Anthropic Capitalism And The New Gimmick Economy — market capitalism struggles with “public goods” (those which are inexhaustible and non-excludable, like infinitely copyable bits that any number of people can have copies of at once), yet much of the world is being recast as an activity where software manipulates information, thus becoming a public good. Capitalism and Communism, which briefly resembled victor and vanquished, increasingly look more like Thelma and Louise; a tragic couple sent over the edge by forces beyond their control. What comes next is anyone’s guess and the world hangs in the balance.
MacroBase — Analytic monitoring for the Internet of Things. The code behind a research paper, written up in the morning paper where Adrian Colyer says, there is another story that also unfolds in the paper – one of careful system design based on analysis of properties of the problem space, of thinking deeply and taking the time to understand the prior art (aka “the literature”), and then building on those discoveries to advance and adapt them to the new situation. “That’s what research is all about!” you may say, but it’s also what we’d (I’d?) love to see more of in practitioner settings, too. The result of all this hard work is a system that comprises just 7,000 lines of code, and I’m sure, many, many hours of thinking!
Survey of Commenters and Comment Readers — Americans who leave news comments, who read news comments, and who do neither are demographically distinct. News commenters are more male, have lower levels of education, and have lower incomes compared to those who read news comments. (via Marginal Revolution)
Moneyball for Book Publishers: A Detailed Look at How We Read (NYT) — On average, fewer than half of the books tested were finished by a majority of readers. Most readers typically give up on a book in the early chapters. Women tend to quit after 50 to 100 pages, men after 30 to 50. Only 5% of the books Jellybooks tested were completed by more than 75% of readers. Sixty percent of books fell into a range where 25% to 50% of test readers finished them. Business books have surprisingly low completion rates. Not surprisingly low to anyone who has ever read a business book. They’re always a 20-page idea stretched to 150 pages because that’s how wide a book’s spine has to be to visible on the airport bookshelf. Fat paper stock and 14-point text with wide margins and 1.5 line spacing help, too. Don’t forget to leave pages after each chapter for the reader’s notes. And summary checklists. And … sorry, I need to take a moment.
An Adaptive Learning Interface that Adjusts Task Difficulty based on Brain State (PDF) — using blood flow to measure cognitive load, this tool releases new lessons to you when you’re ready for them. The system measures blood flow using functional near-infrared spectroscopy (fNIRS). Increased activation in an area of the brain results in increased levels of oxyhemoglobin. These changes can be measured by emitting frequencies of near-infrared light around 3 cm deep into the brain tissue and measuring the light attenuation caused by levels of oxyhemoglobin. I think we all want a widget on our computer that says “your brain is full, go offline to recover,” if only to validate naptime.
Deploying Software — Your deploys should be as boring, straightforward, and stress-free as possible. cf Maciej Ceglowski’s “if you find it interesting, it doesn’t belong in production.”
Replicating SQLite Using Raft — rqlite is written in Go and uses Raft to achieve consensus across all the instances of the SQLite databases. rqlite ensures that every change made to the database is made to a quorum of SQLite files, or none at all.
Brain Modem — a tiny sensor that travels through blood vessels, lodges in the brain and records neural activity. The “stentrode” (stent + electrode) is the size of a paperclip, and Melbourne researchers (funded by DARPA) have made the first successful animal trials.
Robots in American Law — This article closely examines a half century of case law involving robots. […] The first set highlights the role of robots as the objects of American law. Among other issues, courts have had to decide whether robots represent something “animate” for purposes of import tariffs, whether robots can “perform” as that term is understood in the context of a state tax on performance halls, and whether a salvage team “possesses” a shipwreck it visits with an unmanned submarine. (via BoingBoing)
Princeton Bitcoin Book (PDF) — The Coursera course accompanying this book had 30,000 students in its first version, and it was a success based on engagement and end-of-course feedback. Large introduction to Bitcoin from Princeton. (via Cory Doctorow)
A Quartet of Complementary Brain Books (Vaughan Bell) — The books have been chosen to complement each other and the idea is that if you read all four, you should have a solid grounding in modern cognitive neuroscience and beyond.
NIST Report on Post-Quantum Cryptography (PDF) — in case you missed it, “post-quantum crypto” is “existing crypto relies on how hard it is to find the prime factors of large numbers, of which we suspect quantum computers may make a mockery. Wut to do?” The goal of post-quantum cryptography (also called quantum-resistant cryptography) is to develop cryptographic systems that are secure against both quantum and classical computers, and can interoperate with existing communications protocols and networks.
