"design" entries

Four short links: 11 March 2015

Four short links: 11 March 2015

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

by Nat Torkington | @gnat | +Nat Torkington | March 11, 2015
  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 Startups — There 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 Dashboard — the 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.
Four short links: 9 March 2015

Four short links: 9 March 2015

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

by Nat Torkington | @gnat | +Nat Torkington | March 9, 2015
  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.
Four short links: 6 March 2015

Four short links: 6 March 2015

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

by Nat Torkington | @gnat | +Nat Torkington | March 6, 2015
  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. Templar — an HTTP proxy that provides advanced features to help you make better use of and tame HTTP APIs. Timeouts, caching, metrics, request collapsing, …
Four short links: 5 March 2015

Four short links: 5 March 2015

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

by Nat Torkington | @gnat | +Nat Torkington | March 5, 2015
  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 Machines — I 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.
Four short links: 4 March 2015

Four short links: 4 March 2015

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

by Nat Torkington | @gnat | +Nat Torkington | March 4, 2015
  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.
Four short links: 3 March 2015

Four short links: 3 March 2015

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

by Nat Torkington | @gnat | +Nat Torkington | March 3, 2015
  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 Unicorns — The 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 Them — It 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 2.0 — Signal 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.
Four short links: 2 March 2015

Four short links: 2 March 2015

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

by Nat Torkington | @gnat | +Nat Torkington | March 2, 2015
  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 Wrong — When 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.
Four short links: 23 February 2015

Four short links: 23 February 2015

Self-Assembling Chairs, Home Monitoring, Unicorn Horn, and Cloud Security

by Nat Torkington | @gnat | +Nat Torkington | February 23, 2015
  1. MIT Scientists and the Self-Assembling Chair (Wired) — using turbulence to randomise interactions, and pieces that connect when the random motions align. From the Self-Assembly Lab at MIT.
  2. Calaos — a free software project (GPLv3) that lets you control and monitor your home.
  3. Founder Wants to be a Horse Not a Unicorn (Business Insider) — this way of thinking  —  all or nothing moonshots to maximise shareholder value  —  has become pervasive dogma in tech. It’s become the only respectable path. Either you’re running a lowly lifestyle business, making ends meet so you can surf all afternoon, or you’re working 17-hour days goring competitors with your $US48MM Series C unicorn horn on your way to billionaire mountain.
  4. Using Google Cloud Platform for Security Scanning (Google Online Security) — platform vendors competing on the things they can offer for free on the base platform, things which devs and ops used to have to do themselves.
Four short links: 19 February 2015

Four short links: 19 February 2015

Magical Interfaces, Automation Tax, Cyber Manhattan Project, and US Chief Data Scientist

by Nat Torkington | @gnat | +Nat Torkington | February 19, 2015
  1. MAS S66: Indistinguishable From… Magic as Interface, Technology, and Tradition — MIT course taught by Greg Borenstein and Dan Novy. Further, magic is one of the central metaphors people use to understand the technology we build. From install wizards to voice commands and background daemons, the cultural tropes of magic permeate user interface design. Understanding the traditions and vocabularies behind these tropes can help us produce interfaces that use magic to empower users rather than merely obscuring their function. With a focus on the creation of functional prototypes and practicing real magical crafts, this class combines theatrical illusion, game design, sleight of hand, machine learning, camouflage, and neuroscience to explore how ideas from ancient magic and modern stage illusion can inform cutting edge technology.
  2. Maybe We Need an Automation Tax (RoboHub) — rather than saying “automation is bad,” move on to “how do we help those displaced by automation to retrain?”.
  3. America’s Cyber-Manhattan Project (Wired) — America already has a computer security Manhattan Project. We’ve had it since at least 2001. Like the original, it has been highly classified, spawned huge technological advances in secret, and drawn some of the best minds in the country. We didn’t recognize it before because the project is not aimed at defense, as advocates hoped. Instead, like the original, America’s cyber Manhattan Project is purely offensive. The difference between policemen and soldiers is that one serves justice and the other merely victory.
  4. White House Names DJ Patil First US Chief Data Scientist (Wired) — There is arguably no one better suited to help the country better embrace the relatively new discipline of data science than Patil.
Four short links: 9 February 2015

Four short links: 9 February 2015

iBeacon at Scale, Product Teams, Progress Bars, and Distributed Fallacies

by Nat Torkington | @gnat | +Nat Torkington | February 9, 2015
  1. The Realities of Installing iBeacon at Scale (Brooklyn Museum) — death by a thousand mundane little real-world pains.
  2. How We Build Software (Intercom) — rare to see descriptions of how to build product teams.
  3. MProgress.js — Material Design progress bars for the web.
  4. Eight Fallacies of Distributed Computing — your network is unreliable, slow, congested, insecure, changing, expensive, and inconsistent. And that’s on a good day.