Jeff Jonas was one of seven IBM employees who today entered into the exclusive fraternity of IBM Fellows, the top honor the company bestows on technical experts. (In a company with more than 425,000 employees worldwide, there are only 77 active Fellows.) Jonas arrived at this pinnacle of achievement via a strange route: He dropped out of both high school and college; the first company he started went bankrupt; he has been homeless; and he has spent a lot of time in Las Vegas casinos.
I’ll explain those strange biographical details later. But, first, it’s important for you to understand that Jonas has a powerful vision of the future of data analytics that could transform the way people think about and use information. He calls it “sensemaking on streams.”
Every entity in the universe, whether it’s a person or an asteroid or a building, has a set of identifying characteristics that help us differentiate that entity from every other one. Entities are in motion, physically, and they’re changing in other ways. Their relationships to each other are shifting, as well. Every day, individuals and organizations are bombarded with many bits of disconnected information about entities. These days, because of the Internet, sensor networks, mobile communications and other technologies, we receive a huge volume of signals. Sometimes it seems like our heads will explode, right?
For the past 3 ½ years, Jonas and a small team at IBM have been developing a new software program, code-named G2, with a goal of making sense of all of this information, as it flows in, so we can act on it. “Every piece of data is a question. It’s like the piece of a puzzle,” he says. “As each piece comes in, we have to understand what it is and how it might fit into the puzzle.”
G2, an analytics engine, puts all the pieces of information in context of everything else we know that’s related. Each additional piece of information also changes the shape of the puzzle. This puzzle has no edges—only more pieces.
In the past, a lot of the puzzle pieces just fell in huge piles. We collected some and tried to organize them, or we didn’t even bother.
But now, G2 begins to make it possible to manage the flow of data and make sense of it—sizing things up and signaling what to do in about 200 milliseconds. “Data talks to itself,” Jonas says.
Jonas could have benefited from data talking to itself a couple of years ago. One of his charge card numbers was stolen without him realizing it. He doesn’t review his card bills closely, and, because the thief sneakily charged only a few hundred dollars per billing period, neither the card company nor Jonas knew what was up for several months. Finally, the card issuer spotted a suspicious anomaly and alerted him.
In the future, Jonas believes, G2 will prevent this sort of thing from happening. If individuals give their credit card companies permission to gather and compare bits of information about them and put the pieces in context, they’ll be able to know if a person is spending his or her money or somebody else is spending it. For instance, if Jonas’ Facebook page says he’s in Bucharest but somebody’s trying to buy jewelry at Tiffany’s in New York with his credit card, the transaction can be stopped before it goes through.
There are untold numbers of potential uses for G2, from banking and cybersecurity to logistics and public safety. Pieces of Jonas’ G2 vision will start to appear in IBM products before too long.
Now, concerning all the strange biographical details I mentioned at the top: You’ll have to wait for a future post.