Amazon Lumberyard — a free, cross-platform, 3D game engine for you to create the highest-quality games, connect your games to the vast compute and storage of the AWS Cloud, and engage fans on Twitch. From Amazon.
Social Intelligence in Mario Bros (YouTube) — collaborative agents built by cognitive AI researchers … they have drives, communicate, learn from each other, and solve problems. Oh, and the agents are Mario, Luigi, Yoshi, and Toad within a Super Mario Brothers clone. No code or papers about it on the research group’s website yet, just a YouTube video and a press release on the university’s website, so appropriately adjust your priors for imminent world destruction at the hands of a rampaging super-AI. (via gizmag)
Simple Anomaly Detection for Weekly Patterns — Rule-based heuristics do not scale and do not adapt easily, especially if we have thousands of alarms to set up. Some statistical approach is needed that is generic enough to handle many different metric behaviours.
How to Design a Robotics Experiment (Robohub) — although there are many good experimental scientists in the robotic community, there has not been uniformly good experimental work and reporting within the community as a whole. This has advice such as “the five components of a well-designed experiment.”
Elemental Machines — Boston startup fitting experiments & experimenters with sensors, deep learning to identify problems (vibration, humidity, etc.) that could trigger experimental failure. [C]rucial experiments are often delayed by things that seem trivial in retrospect. “I talked to my friends who worked in labs,” Iyengar says. “Everyone had a story to tell.” One scientist’s polymer was unstable because of ultraviolet light coming through a nearby window, he says; that took six months to debug. Another friend who worked at a pharmaceutical company was testing drug candidates in mice. The results were one failure after another, for months, until someone figured out that the lab next door was being renovated, and after-hours construction was keeping the mice awake and stressing them out. (that quote from Xconomy)
Usborne Computer and Coding Books — not only do they have sweet Scratch books for kids, they also have their nostalgia-dripping 1980s microcomputer books online. I still have a pile of my well-loved originals.
Powerful People are Terrible at Making Decisions Together — Researchers from the Haas School of Business at the University of California, Berkeley, undertook an experiment with a group of health care executives on a leadership retreat. They broke them into groups, presented them with a list of fictional job candidates, and asked them to recommend one to their CEO. The discussions were recorded and evaluated by independent reviewers. The higher the concentration of high-ranking executives, the more a group struggled to complete the task. They competed for status, were less focused on the assignment, and tended to share less information with each other.
MyBinder — turn a GitHub repo into a collection of interactive notebooks powered by Jupyter and Kubernetes.
Old-School PC Fonts — definitive collection of ripped-from-the-BIOS fonts from the various types of PCs. Your eyes will ache with nostalgia. (Or, if you’re a young gun, wondering how anybody wrote code with fonts like that) (my terminal font is VT220 because it makes me happy and productive)
Cognitive Load: Brain Gems — We distill the latest behavioural economics & consumer psychology research down into helpful little brain gems.
Chimera (Paper a Day) — the authors summarise six main lessons learned while building Chimera: (1) Things break down at large scale; (2) Both learning and hand-crafted rules are critical; (3) Crowdsourcing is critical, but must be closely monitored; (4) Crowdsourcing must be coupled with in-house analysts and developers; (5) Outsourcing does not work at a very large scale; (6) Hybrid human-machine systems are here to stay.
Microsoft Embedding Research — To break down the walls between its research group and the rest of the company, Microsoft reassigned about half of its more than 1,000 research staff in September 2014 to a new group called MSR NExT. Its focus is on projects with greater impact to the company rather than pure research. Meanwhile, the other half of Microsoft Research is getting pushed to find more significant ways it can contribute to the company’s products. The challenge is how to avoid short-term thinking from your research team. For instance, Facebook assigns some staff to focus on long-term research, and Google’s DeepMind group in London conducts pure AI research without immediate commercial considerations.
Google’s Go-Playing AI — The key to AlphaGo is reducing the enormous search space to something more manageable. To do this, it combines a state-of-the-art tree search with two deep neural networks, each of which contains many layers with millions of neuron-like connections. One neural network, the “policy network,” predicts the next move, and is used to narrow the search to consider only the moves most likely to lead to a win. The other neural network, the “value network,” is then used to reduce the depth of the search tree — estimating the winner in each position in place of searching all the way to the end of the game.