The Quest for Meaning (continued)
The next generation of Autonomy software - embedded in intranet sites - creates a single interface for Oracle databases and legacy mainframe resources, archived email and Lotus Notes, Excel spreadsheets, and Word files. By partnering with young companies, such as Corechange, Intraspect Software, Verge Software, Provenance Systems, and Hyperwave Information Management, that make so-called middle-office software to build intranet portals, Autonomy is aiming to become the language lobe in the evolving big brain of the modern corporation. In making tools that learn more about you the more you use them, Autonomy is also riding the wave of personal profiling and customization that could someday take the place of the traditional service industry.
Autonomy is just one of the companies putting Bayes' rule to use in ways its creator couldn't have imagined. The reverend is hard at work in Microsoft Office's wizards, which anticipate your needs by observing behaviors such as cursor movements and hesitations. The theorem also plays a role in the troubleshooting areas on Microsoft.com, where Bayesian methods of diagnosing user problems save the company hundreds of millions of dollars a year in service calls, says Eric Horvitz, one of 25 Bayesian specialists who work with Microsoft's product teams.
One of the most promising uses of these strategies, predicts Horvitz, will be in the development of what Microsoft calls continual computation. Anticipating a user's next move could cut the time spent launching frequently used apps. Likewise, your browser could pre-fetch potentially interesting pages and cache them for you in the background.
In Redmond, there's a prototype running on a desktop computer christened the Bayesian Receptionist. Using a voice interface rather than text, the Bayesian Receptionist greets visitors to the Conversational Architectures Group and answers questions as needed. Horvitz points out that the particular strength of Bayesian approaches - making accurate guesses under conditions of uncertainty - is especially relevant for interfaces that converse, because they have to depend on constant renegotiation of the subject at hand, following the flow of spontaneous exchange while navigating through topic hierarchies. "Uncertainty about communication is at the heart of conversation," Horvitz observes.
He believes the smart objects of the future will inevitably carry a piece of Bayes' legacy: "Data from Star Trek? He'll be Bayesian."
When he's not helping build the Bayesian future, Michael Lynch lives in a village outside Cambridge that's so small - population 120 - he asks me not to name it in print. Many houses in the area are covered with corn-thatch roofs in the ancient style, and the older residents pray in churches with stone towers built to keep watch for Viking raiders. The locals all ask after Lynch's beloved otter hound, Gromit, named for Nick Park's animated clay canine. Standing in a garden, watching red chickens peck under the hedges, you wouldn't know which century you had arrived in. Bayes' Tunbridge Wells must have been something like this, seemingly thousands of miles away from the "dark satanic mills" that appalled Blake at the dawn of the Industrial Revolution.
When Lynch bought his house three years ago, he dug a koi pond where a rubbish dump had been. In winter, he boils kettles of water to make holes in the ice so the fish can have more oxygen while they hibernate. He stocked the pond with fish he bought at a pet store, but in just a few weeks, wild carp appeared, swimming among the ones he'd placed there. Lynch thinks they may have come in as eggs clinging to the legs of migrating herons.
"It's amazing how absolutely pervasive life is, given half a chance," he observes. "You dig a pool of water, you leave a patch of earth, something will grow there."
Lynch sees the marriage of Bayes' ideas and modern processing power as characteristic of a new, more mature phase of technology - an era in which humanity will no longer believe it's standing at the center of the universe.
"Rules-based, Boolean computing assumes that we know best how to solve a problem," he says. "My background comes completely the other way. The problem tells you how to solve the problem. That's what the next generation of computing is going to be about: listening to the world."
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