At the last Performance Firestarters on The Power of Feeds at Google, our speakers talked about the use of client and third party APIs and data feeds to dynamically update advertising messaging (beyond pricing and stock levels) to add new levels of contextual relevance (location, behaviour, weather, exposure to other media and so on).
It was a fascinating session and it seems that we're only scratching the surface of where this might go. Visar Shabi, CTO at the super-smart BrainLabs, spoke about applying a layer of machine learning (or even utilising prediction APIs) to the input of data so that we might develop a model that continuously updates itself. Alistair Dent of iProspect talked about how APIs bring scalability and speed to managing real-time changes in communications, and all the different ways in which we might use structured data to do this in better ways. Kris Tait of digital agency Croud (who themselves have a really interesting operating model) spoke of how they had used data feeds to dynamically update advertising messages for their client Netflix, making 297,000 changes over a six month period (the equivalent of 50,000 changes a month).
Kris also described the process of using feeds as being one of augmenting human capability. In doing so he mentioned a really interesting delineation between AI (Artificial Intelligence) and IA (Intelligence Augmentation, or Amplification), which led me to this recent Andreessen Horowitz podcast (embedded above) featuring the NYT's John Markoff who's just written a book, Machines of Loving Grace, about the increasingly complex relationship between humans and machines.
In the interview Markoff talks about how two communities had grown up in Silicon Valley - one focused on Artificial Intelligence and how technology might replicate or replace humans, and the other all about how technology might augment human capability. He talks about the McLuhanism of how we shape our tools and then our tools shape us (but we do shape our tools), why we'll end up talking to machines but not just through a conversational UI, whether robots really will replace human jobs, what’s really happening with Moore’s Law, and why we’re not seeing an equivalent Moore’s Law-type impact on productivity growth. A useful distinction and a fascinating listen.
