For the closing keynote of this year's IDF, vice president and chief technology officer, Justin Rattner gave us a glimpse into Intel's vision for the future of computing.
Kicking things off he talked about the relationships we have with our devices. Currently they can do many things and do them very well - you can surf the web, see what your friends are doing, navigate to a new destinations, and record a video when you get there all from a single mobile device. However, said device seldom predicts what you're up to: it has no overarching intelligence. Thus the challenge of future devices is to make them not just simply tools but "assistants", said Rattner.
The key to this transition, he explained, is to not just rely on hard-sensing data but soft-sensing data as well. Hard-sensing data is what we normally think of when someone mentions sensing, it's GPS, it's accelarometers, it's temperature. All of which is essential to making a device aware of its surroundings. However, to make a device context aware it also needs to tap into the software data our devices also have access to. Stuff like calendar entries, your search history, and your music preferences. By adding the two together you get a device that can for instance, see that you have an appointment and send you alert fifteen minutes beforehand with information on which route to take to get there or tell you to go buy a present for your friends birthday in a couple of days time.
To demonstrate this sort of functoinality Rattner brought on Tim Jarrell, of travel company Fodor, who demonstrated a mobile device app the company had been working on. He showed how it could popup recommendations of sites to visit as you walk down the street based on your likes and dislikes. If you then fancied something to eat (without some internal body sensors it wasn't able to go so far as predicting when you'd be hungry) it would tell you not only what was nearby but filter the results based on your favourite food.
Extending the concept further we were next shown some new sensors. One measured the gait of a person, tracking the swing and stride time of the wearer. Aimed for use by the over 65's, by analysing your gait and picking out irregularities, it would be possible to sense the risk of elderly people falling. By being aware of this irregularity it would be possible to take preventative measures to improve the wearer's movement and hopefully prevent a potentially highly damaging fall.