Jeff Jonas on context computing, irresistible surveillance, and hunting astroids with Space Time Boxes
The O'Reilly Radar Podcast: Context-aware computing, privacy by design, and predicting astroid collisions.
O’Reilly’s Jenn Webb sits down with Jeff Jonas, an IBM fellow and chief scientist of context computing, Ironman triathlete, and contributing author to Privacy in the Modern Age: The Search for Solutions. Jonas talks about applications of context-aware computing, his new G2 software, and astroid hunting with astronomers at the University of Honolulu.
Here are a few highlights from our conversation:
The definition I’m using of context is this: to better understand something by taking into account the things around it. Context computing is taking a new piece of data that arrived in the enterprise as a puzzle piece and finding other pieces of data that had been previously seen and see how it fits. Instead of using algorithms staring at puzzle pieces, you end up with whole chunks of the puzzle and it’s much easier to make a high-quality prediction.
The purpose of G2 is to be able to take structured and unstructured data from batch or streaming sources. Think of it as new observations across a virtually unlimited number of data points. You could think of this as internet of things feeding it or transactional systems or social data or mobile data. It’s about weaving all those puzzle pieces together and then using the puzzle pieces as they land to figure out what’s important or not and use these system to help focus people’s attention.
There are 600,000 known asteroids, but none of them hit Earth. Now and then, they hit each other. It’s only been seen twice. The first time, about five years ago, the Hubble telescope just took a picture. In the middle of the picture is a giant X. It’s because two asteroids hit each other. Total accident; it was not predicted. I asked them, ‘Well, why didn’t you compute if the asteroids were going to hit each other?’ They said, ‘You silly fool. That’s multi-body orbit math, which means expensive, and it’s an N-squared problem, which means 10 million computer hours.’ I said, ‘But if you use these Space Time Boxes, you can figure out if they’re ever going to be near each other and then only use the heavy compute if they’re going to be near each other.’ We did a 25-year forecast, and now they’re pointing the telescopes at places in space and actually watching asteroids get close to each other.