Last October, a robot car designed by a team of Stanford engineers covered 132 miles of desert road without human intervention to capture a $2 million prize offered by the Defense Advanced Research Projects Agency, part of the Pentagon. The feat was particularly striking because 18 months earlier, during the first such competition, the best vehicle got no farther than seven miles, becoming stuck after driving off a mountain road.
Now the Pentagon agency has upped the ante: Next year the robots will be back on the road, this time in a simulated traffic setting. It is being called the “urban challenge.”
At Microsoft, researchers are working on the idea of “predestination.” They envision a software program that guesses where you are traveling based on previous trips, and then offers information that might be useful based on where the software thinks you are going.
Tellme Networks, a company in Mountain View, Calif., that provides voice recognition services for both customer service and telephone directory applications, is a good indicator of the progress that is being made in relatively constrained situations, like looking up a phone number or transferring a call.
Tellme supplies the system that automates directory information for toll-free business listings. When the service was first introduced in 2001, it could correctly answer fewer than 37 percent of phone calls without a human operator’s help. As the system has been constantly refined, the figure has now risen to 74 percent.
More striking advances are likely to come from new biological models of the brain. Researchers at the École Polytechnique Fédérale de Lausanne in Lausanne, Switzerland, are building large-scale computer models to study how the brain works; they have used an I.B.M. parallel supercomputer to create the most detailed three-dimensional model to date of a column of 10,000 neurons in the neocortex.
“The goal of my lab in the past 10 to 12 years has been to go inside these little columns and try to figure out how they are built with exquisite detail,” said Henry Markram, a research scientist who is head of the Blue Brain project. “You can really now zoom in on single cells and watch the electrical activity emerging.”
Blue Brain researchers say they believe the simulation will provide fundamental insights that can be applied by scientists who are trying to simulate brain functions.
Do you think your high-paid managers really know best? A Dutch sociology professor has doubts.
The professor, Chris Snijders of the Eindhoven University of Technology, has been studying the routine decisions that managers make, and is convinced that computer models, by and large, can do a better job of it. He even issued a challenge late last year to any company willing to pit its humans against his algorithms.
“As long as you have some history and some quantifiable data from past experiences,” Mr. Snijders claims, a simple formula will soon outperform a professional’s decision-making skills. “It’s not just pie in the sky,” he said. “I have the data to support this.”
Some of Mr. Snijders’s experiments from the last two years have looked at the results that purchasing managers at more than 300 organizations got when they placed orders for computer equipment and software. Computer models given the same tasks achieved better results in categories like timeliness of delivery, adherence to the budget and accuracy of specifications.
No company has directly taken Mr. Snijders up on his challenge. But a Dutch insurer, Interpolis, whose legal aid department has been expanding rapidly in recent years, called in Mr. Snijders to evaluate a computer model it had designed to automate the routing of new cases — a job previously handled manually by the department’s in-house legal staff.
The manager in charge of the project, Ludo Smulders, said the model was much faster and more accurate than the old system. “We’re very satisfied about the results it’s given our organization,” he said. “That doesn’t mean there are no daily problems, but the problems are much smaller than when the humans did it by hand. And it lets them concentrate more on giving legal advice, which is what their job is.”
Mr. Snijders’s work builds on something researchers have known for decades: that mathematical models generally make more accurate predictions than humans do. Studies have shown that models can better predict, for example, the success or failure of a business start-up, the likelihood of recidivism and parole violation, and future performance in graduate school.
They also trump humans at making various medical diagnoses, picking the winning dogs at the racetrack and competing in online auctions. Computer-based decision-making has also grown increasingly popular in credit scoring, the insurance industry and some corners of Wall Street.
The main reason for computers’ edge is their consistency — or rather humans’ inconsistency — in applying their knowledge.
The summary: computers will eventually be better at everything, they’ll take over all our jobs, completely automise our economy and we will be living in robot nation.