"design" entries

Four short links: 25 March 2015

Four short links: 25 March 2015

Selling Customers, Classier Parsing, License Plates, and GitHub's CSS

  1. RadioShack’s Customer Data For Sale (Ars Technica) — trying to sell customer data as part of court-supervised bankruptcy.
  2. Classp: A Classier Way to Parse (Google Code) — The abstract syntax tree is what programmers typically want to work with. With class patterns, you only have two jobs: design the abstract syntax tree and write a formatter for it. (A formatter is the function that writes out the abstract syntax tree in the target language.)
  3. 4.6M License Plate Records From FOIA Request (Ars Technica) — from Oakland.
  4. Primerthe CSS toolkit and guidelines that power GitHub.
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Four short links: 23 March 2015

Four short links: 23 March 2015

Agricultural Robots, Business Model Design, Simulations, and Interoperable JSON

  1. Swarmfarm RoboticsHis 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.
  2. 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.
  3. Explorable Explanations — points to many sweet examples of interactive explorable simulations/explanations.
  4. 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.
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Full-stack tensions on the Web

How much do you need to know?

Vista_de_la_Biblioteca_VasconcelosI expected that CSSDevConf would be primarily a show about front-end work, focused on work in clients and specifically in browsers. I kept running into conversations, though, about the challenges of moving between the front and back end, the client and the server side. Some were from developers suddenly told that they had to become “full-stack developers” covering the whole spectrum, while others were from front-end engineers suddenly finding a flood of back-end developers tinkering with the client side of their applications. “Full-stack” isn’t always a cheerful story.

In the early days of the Web, “full-stack” was normal. While there were certainly people who focused on running web servers or designing sites as beautiful as the technology would allow, there were lots of webmasters who knew how to design a site, write HTML, manage a server, and maybe write some CGI code for early applications.

Formal separation of concerns among HTML, CSS, and JavaScript made it easier to share responsibilities among specialists. As the dot-com boom proceeded, specialization accelerated, with dedicated designers, programmers, and sysadmins coming to the work. Perhaps there were too many titles.

Even as the bust set in, specialization remained the trend because Web projects — especially on the server side — had grown far more complicated. They weren’t just a server and a few scripts, but a complete stack, including templates, logic, and usually a database. Whether you preferred the LAMP stack, a Microsoft ASP stack, or perhaps Java servlets and JSP, the server side rapidly became its own complex arena. Intranet development in particular exploded as a way to build server-based applications that could (cheaply) connect data sources to users on multiple platforms. Writing web apps was faster and cheaper than writing desktop apps, with more tolerance for platform variation.
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Four short links: 11 March 2015

Four short links: 11 March 2015

Working Manager, Open Source Server Chassis, Data Context, and Coevolved Design & Users

  1. As a Working Manager (Ian Bicking) — I look forward to every new entry in Ian’s diary, and this one didn’t disappoint. But I’m a working manager. Is now the right time to investigate that odd log message I’m seeing, or to think about who I should talk to about product opportunities? There’s no metric to compare the priority of two tasks that are so far apart. If I am going to find time to do development I am a bit worried I have two options: (1) Keep doing programming after hours; (2) Start dropping some balls as a manager.
  2. Introducing Yosemite (Facebook) — a modular chassis that contains high-powered system-on-a-chip (SoC) processor cards.
  3. The Joyless World of Data-Driven StartupsThere is so much invisible, fluid context wrapped around a data point that we are usually unable to fully comprehend exactly what that data represents or means. We often think we know, but we rarely do. But we really WANT it to mean something, because using data in our work is scientific. It’s not our decision that was wrong — we used the data that was available. Data is the ultimate scapegoat.
  4. History of the Urban Dashboardthe dashboard and its user had to evolve in response to one another. The increasing complexity of the flight dashboard necessitated advanced training for pilots — particularly through new flight simulators — and new research on cockpit design.
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Four short links: 9 March 2015

Four short links: 9 March 2015

Shareable Audio, Designing Robot Relationships, Machine Learning for Programming, and Geospatial Databases

  1. Four Types of Audio That People Share (Nieman Lab) — Audio Explainers, Whoa! Sounds, Storytellers, and Snappy Reviews, the results of experiments with NPR stations.
  2. 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.
  3. Machine Learning for General Programming — Peter Norvig talk. What more do you need to know?
  4. 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.
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Four short links: 6 March 2015

Four short links: 6 March 2015

Design Fiction, 3D License, Web Funding, and API Magic

  1. Matt Jones: Practical Design Fiction (Vimeo) — the log scale of experience! Fantastic hour-long recap of the BERG thinking that he’s continued at the Google Creative Lab in NYC. (via Matt Jones)
  2. 3dPL — public license for 3d objects. (via BoingBoing)
  3. Google Contributor — when the web’s biggest advertiser tries alternative ways to fund web content, I’m interested.
  4. Templaran HTTP proxy that provides advanced features to help you make better use of and tame HTTP APIs. Timeouts, caching, metrics, request collapsing, …
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Four short links: 5 March 2015

Four short links: 5 March 2015

Web Grain, Cognition and Computation, New Smart Watch, and Assessing Accuracy

  1. The Web’s Grain (Frank Chimero) — What would happen if we stopped treating the web like a blank canvas to paint on, and instead like a material to build with?
  2. Bruce Sterling on Convergence of Humans and MachinesI like to use the terms “cognition” and “computation”. Cognition is something that happens in brains, physical, biological brains. Computation is a thing that happens with software strings on electronic tracks that are inscribed out of silicon and put on fibre board. They are not the same thing, and saying that makes the same mistake as in earlier times, when people said that human thought was like a steam engine.
  3. Smart Pocket Watch — I love to see people trying different design experiences. This is beautiful. And built on Firefox OS!
  4. Knowledge-Based Trust (PDF) — Google research paper on how to assess factual accuracy of web page content. It was bad enough when Google incentivised people to make content-free pages. Next there’ll be a reward for scamming bogus facts into Google’s facts database.
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Four short links: 4 March 2015

