Facebook Biometrics Cache (Business Insider) — Facebook has been accused of violating the privacy of its users by collecting their facial data, according to a class-action lawsuit filed last week. This data-collection program led to its well-known automatic face-tagging service. But it also helped Facebook create “the largest privately held stash of biometric face-recognition data in the world,” the Courthouse News Service reports.
The Clustering of Time Series Sequences is Meaningless (PDF) — Clustering of time series subsequences is meaningless. More concretely, clusters extracted from these time series are forced to obey a certain constraint that is pathologically unlikely to be satisfied by any data set, and because of this, the clusters extracted by any clustering algorithm are essentially random. While this constraint can be intuitively demonstrated with a simple illustration and is simple to prove, it has never appeared in the literature. We can justify calling our claim surprising since it invalidates the contribution of dozens of previously published papers. We will justify our claim with a theorem, illustrative examples, and a comprehensive set of experiments on reimplementations of previous work. From 2003, warning against sliding window techniques.
Toolkits for the Mind (MIT TR) — Programming–language designer Guido van Rossum, who spent seven years at Google and now works at Dropbox, says that once a software company gets to be a certain size, the only way to stave off chaos is to use a language that requires more from the programmer up front. “It feels like it’s slowing you down because you have to say everything three times,” van Rossum says. Amen!
Robots Roam Earth’s Imperiled Oceans (Wired) — It’s six feet long and shaped like an airliner, with two wings and a tail fin, and bears the message, “OCEANOGRAPHIC INSTRUMENT PLEASE DO NOT DISTURB.” All caps considered, though, it’s a more innocuous epigram than the one on a drone I saw back at the dock: “Not a weapon — Science Instrument.”
Giving Robots and Prostheses the Human Touch — the team, led by mechanical engineer Veronica J. Santos, is constructing a language of touch that both a computer and a human can understand. The researchers are quantifying this with mechanical touch sensors that interact with objects of various shapes, sizes, and textures. Using an array of instrumentation, Santos’ team is able to translate that interaction into data a computer can understand. The data is used to create a formula or algorithm that gives the computer the ability to identify patterns among the items it has in its library of experiences and something it has never felt before. This research will help the team develop artificial haptic intelligence, which is, essentially, giving robots, as well as prostheses, the “human touch.”
boltons — things in Python that should have been builtins.
Everything We Wish We’d Known About Building Data Products (DJ Patil and RusJan Belkin) — Data is super messy, and data cleanup will always be literally 80% of the work. In other words, data is the problem. […] “If you’re not thinking about how to keep your data clean from the very beginning, you’re fucked. I guarantee it.” […] “Every single company I’ve worked at and talked to has the same problem without a single exception so far — poor data quality, especially tracking data,” he says.“Either there’s incomplete data, missing tracking data, duplicative tracking data.” To solve this problem, you must invest a ton of time and energy monitoring data quality. You need to monitor and alert as carefully as you monitor site SLAs. You need to treat data quality bugs as more than a first priority. Don’t be afraid to fail a deploy if you detect data quality issues.
The Internet of Kafkaesque Things (ACLU) — As computers are deployed in more regulatory roles, and therefore make more judgments about us, we may be afflicted with many more of the rigid, unjust rulings for which bureaucracies are so notorious.
Complete Force Control in Constrained Under-actuated Mechanical Systems (Robohub) — Nori focuses on finding ways to advance the dynamic system of a robot – the forces that interact and make the system move. Key to developing dynamic movements in a robot is control, accompanied by the way the robot interacts with the environment. Nori talks us through the latest developments, designs, and formulas for floating-base/constrained mechanical systems, whole-body motion control of humanoid systems, whole-body dynamics computation on the iCub humanoid, and finishes with a video on recent implementations of whole-body motion control on the iCub. Video and download of presentation.
Welfare Makes America More Entrepreneurial (The Atlantic) — In a 2014 paper, Olds examined the link between entrepreneurship and food stamps, and found that the expansion of the program in some states in the early 2000s increased the chance that newly eligible households would own an incorporated business by 16%. (Incorporated firms are a better proxy for job-creating startups than unincorporated ones.)
Festo’s Fantastical Insectoid Robots Include Bionic Ants and Butterflies (IEEE) — Each butterfly has a 50-centimeter wingspan and weighs just 32 grams, but carries along two servo motors to independently actuate the wings, an IMU, accelerometer, gyro, and compass, along with two tiny 90-mAh lithium-polymer batteries. With a wing beat frequency of between one and two flaps per second, top speed is 2.5 m/s, with a flight time of three to four minutes before needing a 15-minute charge. The wings themselves use impossibly thin carbon rods for structure, and are covered with an even thinner elastic capacitor film.
Arduino Celebration and Hexbugs hacking with Bob Martin (SparkFun) — The Hunter demo is a combination of object detection and object avoidance. It uses an IR sensor array to determine objects around it. Objects that appear and then disappear quickly, say in a second or two are targets which it will walk towards; however, a target that stays constant will be avoided. I’m still trying to find the perfect balance between making a decision between fleeing prey and a wall using only simple proximity samples from an IR detector array.
