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.
Crossword-Solving Neural Networks — Hill describes recent progress in learning-based AI systems in terms of behaviourism and cognitivism: two movements in psychology that effect how one views learning and education. Behaviourism, as the name implies, looks at behaviour without looking at what the brain and neurons are doing, while cognitivism looks at the mental processes that underlie behaviour. Deep learning systems like the one built by Hill and his colleagues reflect a cognitivist approach, but for a system to have something approaching human intelligence, it would have to have a little of both. “Our system can’t go too far beyond the dictionary data on which it was trained, but the ways in which it can are interesting, and make it a surprisingly robust question and answer system – and quite good at solving crossword puzzles,” said Hill. While it was not built with the purpose of solving crossword puzzles, the researchers found that it actually performed better than commercially-available products that are specifically engineered for the task.
Mathematical Foundations for Social Computing (PDF) — collection of pointers to existing research in social computing and some open challenges for work to be done. Consider situations where a highly structured decision must be made. Some examples are making budgets, assigning water resources, and setting tax rates. […] One promising candidate is “Knapsack Voting.” […] This captures most budgeting processes — the set of chosen budget items must fit under a spending limit, while maximizing societal value. Goel et al. prove that asking users to compare projects in terms of “value for money” or asking them to choose an entire budget results in provably better properties than using the more traditional approaches of approval or rank-choice voting.
Intelligence-Augmented Rat Cyborgs in Maze Solving (PLoS) — We compare the performance of maze solving by computer, by individual rats, and by computer-aided rats (i.e. rat cyborgs). They were asked to find their way from a constant entrance to a constant exit in 14 diverse mazes. Performance of maze solving was measured by steps, coverage rates, and time spent. The experimental results with six rats and their intelligence-augmented rat cyborgs show that rat cyborgs have the best performance in escaping from mazes. These results provide a proof-of-principle demonstration for cyborg intelligence. In addition, our novel cyborg intelligent system (rat cyborg) has great potential in various applications, such as search and rescue in complex terrains.
Nissan’s Self-Parking Office Chairs — clever hack, but thought-provoking: will we have an auto-navigating office chair before the self-driving auto revolution arrives? Because, you know, my day isn’t sedentary enough as it is …
The Man Behind the Robot Revolution — profile of the man behind Willow Garage. Why he and it are interesting: Although the now defunct research-lab-startup hybrid might not ring any bells to you now, it was one of the most influential forces in modern robotics. The freewheeling robot collective jump-started the current race to apply robotics components like computer vision, manipulation, and autonomy into applications for everything from drones and autonomous cars to warehouse operations at places like Google, Amazon, and car companies like BMW. Google alone acquired three of the robot companies spawned by Willow.
NSA’s Lousy Evaluation of Drone Strike Algorithm Effectiveness (Ars Technica) — vastly overstating the quality of the predictions. The 0.008% false positive rate would be remarkably low for traditional business applications. This kind of rate is acceptable where the consequences are displaying an ad to the wrong person, or charging someone a premium price by accident. However, even 0.008% of the Pakistani population still corresponds to 15,000 people potentially being misclassified as “terrorists” and targeted by the military—not to mention innocent bystanders or first responders who happen to get in the way. Security guru Bruce Schneier agreed. “Government uses of big data are inherently different from corporate uses,” he told Ars. “The accuracy requirements mean that the same technology doesn’t work. If Google makes a mistake, people see an ad for a car they don’t want to buy. If the government makes a mistake, they kill innocents.” (via Cory Doctorow)
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.”
2015 CCC Videos — collected talks from the 32nd Chaos Computer Congress conference.
An Integrated Bayesian Approach for Effective Multi-Truth Discovery (PDF) — Integrating data from multiple sources has been increasingly becoming commonplace in both Web and the emerging Internet of Things (IoT) applications to support collective intelligence and collaborative decision-making. Unfortunately, it is not unusual that the information about a single item comes from different sources, which might be noisy, out-of-date, or even erroneous. It is therefore of paramount importance to resolve such conflicts among the data and to find out which piece of information is more reliable.
A Psychological Exploration of Engagement in Geek Culture — Seven studies (N = 2354) develop the Geek Culture Engagement Scale (GCES) to quantify geek engagement and assess its relationships to theoretically relevant personality and individual differences variables. These studies present evidence that individuals may engage in geek culture in order to maintain narcissistic self-views (the great fantasy migration hypothesis), to fulfill belongingness needs (the belongingness hypothesis), and to satisfy needs for creative expression (the need for engagement hypothesis). Geek engagement is found to be associated with elevated grandiose narcissism, extraversion, openness to experience, depression, and subjective well-being across multiple samples.