Four short links: 4 March 2015

Go Microservices, Watch Experience, Multithreading Bugs, and Spooks Ahoy

  1. Microservices in Go — tale of rewriting a Ruby monolith as Go microservices. Interesting, though being delivered at Gophercon India suggests the ending is probably not unhappy.
  2. Watch & Wear (John Cross Neumann) — Android watch as predictor of the value and experience of an Apple Watch. I believe this is the true sweet spot for meaningful wearable experiences. Information that matters to you in the moment, but requires no intervention. Wear actually does this extremely well through Google Now. Traffic, Time to Home, Reminders, Friend’s Birthdays, and Travel Information all work beautifully. […] After some real experience with Wear, I think what is more important is to consider what Apple Watch is missing: Google Services. Google Services are a big component of what can make wearing a tiny screen on your wrist meaningful and personal. I wouldn’t be surprised after the initial wave of apps through the app store if Google Now ends up being the killer app for Apple Watch.
  3. Solving 11 Likely Problems In Your Multithreaded Code (Joe Duffy) — a good breakdown of concurrency problems, including lower-level ones than high-level languages expose. But beware. If you try this [accessing variables with synchronisation] on a misaligned memory location, or a location that isn’t naturally sized, you can encounter a read or write tearing. Tearing occurs because reading or writing such locations actually involves multiple physical memory operations. Concurrent updates can happen in between these, potentially causing the resultant value to be some blend of the before and after values.
  4. Obama Sharply Criticizes China’s Plans for New Technology Rules (Reuters) — In an interview with Reuters, Obama said he was concerned about Beijing’s plans for a far-reaching counterterrorism law that would require technology firms to hand over encryption keys, the passcodes that help protect data, and install security “backdoors” in their systems to give Chinese authorities surveillance access. Goose sauce is NOT gander sauce! NOT! Mmm, delicious spook sauce.
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Four short links: 3 March 2015

Four short links: 3 March 2015

Wearable Warning, Time Series Data, App Cards, and Secure Comms

  1. You Guys Realize the Apple Watch is Going to Flop, Right? — leaving aside the “guys” assumption of its readers, you can take this either as a list of the challenges Apple will inevitably overcome or bypass when they release their watch, or (as intended) a list of the many reasons that it’s too damn soon for watches to be useful. The Apple Watch is Jonathan Ive’s new Newton. It’s a potentially promising form that’s being built about 10 years before Apple has the technology or infrastructure to pull it off in a meaningful way. As a result, the novel interactions that could have made the Apple watch a must-have device aren’t in the company’s launch product, nor are they on the immediate horizon. And all Apple can sell the public on is a few tweets and emails on their wrists—an attempt at a fashion statement that needs to be charged once or more a day.
  2. InfluxDB, Now With Tags and More UnicornsThe combination of these new features [tagging, and the use of tags in queries] makes InfluxDB not just a time series database, but also a database for time series discovery. It’s our solution for making the problem of dealing with hundreds of thousands or millions of time series tractable.
  3. The End of Apps as We Know ThemIt may be very likely that the primary interface for interacting with apps will not be the app itself. The app is primarily a publishing tool. The number one way people use your app is through this notification layer, or aggregated card stream. Not by opening the app itself. To which one grumpy O’Reilly editor replied, “cards are the new walled garden.”
  4. Signal 2.0Signal uses your existing phone number and address book. There are no separate logins, usernames, passwords, or PINs to manage or lose. We cannot hear your conversations or see your messages, and no one else can either. Everything in Signal is always end-to-end encrypted, and painstakingly engineered in order to keep your communication safe.
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Four short links: 2 March 2015

Four short links: 2 March 2015

Onboarding UX, Productivity Vision, Bad ML, and Lifelong Learning

  1. User Onboarding Teardowns — the UX of new users. (via Andy Baio)
  2. Microsoft’s Productivity Vision — always-on thinged-up Internet everywhere, with predictions and magic by the dozen.
  3. Machine Learning Done WrongWhen dealing with small amounts of data, it’s reasonable to try as many algorithms as possible and to pick the best one since the cost of experimentation is low. But as we hit “big data,” it pays off to analyze the data upfront and then design the modeling pipeline (pre-processing, modeling, optimization algorithm, evaluation, productionization) accordingly.
  4. Ten Simple Rules for Lifelong Learning According to Richard Hamming (PLoScompBio) — Exponential growth of the amount of knowledge is a central feature of the modern era. As Hamming points out, since the time of Isaac Newton (1642/3-1726/7), the total amount of knowledge (including but not limited to technical fields) has doubled about every 17 years. At the same time, the half-life of technical knowledge has been estimated to be about 15 years. If the total amount of knowledge available today is x, then in 15 years the total amount of knowledge can be expected to be nearly 2x, while the amount of knowledge that has become obsolete will be about 0.5x. This means that the total amount of knowledge thought to be valid has increased from x to nearly 1.5x. Taken together, this means that if your daughter or son was born when you were 34 years old, the amount of knowledge she or he will be faced with on entering university at age 17 will be more than twice the amount you faced when you started college.
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