The Care and Feeding of Weird Machines Found in Executable Metadata (YouTube) — talk from 29th Chaos Communication Congress, on using tricking the ELF linker/loader into arbitrary computation from the metadata supplied. Yes, there’s a brainfuck compiler that turns code into metadata which is then, through a supernatural mix of pixies, steam engines, and binary, executed. This will make your brain leak. Weird machines are everywhere.
European Libraries May Digitise Books Without Permission — “The right of libraries to communicate, by dedicated terminals, the works they hold in their collections would risk being rendered largely meaningless, or indeed ineffective, if they did not have an ancillary right to digitize the works in question,” the court said. Even if the rights holder offers a library the possibility of licensing his works on appropriate terms, the library can use the exception to publish works on electronic terminals, the court ruled. “Otherwise, the library could not realize its core mission or promote the public interest in promoting research and private study,” it said.
Laws of Crappy Dashboards — (caution, NSFW language … “crappy” is my paraphrase) so true. Not talking to users will result in a [crappy] dashboard. You don’t know if the dashboard is going to be useful. But you don’t talk to the users to figure it out. Or you just show it to them for a minute (with someone else’s data), never giving them a chance to figure out what the hell they could do with it if you gave it to them.
Liquibase — source control for your database. Apache 2.0 licensed.
A Few Useful Things to Know About Machine Learning (PDF) — This article summarizes twelve key lessons that machine learning researchers and practitioners have learned. These include pitfalls to avoid, important issues to focus on, and answers to common questions. My fave: First-timers are often surprised by how little time in a machine learning project is spent actually doing machine learning. But it makes sense if you consider how time-consuming it is to gather data, integrate it, clean it and pre-process it, and how much trial and error can go into feature design.
Machine Learning for Plant Properties — startup building database of plant genomics, properties, research, etc. for mining. The more familiar you are with your data and its meaning, the better your machine learning will be at suggesting fruitful lines of query … and the more valuable your startup will be.
Dissecting Message Queues — throughput, latency, and qualitative comparison of different message queues. MQs are to modern distributed architectures what function calls were to historic unibox architectures.
1915 Data Visualization Rules — a reminder that data visualization is not new, but research into effectiveness of alternative presentation styles is.
Material Design in the Google I/O App (Medium) — steps through design thinking as they put Google’s new design metaphor in place. I’ve been chewing on material design. It brings an internal consistency and logic to the Android world that Apple’s iOS and OS X visual worlds have been losing over the years. How long until web users expect this consistency too?
Stewart and Slack (Wired) — profile of Foo Stewart Butterfield and his shiny Slack startup.
Neglected Machine Learning Ideas — Perhaps my list is a “send me review articles and book suggestions” cry for help, but perhaps it is useful to others as an overview of neat things.
First Crowdfunded Book on Booker Shortlist — Booker excludes self-published works, but “The Wake” was through Unbound, a Threadless-style “if we hit this limit, the book is printed and you have bought a copy” site.
Watson Can Debate Its Opponents (io9) — Speaking in nearly perfect English, Watson/The Debater replied: “Scanned approximately 4 million Wikipedia articles, returning ten most relevant articles. Scanned all 3,000 sentences in top ten articles. Detected sentences which contain candidate claims. Identified borders of candidate claims. Assessed pro and con polarity of candidate claims. Constructed demo speech with top claim predictions. Ready to deliver.”
ipfs — a global, versioned, peer-to-peer file system. It combines good ideas from Git, BitTorrent, Kademlia, and SFS. You can think of it like a single BitTorrent swarm, exchanging Git objects, making up the web. IPFS provides an interface much simpler than HTTP, but has permanence built in.. (via Sourcegraph)