Swarmfarm Robotics — His previous weed sprayer weighed 21 tonnes, measured 36 metres across its spray unit, guzzled diesel by the bucketload and needed a paid driver who would only work limited hours. Two robots working together on Bendee effortlessly sprayed weeds in a 70ha mung-bean crop last month. Their infra-red beams picked up any small weeds among the crop rows and sent a message to the nozzle to eject a small chemical spray. Bate hopes to soon use microwave or laser technology to kill the weeds. Best of all, the robots do the work without guidance. They work 24 hours a day. They have in-built navigation and obstacle detection, making them robust and able to decide if an area of a paddock should not be traversed. Special swarming technology means the robots can detect each other and know which part of the paddock has already been assessed and sprayed.
Route to Market (Matt Webb) — The route to market is not what makes the product good. […] So the way you design the product to best take it to market is not the same process to make it great for its users.
I-JSON (Tim Bray) — I-JSON is just a note saying that if you construct a chunk of JSON and avoid the interop failures described in RFC 7159, you can call it an “I-JSON Message.” If any known JSON implementation creates an I-JSON message and sends it to any other known JSON implementation, the chance of software surprises is vanishingly small.
Sirius — UMich open source “intelligent Personal Assistant” (aka Siri, Cortana, Google Now, etc.). Text recognition, image recognition, query processing components. They hope it’ll be a focal point for research in the area, the way that open source operating systems have focused university research.
MIT DragonBot Evolving to Teach Kids (IEEE Spectrum) — they’re moving from “Wizard of Oz” (humans-behind-the-scenes) control to autonomous operation. Lovely example of Flintstoning in a robotics context.
Personal Assistants Coming (Robohub) — 2015 is the year physical products will be coming to market and available for experimentation and testing. Pepper ships in the summer in Japan, JIBO ships preorders in Q3, as does Cubic in the fall and EmoSpark in the summer. […]The key to the outcome of this race is whether a general purpose AI will be able to steer people through their digital world, or whether users would rather navigate to applications that are specialists (such as American Airlines or Dominos Pizza).
Surgical Micro-Robot Swarms — A swarm of medical microrobots. Start with cm sized robots. These already exist in the form of pillbots and I reference the work of Paolo Dario’s lab in this direction. Then get 10 times smaller to mm sized robots. Here we’re at the limit of making robots with conventional mechatronics. The almost successful I-SWARM project prototyped remarkable robots measuring 4 x 4 x 3mm. But now shrink by another 3 orders of magnitude to microbots, measured in micrometers. This is how small robots would have to be in order to swim through and access (most of) the vascular system. Here we are far beyond conventional materials and electronics, but amazingly work is going on to control bacteria. In the example I give from the lab of Sylvain Martel, swarms of magnetotactic bacteria are steered by an external magnetic field and, interestingly, tracked in an MRI scanner.
Media Hacking — interesting discussion of the techniques used to spread disinformation through social media, often using bots to surface/promote a message.
Apple Research Kit — Apple positioning their mobile personal biodata tools with medical legitimacy, presumably as a way to distance themselves from the stereotypical quantified selfer. I’m reminded of the gym chain owner who told me, about the Nike+, “yeah, maybe 5% of my clients will want this. The rest go to the gym so they can eat and drink what they want.”
Designing the Human-Robot Relationship (O’Reilly) — We can use those same principles [Jakob Nielsen’s usability heuristics] and look for implications of robots serving our higher ordered needs, as we move from serving needs related to convenience or performance to actually supporting our decision making to emerging technologies, moving from being able to do anything or be magic in terms of the user interface to being more human in the user interface.
Why Are Geospatial Databases So Hard To Build? — Algorithms in computer science, with rare exception, leverage properties unique to one-dimensional scalar data models. In other words, data types you can abstractly represent as an integer. Even when scalar data types are multidimensional, they can often be mapped to one dimension. This works well, as the majority of [what] data people care about can be represented with scalar types. If your data model is inherently non-scalar, you enter an algorithm wasteland in the computer science literature.
Matthew Effects in Reading (PDF) — Walberg, following Merton, has dubbed those educational sequences where early achievement spawns faster rates of subsequent achievement “Matthew effects,” after the Gospel according to Matthew: “For unto every one that hath shall be given, and he shall have abundance: but from him that hath not shall be taken away even that which he hath” (XXV:29) (via 2015 Troubling Trends and Possibilities in K-12)
Working Below the API is a Dead End (Forbes) — Drivers are opting into a dichotomous workforce: the worker bees below the software layer have no opportunity for on-the-job training that advances their career, and compassionate social connections don’t pierce the software layer either. The skills they develop in driving are not an investment in their future. Once you introduce the software layer between ‘management’ (Uber’s full-time employees building the app and computer systems) and the human workers below the software layer (Uber’s drivers, Instacart’s delivery people), there’s no obvious path upwards. In fact, there’s a massive gap and no systems in place to bridge it. (via John Robb)
The Real Robot Economy and the Bus Ticket Inspector (Guardian) — None of the cinematic worries about machines that take decisions about healthcare or military action are at play here. Hidden in these everyday, mundane interactions are different moral or ethical questions about the future of AI: if a job is affected but not taken over by a robot, how and when does the new system interact with a consumer? Is it ok to turn human social intelligence – managing a difficult customer – into a commodity? Is it ok that a decision lies with a handheld device, while the human is just a mouthpiece? Where “robots” is the usual shorthand for technology that replaces manual work. (via Dan Hill)