on threats, attack vectors, and vulnerabilities found during the course of our research. Two Firefox, two Apache Traffic Server (ATS), and four Node-http2 vulnerabilities will be discussed alongside the release of the first public HTTP/2 fuzzer. We showed how these bugs were found, their root cause, why they occur, and how to trigger them.
The Autonomous Winter is Coming — The future of any given manufacturer will be determined by how successfully they manage their brands in a market split between Mobility customers and Driving customers.
Andrew Ng (Wired) — I think self-driving cars are a little further out than most people think. There’s a debate about which one of two universes we’re in. In the first universe it’s an incremental path to self-driving cars, meaning you have cruise control, adaptive cruise control, then self-driving cars only on the highways, and you keep adding stuff until 20 years from now you have a self-driving car. In universe two you have one organization, maybe Carnegie Mellon or Google, that invents a self-driving car and bam! You have self-driving cars. It wasn’t available Tuesday but it’s on sale on Wednesday. I’m in universe one. I think there’s a lot of confusion about how easy it is to do self-driving cars. There’s a big difference between being able to drive a thousand miles, versus being able to drive anywhere. And it turns out that machine-learning technology is good at pushing performance from 90 to 99 percent accuracy. But it’s challenging to get to four nines (99.99 percent). I’ll give you this: we’re firmly on our way to being safer than a drunk driver.
Google Cloud BigTable — Google’s BigTable, with Apache HBase API, single-digit millisecond latency, and “fully managed”. G are hell-bent on catching up with Amazon and Microsoft at this cloud serving thing.
Call Me Maybe: Aerospike — We’re setting a timeout of 500ms here, and operations still time out every time a partition between nodes occurs. In these tests we aren’t interfering with client-server traffic at all. Aerospike may claim “100% uptime”, but this is only meaningful with respect to particular latency bounds. Given Aerospike claims millisecond-scale latencies, you may want to reconsider whether you consider this “uptime”.
Grasping with Robots: Which Object is in Reach? (Robohub) — This post is part of our ongoing efforts to make the latest papers in robotics accessible to a general audience. … a new approach to build a comprehensive representation of the capabilities of a robot related to reaching and grasping. Very short, very readable, as promised.