"hardware" entries

Four short links: 21 April 2015

Four short links: 21 April 2015

Chromebooks and Arduinos, 3rd Person Driving, Software Development, and Go Debugging

  1. Chromebooks and Arduino — two great edtech tastes that taste great together.
  2. 3rd Person Driving (IEEE) — A Taiwan company called SPTek has figured out a way to use an array of cameras to generate a 3-D “Around View Monitor” that can show you multiple different views of the outside of your car. Use a top-down view for tight parking spaces, a front view looking backward for highway lane changes, or a see-through rear view for pulling out into traffic. It’s not a video game; it’s the next step in safety.
  3. Lessons Learned in Software Development — omg every word of this.
  4. Cross-Platform Debugger for Gotake the source code of a target program, insert debugging code between every line, then compile and run that instead. The result is a fully-functional debugger that is extremely portable. In fact, thanks to gopherjs, you can run it right here in your browser!
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Four short links: 20 April 2015

Four short links: 20 April 2015

Edtech Advice, MEMS Sensors, Security in Go, and Building Teams

  1. Ed Tech Developer’s Guide (PDF) — U.S. government’s largely reasonable advice for educational technology startups. Nonetheless, take with a healthy dose of The Audrey Test.
  2. The Crazy-Tiny Next Generation of Computers — 1 cubic millimeter-sized sensors are coming. The only sound you might hear is a prolonged groan. That’s because these computers are just one cubic millimeter in size, and once they hit the floor, they’re gone. “We just lose them,” Dutta says. “It’s worse than jewelry.”
  3. Looking for Security Trouble Spots in Go — brief summary of the known security issues in and around Go code.
  4. The New Science of Building Great Teams (Sandy Pentland) — fascinating discussion of MIT’s Human Dynamics lab’s research into how great teams function. The data also reveal, at a higher level, that successful teams share several defining characteristics: 1. Everyone on the team talks and listens in roughly equal measure, keeping contributions short and sweet. 2. Members face one another, and their conversations and gestures are energetic. 3. Members connect directly with one another—not just with the team leader. 4. Members carry on back-channel or side conversations within the team. 5. Members periodically break, go exploring outside the team, and bring information back.
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Four short links: 16 April 2015

Four short links: 16 April 2015

Relationships and Inference, Mother of All Demos, Kafka at Scale, and Real World Hardware

  1. DeepDiveDeepDive is targeted to help users extract relations between entities from data and make inferences about facts involving the entities. DeepDive can process structured, unstructured, clean, or noisy data and outputs the results into a database.
  2. From the Vault: Watching (and re-watching) “The Mother of All Demos”“I wish there was more about the social vision for computing—I worked with him for a long time, and Doug was always thinking ‘how can we collectively collaborate,’ like a sort of rock band.”
  3. Running Kafka at Scale (LinkedIn Engineering) — This tiered infrastructure solves many problems, but it greatly complicates monitoring Kafka and assuring its health. While a single Kafka cluster, when running normally, will not lose messages, the introduction of additional tiers, along with additional components such as mirror makers, creates myriad points of failure where messages can disappear. In addition to monitoring the Kafka clusters and their health, we needed to create a means to assure that all messages produced are present in each of the tiers, and make it to the critical consumers of that data.
  4. 3D Printing Titanium, and the Bin of Broken Dreams — you will learn HUGE amounts on the challenges of real-world manufacturing by reading this.
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Four short links: 10 April 2015

Four short links: 10 April 2015

Graph Algorithm, Touchy Robots, Python Bolt-Ons, and Building Data Products

  1. Exact Maximum Clique for Large or Massive Real Graphs — explanation of how BBMCSP works.
  2. Giving Robots and Prostheses the Human Touchthe 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.”
  3. boltons — things in Python that should have been builtins.
  4. 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.
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Four short links: 3 April 2015

Four short links: 3 April 2015

Augmenting Humans, Body-Powered CPUs, Predicting the Future, and Hermit Life

  1. Unpowered Ankle Exoskeleton“As we understand human biomechanics better, we’ve begun to see wearable robotic devices that can restore or enhance human motor performance,” says Collins. “This bodes well for a future with devices that are lightweight, energy-efficient, and relatively inexpensive, yet enhance human mobility.”
  2. Body-Powered Processing (Ars Technica) — The new SAM L21 32-bit ARM family of microcontroller (MCUs) consume less than 35 microamps of power per megahertz of processing speed while active, and less than 200 nanoamps of power overall when in deep sleep mode—with varying states in between. The chip is so low power that it can be powered off energy capture from the body. (via Greg Linden)
  3. Temporal Effects in Trend Prediction: Identifying the Most Popular Nodes in the Future (PLOSone) — We find that TBP have high general accuracy in predicting the future most popular nodes. More importantly, it can identify many potential objects with low popularity in the past but high popularity in the future.
  4. The Shut-In EconomyIn 1998, Carnegie Mellon researchers warned that the Internet could make us into hermits. They released a study monitoring the social behavior of 169 people making their first forays online. The Web-surfers started talking less with family and friends, and grew more isolated and depressed. “We were surprised to find that what is a social technology has such anti-social consequences,” said one of the researchers at the time. “And these are the same people who, when asked, describe the Internet as a positive thing.”
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Four short links: 1 April 2015

