Le Web 2012 presentation - Dalton Caldwell

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The Internet of Things: Signal, Noise, & Business Models

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Le Web 2012 presentation - Dalton Caldwell

  1. 1. The Internet of Things: Signal, Noise, & Business Models Dalton Caldwell Founder/CEO App.net
  2. 2. Good news!• The “The Internet of Things”-era has begun• Polished, useful IoT products released daily• Amount of information sensed/stored by IoT will increase exponentially
  3. 3. (Some) bad news.• IoT is going to make things a lot “noisier”• Making sense of the noise is harder than building the machines which create it• Think your email inbox and social feeds are overwhelming? Just wait. • ie how much data will Google Glasses generate?
  4. 4. What can be learn fromrunning a server farm?• Event notifications must follow Goldilocks principle: all the way on or off is bad• What do you do with 10TB of logfiles?• How manageable are SMS/Email alerts from: 1 server? 10 servers? 100 servers? 1000 servers?
  5. 5. Noise management on the social web• Think about services that auto-tweet or post Open Graph actions • Watching a video, reading an article, listening to a song... these actions generate noise• How are consumers supposed to manage this? • On an unfiltered stream: unfollow the person, or ask them to stop posting so much “spam” • On a filtered stream: let the algorithm do the work for you, also you can give the algorithm hints
  6. 6. Filtered Streams vs Unfiltered Streams• Consuming an unfiltered stream is increasingly difficult... human limits on information consumption• Algorithmically filtered streams make arbitrarily large amounts of input data feel manageable• FB newsfeed: a great filtered stream implementation • Surfaces important events • Eliminates redundancy • Optimizes on time and engagement metrics
  7. 7. How will people manage their personal IoT?• Raw IoT data is specialized, but event/alert notifications will likely utilize: • Email, SMS or Social streams• A stream is especially useful because it allows sophisticated noise filtering
  8. 8. Some business model challenges...• If you are an advertising-supported stream company, you there is a good chance you: • Don’t want 3rd-party UIs displaying the stream • Don’t want 3rd-party filtering algorithms • Don’t want your “content” leaking out • Don’t want to host home automation-type data(?) • Optimize for user engagement on your stream, not utility. Those are not the same thing.
  9. 9. What if we ignored those business model limits?• Unbundle the stream. • Pluggable APIs which write to unified stream • Pluggable filters of unified stream • Pluggable UIs + methods of stream consumption• Ownership/exportability of all data
  10. 10. Examples of existing unbundled services• Unbundled read/write APIs? IFTTT• Unbundled UIs? 3rd-party Twitter clients• Unbundled stream filters? Flipboard• (Worth noting these examples have all faced recent “platform risk” setbacks)
  11. 11. App.net: Built to be unbundled• Pluggable APIs? Nearly 100 apps in the directory, dozens of available libraries/ programming languages• Pluggable filters? 3rd party notification frameworks and threshold filters.• Pluggable UIs? ~90% of usage already occurs in 3rd party UI, exactly as intended• Users own data. Data export since day 1.
  12. 12. App.net private messages API• Person will be able to use their account to create a private, unbundled stream• A single paid account can be written to from any number of endpoints, including IoT• The stream can be filtered/consumed in any way 3rd party devs can dream up• App.net’s paid, “services” business model supports this kind of use-case
  13. 13. Wrapping up...• Digital information is already overwhelming, but IoT will make this far problem far worse• Making data useful: more important than collection• Existing unified streams have business models which discourage unbundling of filter components• “Unbundling the stream” allows focused innovation in UIs, filters, and notification frameworks

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