"hardware" entries

Four short links: 26 May 2015

Four short links: 26 May 2015

Keyboard Programming, Oblique Strategies, Engineering Ethics, and Visualisation Gallery

  1. Introduction to Keyboard Programming — what happens when you press a key. (hint: a lot)
  2. Oblique Strategies: Prompts for ProgrammersDo it both ways. Very often doing it both ways is faster than analyzing which is best. Now you also have experimental data instead of just theoretical. Add a toggle if possible. This will let you choose later. Some mistakes are cheaper to make than to avoid.
  3. The Responsibility We Have as Software EngineersWhere’s our Hippocratic Oath, our “First, Do No Harm?” Remember that moment when Google went from “amazing wonderful thing we didn’t have before, which makes our lives so much better” to “another big scary company and holy shit it knows a lot about us!”? That’s coming for our industry and the software engineering profession in particular.
  4. Gallery of Concept Visualisation — plenty I hadn’t seen before.
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Four short links: 14 May 2015

Four short links: 14 May 2015

Human-Machine Cooperation, Concurrent Systems Books, AI Future, and Gesture UI

  1. Ghosts in the Machines (Courtney Nash) — People are neither masters of machines, nor subservient to their machine-learning outcomes — we cannot, and should not, separate the two. We are actors, together, in a very complex system. David Woods calls this “joint cognitive systems.”
  2. TLA+ (Leslie Lamport) — two tutorials: “Principles of Concurrent Computing” and “Specification of Concurrent Systems.” Ironically, I see people grizzling that the book on distributed systems hasn’t been linearised. I wonder if you can partition it into the two tutorials and still have full availability…
  3. Deep Learning vs Probabilistic vs LogicAs of 2015, I pity the fool who prefers Modus Ponens over Gradient Descent.
  4. Touché (Disney Research) — measur[es] capacitive response of object and human at multiple frequencies, a technique that we called Swept Frequency Capacitive Sensing. The signal travels through different paths depending on its frequency, capturing the posture of human hand and body as well as other properties of the context. The resulted data is classified using machine learning algorithms to identify gestures that are then used to trigger desired responses of the user interface.
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Four short links: 13 May 2015

Four short links: 13 May 2015

Makey Makey Go, Driverless Accidents, HTTP/2 Guidelines, and Choking The Mac

  1. Makey Makey Go (Kickstarter) — $19 portable Makey Makey hardware kit. (via Makezine)
  2. US Driverless Car Accidents (NYTimes) — Delphi sent AP an accident report showing its car was hit, but Google has not made public any records, so both enthusiasts and critics of the emerging technology have only the company’s word on what happened. The California Department of Motor Vehicles said it could not release details from accident reports. This lack of transparency troubles critics who want the public to be able to monitor the rollout of a technology that its own developers acknowledge remains imperfect.
  3. Architecting Websites for the HTTP/2 EraHTTP/2 introduces multiplexing, which allows one TCP/IP connection to request and receive multiple resources, intertwined. Requests won’t be blocking anymore, so there is no need for multiple TCP connections on multiple domain names. In fact, opening multiple connections would hurt performance in HTTP/2. This is going to be exciting.
  4. tripmode — software to control the downloads your Mac software wants to make, even when you’re tethered or on a pay-per-meg hotspot.
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Four short links: 11 May 2015

Four short links: 11 May 2015

Age of Infrastructure, Facial Expressions, Proof Assistants, and Programmer Talent

  1. Welcome to the Age of Infrastructure (Annalee Newitz) — The Internet isn’t that thing in there, inside your little glowing box. It’s in your washing machine, kitchen appliances, pet feeder, your internal organs, your car, your streets, the very walls of your house. You use your wearable to interface with the world out there.
  2. Facial Performance Sensing Head-Mounted Display (YouTube) — glorious use of an Oculus headset, to capture (for reproduction on an avatar) fine-grained facial expressions. From SIGGRAPH 2015.
  3. Mathematical Proof Assistants — human augmentation in mathematics.
  4. The Programmer Talent Myth (LWN) — Jacob Kaplan-Moss on the distribution of programmer talent and the damage that the bimodal myth causes.
Comments: 2
Four short links: 5 May 2015

Four short links: 5 May 2015

Agile Hardware, Time Series Data, Data Loss, and Automating Security

  1. How We Do Agile Hardware Development at MeldIn every sprint we built both hardware and software. This doesn’t mean we had a fully fabricated new board rev once a week. […] We couldn’t build a complete new board every week, and early on we didn’t even know for sure what parts we wanted in our final BOM (Bill of Materials) so we used eval boards. These stories of how companies iterated fast will eventually build a set of best practices for hardware startups, similar to those in software.
  2. Recording Time Series — if data arrives with variable latency, timestamps are really probabilistic ranges. How do you store your data for searches and calculations that reflect reality, and are not erroneous because you’re ignoring a simplification you made to store the data more conveniently?
  3. Call Me Maybe, ElasticSearch 1.5.0To be precise, Elasticsearch’s transaction log does not put your data safety first. It puts it anywhere from zero to five seconds later. In this test we kill random Elasticsearch processes with kill -9 and restart them. In a datastore like Zookeeper, Postgres, BerkeleyDB, SQLite, or MySQL, this is safe: transactions are written to the transaction log and fsynced before acknowledgement. In Mongo, the fsync flags ensure this property as well. In Elasticsearch, write acknowledgement takes place before the transaction is flushed to disk, which means you can lose up to five seconds of writes by default. In this particular run, ES lost about 10% of acknowledged writes.
  4. FIDO — Netflix’s open source system for automatically analyzing security events and responding to security incidents.
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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.
Comments: 2
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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