Oura — very nice wearable, with no UI to worry about. Put it on, and it’s on. (via Fast Company)
Science Isn’t Broken — it’s just a hell of a lot harder than we give it credit for. Beautifully written (and interactively illustrated) description of why science is easy to get wrong.
Eigenvectors in Plain English — absolutely the easiest to understand explanation I’ve ever read. It’s a miracle. (And I crashed and burned in linear algebra when matrices were used, so if *I* can get it …)
John Horton Conway (The Guardian) — These were two separate areas of study that Conway had arrived at by two different paths. So, there’s no reason for them to be linked. But somehow, through the force of his personality, and the intensity of his passion, he bent the mathematical universe to his will. Fascinating profile, taken from a new book.
MIT Self-Assembly Lab — multi-material 3D/4D printing, advances in materials science, and new capabilities in simulation/optimization software […] made it possible to fully program a wide range of materials to change shape, appearance, or other property, on demand.
Kalman Filter — an algorithm that uses a series of measurements observed over time, containing statistical noise and other inaccuracies, and produces estimates of unknown variables that tend to be more precise than those based on a single measurement alone.
Interview with Bruce Sterling — Singapore is like a science fictional society without the fiction. Dubai is like a science fictional society without the science. […] Robots just don’t want to live. They’re inventions, not creatures; they don’t have any appetites or enthusiasms. I don’t think they’d maintain themselves very long without our relentlessly pushing them uphill against their own lifeless entropy. They’re just not entities in the same sense that we are entities; they don’t have much skin in our game. They don’t care and they can’t be bothered. We don’t yet understand how and why we ourselves care and bother, so we’d be hard put to install that capacity inside our robot vacuum cleaners.
Japan’s Robot Revolution — Fugitt said Japan’s weakness was in application and deployment of its advanced technologies. “The Japanese expect other countries and people to appreciate their technology, but they’re inwardly focused. If it doesn’t make sense to them, they typically don’t do it,” he said, citing the example of Japanese advanced wheelchairs having 100 kilogram weight limits. […] South Korea could be a threat [to Japan’s lead in robotics] if the chaebol opened up [and shared technologies], but I don’t see it happening. The U.S. will come in and disrupt things; they’ll cause chaos in a particular market and then run away.
A World Without Work (The Atlantic) — In 1962, President John F. Kennedy said, “If men have the talent to invent new machines that put men out of work, they have the talent to put those men back to work.” […] Technology creates some jobs too, but the creative half of creative destruction is easily overstated. Nine out of 10 workers today are in occupations that existed 100 years ago, and just 5% of the jobs generated between 1993 and 2013 came from “high tech” sectors like computing, software, and telecommunications.
How Not to be Wrong: The Power of Mathematical Thinking (Amazon) — Ellenberg chases mathematical threads through a vast range of time and space, from the everyday to the cosmic, encountering, among other things, baseball, Reaganomics, daring lottery schemes, Voltaire, the replicability crisis in psychology, Italian Renaissance painting, artificial languages, the development of non-Euclidean geometry, the coming obesity apocalypse, Antonin Scalia’s views on crime and punishment, the psychology of slime molds, what Facebook can and can’t figure out about you, and the existence of God. (via Pam Fox)
What Turing Himself Said About the Imitation Game (IEEE) — fascinating history. The second myth is that Turing predicted a machine would pass his test around the beginning of this century. What he actually said on the radio in 1952 was that it would be “at least 100 years” before a machine would stand any chance with (as Newman put it) “no questions barred.”
Running Effective Retrospectives — Each change to the team’s workflow is treated as a scientific experiment, whereby a hypothesis is formed, data collected, and expectations compared with actual results.
Pocket Guide to DARPA Robotics Challenge Finals (Robohub) — The robots will start in a vehicle, drive to a simulated disaster building, and then they’ll have to open doors, walk on rubble, and use tools. Finally, they’ll have to climb a flight of stairs. The fastest team with the same amount of points for completing tasks will win. The main issues teams will face are communications with their robot and battery life: “Even the best batteries are still roughly 10 times less energy-dense than the kinds of fuels we all use to get around,” said Pratt.
Monolith First — echoes the idea that platforms should come from successful apps (the way AWS emerged from operating the Amazon store) rather than be designed before use.
Building a More Assured Hardware Security Module (PDF) — proposal for An open source reference design for HSMs; Scalable, first cut in an FPGA and CPU, later allow higher speed options; Composable, e.g. “Give me a key store and signer suitable for DNSsec”; Reasonable assurance by being open, diverse design team, and an increasingly assured tool-chain. See cryptech.is for more info.