Business models that make the Internet of Things feasible

The bid for widespread home use may drive technical improvements.

For some people, it’s too early to plan mass consumerization of the Internet of Things. Developers are contentedly tinkering with Arduinos and clip cables, demonstrating cool one-off applications. We know that home automation can save energy, keep the elderly and disabled independent, and make life better for a lot of people. But no one seems sure how to realize this goal, outside of security systems and a few high-end items for luxury markets (like the Nest devices, now being integrated into Google’s grand plan).

But what if the willful creation of a mass consumer market could make the technology even better? Perhaps the Internet of Things needs a consumer focus to achieve its potential. This view was illuminated for me through a couple recent talks with Mike Harris, CEO of the home automation software platform Zonoff.

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Four short links: 9 April 2014

Four short links: 9 April 2014

Internet of Listeners, Mobile Deep Belief, Crowdsourced Spectrum Data, and Quantum Minecraft

  1. Jasper Projectan open source platform for developing always-on, voice-controlled applications. Shouting is the new swiping—I eagerly await Gartner touting the Internet-of-things-that-misunderstand-you.
  2. DeepBeliefSDK — deep neural network library for iOS. (via Pete Warden)
  3. Microsoft Spectrum Observatory — crowdsourcing spectrum utilisation information. Just open sourced their code.
  4. qcraft — beginner’s guide to quantum physics in Minecraft. (via Nelson Minar)
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The backlash against big data, continued

Ignore the hype. Learn to be a data skeptic.

Yawn. Yet another article trashing “big data,” this time an op-ed in the Times. This one is better than most, and ends with the truism that data isn’t a silver bullet. It certainly isn’t.

I’ll spare you all the links (most of which are much less insightful than the Times piece), but the backlash against “big data” is clearly in full swing. I wrote about this more than a year ago, in my piece on data skepticism: data is heading into the trough of a hype curve, driven by overly aggressive marketing, promises that can’t be kept, and spurious claims that, if you have enough data, correlation is as good as causation. It isn’t; it never was; it never will be. The paradox of data is that the more data you have, the more spurious correlations will show up. Good data scientists understand that. Poor ones don’t.

It’s very easy to say that “big data is dead” while you’re using Google Maps to navigate downtown Boston. It’s easy to say that “big data is dead” while Google Now or Siri is telling you that you need to leave 20 minutes early for an appointment because of traffic. And it’s easy to say that “big data is dead” while you’re using Google, or Bing, or DuckDuckGo to find material to help you write an article claiming that big data is dead. Read more…

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Four short links: 8 April 2014

Four short links: 8 April 2014

Our Robot Future, Embeddable Pi, Behavioural Economics Not Solved Problem, and Imagine Processing Language

  1. Next Five Years for Robots — plausible summary of the near future progression, taken from Helen Greiner’s DEMOlabs talk.
  2. Raspberry Pi Compute Modulea Raspberry Pi shrunk down to fit on a SODIMM with onboard memory, whose connectors you can customise for your own needs. (via Makezine)
  3. Behavioural Economics and Public Policy (Financial Times) — interesting how A/B trials revealed that implementations of Cialdini’s social proof didn’t test as well as non-social-proof persuasive techniques. More useful than something that claims to be the right answer is knowing when you’re closer to the right answer. (via Mind Hacks)
  4. Halide Language — open source programming language designed to make it easier to write high-performance image processing code on modern machines. Its current front end is embedded in C++. Compiler targets include x86/SSE, ARM v7/NEON, CUDA, Native Client, and OpenCL.
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Podcast: Personalizing hardware with data? Personalizing people with CRISPR?

Jim Stogdill, Jon Bruner, and Mike Loukides chat about personalizing all the things.

This week in our Radar podcast, Jon and I both had colds. You’ll be pleased to know that I edited out all the sneezes, coughs, and general upper respiratory mayhem, but unfortunately there is no Audacity filter for a voice that sounds like a frog caught in a mouse trap (mine). If that hasn’t dissuaded you from listening, we covered some things that were really interesting, at least to us.

Here are some links to things you’ll hear in this episode:

Are you a microphone geek? You’re welcome. Jon is a maximizer, I’m a satisfier. Mike remains indeterminate.

Blackberry’s salvation may reside in its QNX embedded systems division.

The Pennsylvania Railroad was an amazing technical organization in its heyday. Railroads were that time’s web, and Pennsylvania was its Google. It created a lot of the practices we still use today for testing and other technical disciplines. Also, I suppose if Atlas were to shrug today (shudder) John Galt would be a data center designer. Read more…

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Advances in health IT must be viewed as a whole

New report ties together devices, data, records, and aspects of care.

Reformers in health care claim gigantic disruption on the horizon: devices that track our movements, new treatments through massive data crunching, fluid electronic records that reflect the patient’s status wherever she goes, and even the end of the doctor’s role. But predictions in the area of health IT are singularly detached from the realities of the technical environment that are supposed to make them happen.

To help technologists, clinicians, and the rest of us judge the state of health IT, I’ve released a report titled “The Information Technology Fix for Health: Barriers and Pathways to the Use of Information Technology for Better Health Care.” It offers an overview of each area of innovation to see what’s really happening and what we need to make it progress further and faster.

Read more…

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