Cut-rate painkillers! Unclaimed riches in Nigeria!! Most of us quickly identify such e-mail messages as spam. But how would you teach that skill to a machine? David Heckerman needed to know. Early this decade, Heckerman was leading a spam-blocking team at Microsoft Research. To build their tool, team members meticulously mapped out thousands of signals that a message might be junk. An e-mail featuring "Viagra," for example, was a good bet to be spam--but things got complicated in a hurry.
Since then, the 50-year-old Heckerman and two colleagues have created their own biology niche at Microsoft, where they build HIV-detecting software. These are research tools to spot infected cells and correlate the viral mutations with the individual's genetic profile. Heckerman's team runs mountains of data through enormous clusters of 320 computers, operating in parallel. Thanks to smarter algorithms and more powerful machines, they're sifting through the data 480 times faster than a year ago. In June, the team released its first batch of tools for free on the Internet.
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