Four short links: 1 April 2015

Tuning Fanout, Moore's Law, 3D Everything, and Social Graph Analysis

  1. Facebook’s Mystery MachineThe goal of this paper is very similar to that of Google Dapper[…]. Both work [to] try to figure out bottlenecks in performance in high fanout large-scale Internet services. Both work us[ing] similar methods, however this work (the mystery machine) tries to accomplish the task relying on less instrumentation than Google Dapper. The novelty of the mystery machine work is that it tries to infer the component call graph implicitly via mining the logs, where as Google Dapper instrumented each call in a meticulous manner and explicitly obtained the entire call graph.
  2. The Multiple Lives of Moore’s LawA shrinking transistor not only allowed more components to be crammed onto an integrated circuit but also made those transistors faster and less power hungry. This single factor has been responsible for much of the staying power of Moore’s Law, and it’s lasted through two very different incarnations. In the early days, a phase I call Moore’s Law 1.0, progress came by “scaling up”—adding more components to a chip. At first, the goal was simply to gobble up the discrete components of existing applications and put them in one reliable and inexpensive package. As a result, chips got bigger and more complex. The microprocessor, which emerged in the early 1970s, exemplifies this phase. But over the last few decades, progress in the semiconductor industry became dominated by Moore’s Law 2.0. This era is all about “scaling down,” driving down the size and cost of transistors even if the number of transistors per chip does not go up.
  3. BoXZY Rapid-Change FabLab: Mill, Laser Engraver, 3D Printer (Kickstarter) — project that promises you the ability to swap out heads to get different behaviour from the “move something in 3 dimensions” infrastructure in the box.
  4. SociaLite (Github) — a distributed query language for graph analysis and data mining. (via Ben Lorica)
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Four short links: 27 March 2015

Four short links: 27 March 2015

Welfare and Entrepreneurialism, Infrastructure Secrets, Insectoid Robots, Hacking Hexbugs

  1. 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.)
  2. Security of Infrastructure Secrets — everything has a key that’s just one compromise or accidental drop away.
  3. 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.
  4. 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.
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Four short links: 26 March 2015

Four short links: 26 March 2015

GPU Graph Algorithms, Data Sharing, Build Like Google, and Distributed Systems Theory

  1. gunrocka CUDA library for graph primitives that refactors, integrates, and generalizes best-of-class GPU implementations of breadth-first search, connected components, and betweenness centrality into a unified code base useful for future development of high-performance GPU graph primitives. (via Ben Lorica)
  2. How to Share Data with a Statisticiansome instruction on the best way to share data to avoid the most common pitfalls and sources of delay in the transition from data collection to data analysis.
  3. Bazela build tool, i.e. a tool that will run compilers and tests to assemble your software, similar to Make, Ant, Gradle, Buck, Pants, and Maven. Google’s build tool, to be precise.
  4. You Can’t Have Exactly-Once Delivery — not about the worst post office ever. FLP and the Two Generals Problem are not design complexities, they are impossibility results.
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Four short links: 24 March 2015

Four short links: 24 March 2015

Tricorder Prototype, Web Performance, 3D Licensing, and Network Simulation

  1. Tricorder Prototypecollar+earpiece, base station, diagnostic stick (lab tests for diabetes, pneumonia, tb, etc), and scanning wand (examine lesions, otoscope for ears, even spirometer). (via Slashdot)
  2. Souders Joins SpeedcurveDuring these engagements, I’ve seen that many of these companies don’t have the necessary tools to help them identify how performance is impacting (hurting) the user experience on their websites. There is even less information about ways to improve performance. The standard performance metric is page load time, but there’s often no correlation between page load time and the user’s experience. We need to shift from network-based metrics to user experience metrics that focus on rendering and when content becomes available. That’s exactly what Mark is doing at SpeedCurve, and why I’m excited to join him.
  3. 3 Steps for Licensing Your 3D-Printed Stuff (PDF) — this paper is not actually about choosing the right license for your 3D printable stuff (sorry about that). Instead, this paper aims to flesh out a copyright analysis for both physical objects and for the digital files that represent them, allowing you to really understand what parts of your 3D object you are—and are not—licensing. Understanding what you are licensing is key to choosing the right license. Simply put, this is because you cannot license what you do not legally control in the first place. There is no point in considering licenses that ultimately do not have the power to address whatever behavior you’re aiming to control. However, once you understand what it is you want to license, choosing the license itself is fairly straightforward. (via BoingBoing)
  4. Augmented Traffic Control — Facebook’s tool for simulating degraded network conditions.
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Four short links: 19 March 2015

Four short links: 19 March 2015

Changing Behaviour, Building Filters, Public Access, and Working Capital

  1. Using Monitoring Dashboards to Change Behaviour[After years of neglect] One day we wrote some brittle Ruby scripts that polled various services. They collated the metrics into a simple database and we automated some email reports and built a dashboard showing key service metrics. We pinpointed issues that we wanted to show people. Things like the login times, how long it would take to search for certain keywords in the app, and how many users were actually using the service, along with costs and other interesting facts. We sent out the link to the dashboard at 9am on Monday morning, before the weekly management call. Within 2 weeks most problems were addressed. It is very difficult to combat data, especially when it is laid out in an easy to understand way.
  2. Quiet Mitsubishi Cars — noise-cancelling on phone calls by using machine learning to build the filters.
  3. NSF Requiring Public AccessNSF will require that articles in peer-reviewed scholarly journals and papers in juried conference proceedings or transactions be deposited in a public access compliant repository and be available for download, reading, and analysis within one year of publication.
  4. Filtered for Capital (Matt Webb) — It’s important to get a credit line [for hardware startups] because growing organically isn’t possible — even if half your sell-in price is margin, you can only afford to grow your batch size at 50% per cycle… and whether it’s credit or re-investing the margin, all that growth incurs risk, because the items aren’t pre-sold. There are double binds all over the place here.
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