U.S. Textile Industry Turns to Tech as Gateway to Revival — Warwick Mills is joining the Defense Department, universities including the Massachusetts Institute of Technology, and nearly 50 other companies in an ambitious $320 million project to push the American textile industry into the digital age. Key to the plan is a technical ingredient: embedding a variety of tiny semiconductors and sensors into fabrics that can see, hear, communicate, store energy, warm or cool a person, or monitor the wearer’s health.
Squeezing AI into Mobile Systems (IEEE Spectrum) — Sze, working with Joel Emer, also an MIT computer science professor and senior distinguished research scientist at Nvidia, developed Eyeriss, the first custom chip designed to run a state-of-the-art convolutional neural network. They showed they could run AlexNet, a particularly demanding algorithm, using less than one-tenth the energy of a typical mobile GPU: instead of consuming 5 to 10 watts, Eyeriss used 0.3 W.
The 8-Bit Game That Makes Statistics Addictive (The Atlantic) — that game is Guess The Correlation. “As a researcher, you read papers and a lot of the time, you eyeball the figures without even reading the text,” he says. “You see a plot—it could even be your own plot—and make a judgment based on it. Contrary to what people believe, they’re not very good at this. And I have the data to prove that.”
Paul Ford on Racter — But don’t get too ahead of things. Using Racter is not as different from using Siri as you might expect. It’s just that Siri has petabytes of stuff in her brain, whereas Racter has a floppy’s worth. Computers have changed a ton in the last 30 years, humans barely at all. Don’t mistake their progress for ours. We’ve learned how to talk to computers, and they’ve learned how to pretend to understand us. Useful when driving. People love chatting with their Amazon Echo. But the conversation still doesn’t really mean anything.
Not Quite So Broken TLS (Adrian Colyer) — instead of ad-hoc codery, A precise and testable specification (in this case for TLS) that unambiguously determines the set of behaviours it allows (and hence also what it does not). The specification should also be executable as a test oracle, to determine whether or not a given implementation is compliant. The paper outlines this for TLS, but I see formal methods growing in importance in coming years. We can’t build an airport with cardboard on a swamp. In this metaphor, cardboard represents our ad hoc dev practices and the swamp is our platform of crap code. The airport is … look, never mind, I’ll work on the metaphor. Read the paper.
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.”
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.
Spermbots — Researchers from the Institute for Integrative Nanosciences at IFW Dresden in Germany have successfully tested tiny, magnetically-driven power suits for individual sperm that can turn them into steerable cyborg “spermbots” that can be remote controlled all the way to the egg. But can they make an underwire bra that the washing machine doesn’t turn into a medieval torture device?
What’s Eating Silicon Valley — In 2014, more Harvard Business School Grads went into technology than into banking for the first time since the dot-com era. […] another reason Wall Street had trouble maintaining goodwill was because of some of the attributes above—hard-charging, too much too soon, parallel reality, money flowing everywhere, rich white guys, etc. The Wall St comparison was new to me, but I can see it as a goodwill risk.
OpenTrons — $3,000 open source personal lab robot for science, with downloadable/shareable protocols.
Why Big Companies Keep Failing: The Stack Fallacy — you’re more likely to succeed if you expand down (to supplant your suppliers) than up (to build the products that are built on top of your product) because you’re a customer of your suppliers, so you know what good product-market fit will look like, but you’re just fantasizing that you can supplant your downstream value.
Tesla Model S Can Now Drive Without You (TechCrunch) — the upside of the Internet of Things is that objects get smarter while you sleep. (In fairness, they can also be pwned by Ukrainian teenagers while you sleep.)
Replacing Judgement with Algorithms (Bruce Schneier) — We can get the benefits of automatic algorithmic systems while avoiding the dangers. It’s not even hard. Transparency and oversight with accountability.
Lessig Interview (WSJ) — the slogan says regulation should be more technology neutral. I am not sure I ever heard a more idiotic statement in my life. There is no neutrality here, just different modes. … I don’t what think the law should say here is what services can do and not do, because the technology is so (fast-changing) the law could never catch up. But that what (we want) to avoid are certain kinds of business models, a prison of bits, where services leverage control over access to content and profit from that control over content.
Bubble-Driven Pseudoscience — In terms of life extension, here are the real opportunities: closing the gap between black and white patients, lowering the infant mortality rate, and making sure the very poorest among us have access to adequate care. You can make sure that many people live longer, right now! But none of this is quite as sexy as living forever, even though it’s got a greater payoff for the nation as a whole. So instead of investing in these areas, you’ve got a bunch of old white men who are afraid to die trying to figure out cryonics.