A gaggle of Harry Potter fans descended for several days this summer on the Oregon Convention Center in Portland for the Leaky Con gathering, an annual haunt of a group of predominantly young women who immerse themselves in a fantasy world of magic, spells and images.
The jubilant and occasionally squealing attendees appeared to have no idea that next door a group of real-world wizards was demonstrating technology that only a few years ago might have seemed as magical.
The scientists and engineers at the Computer Vision and Pattern Recognition conference are creating a world in which cars drive themselves, machines recognize people and "understand" their emotions, and humanoid robots travel unattended, performing everything from mundane factory tasks to emergency rescues.
C.V.P.R., as it is known, is an annual gathering of computer vision scientists, students, roboticists, software hackers -- and increasingly in recent years, business and entrepreneurial types looking for another great technological leap forward.
The growing power of computer vision is a crucial first step for the next generation of computing, robotic and artificial intelligence systems. Once machines can identify objects and understand their environments, they can be freed to move around in the world. And once robots become mobile they will be increasingly capable of extending the reach of humans or replacing them.
Self-driving cars, factory robots and a new class of farm hands known as ag-robots are already demonstrating what increasingly mobile machines can do. Indeed, the rapid advance of computer vision is just one of a set of artificial intelligence-oriented technologies -- others include speech recognition, dexterous manipulation and navigation -- that underscore a sea change beyond personal computing and the Internet, the technologies that have defined the last three decades of the computing world.
"During the next decade we're going to see smarts put into everything," said Ed Lazowska, a computer scientist at the University of Washington who is a specialist in Big Data. "Smart homes, smart cars, smart health, smart robots, smart science, smart crowds and smart computer-human interactions."
The enormous amount of data being generated by inexpensive sensors has been a significant factor in altering the center of gravity of the computing world, he said, making it possible to use centralized computers in data centers -- referred to as the cloud -- to take artificial intelligence technologies like machine-learning and spread computer intelligence far beyond desktop computers.
Apple was the most successful early innovator in popularizing what is today described as ubiquitous computing. The idea, first proposed by Mark Weiser, a computer scientist with Xerox, involves embedding powerful microprocessor chips in everyday objects.
Steve Jobs, during his second tenure at Apple, was quick to understand the implications of the falling cost of computer intelligence. Taking advantage of it, he first created a digital music player, the iPod, and then transformed mobile communication with the iPhone. Now such innovation is rapidly accelerating into all consumer products.
"The most important new computer maker in Silicon Valley isn't a computer maker at all, it's Tesla," the electric car manufacturer, said Paul Saffo, a managing director at Discern Analytics, a research firm based in San Francisco. "The car has become a node in the network and a computer in its own right. It's a primitive robot that wraps around you."
Here are several areas in which next-generation computing systems and more powerful software algorithms could transform the world in the next half-decade.
With increasing frequency, the voice on the other end of the line is a computer.
It has been two years since Watson, the artificial intelligence program created by I.B.M., beat two of the world's best "Jeopardy" players. Watson, which has access to roughly 200 million pages of information, is able to understand natural language queries and answer questions.
The computer maker had initially planned to test the system as an expert adviser to doctors; the idea was that Watson's encyclopedic knowledge of medical conditions could aid a human expert in diagnosing illnesses, as well as contributing computer expertise elsewhere in medicine.
In May, however, I.B.M. went a significant step farther by announcing a general-purpose version of its software, the "I.B.M. Watson Engagement Advisor." The idea is to make the company's question-answering system available in a wide range of call center, technical support and telephone sales applications. The company says that as many as 61 percent of all telephone support calls currently fail because human support-center employees are unable to give people correct or complete information.
Watson, I.B.M. says, will be used to help human operators, but the system can also be used in a "self-service" mode, in which customers can interact directly with the program by typing questions in a Web browser or by speaking to a speech recognition program.
That suggests a "Freakonomics" outcome: There is already evidence that call-center operations that were once outsourced to India and the Philippines have come back to the United States, not as jobs, but in the form of software running in data centers.
A race is under way to build robots that can walk, open doors, climb ladders and generally replace humans in hazardous situations.
In December, the Defense Advanced Research Projects Agency, or Darpa, the Pentagon's advanced research arm, will hold the first of two events in a $2 million contest to build a robot that could take the place of rescue workers in hazardous environments, like the site of the damaged Fukushima Daiichi nuclear plant.
Scheduled to be held in Miami, the contest will involve robots that compete at tasks as diverse as driving vehicles, traversing rubble fields, using power tools, throwing switches and closing valves.
In addition to the Darpa robots, a wave of intelligent machines for the workplace is coming from Rethink Robots, based in Boston, and Universal Robots, based in Copenhagen, which have begun selling lower-cost two-armed robots to act as factory helpers. Neither company's robots have legs, or even wheels, yet. But they are the first commercially available robots that do not require cages, because they are able to watch and even feel their human co-workers, so as not to harm them.
For the home, companies are designing robots that are more sophisticated than today's vacuum-cleaner robots. Hoaloha Robotics, founded by the former Microsoft executive Tandy Trower, recently said it planned to build robots for elder care, an idea that, if successful, might make it possible for more of the aging population to live independently.
Seven entrants in the Darpa contest will be based on the imposing humanoid-shaped Atlas robot manufactured by Boston Dynamics, a research company based in Waltham, Massachusetts. Among the wide range of other entrants are some that look anything but humanoid -- with a few that function like "transformers" from the world of cinema. The contest, to be held in the infield of the Homestead-Miami Speedway, may well have the flavor of the bar scene in "Star Wars."
Amnon Shashua, an Israeli computer scientist, has modified his Audi A7 by adding a camera and artificial-intelligence software, enabling the car to drive the 65 kilometers, or 40 miles, between Jerusalem and Tel Aviv without his having to touch the steering wheel.
In 2004, Darpa held the first of a series of "Grand Challenges" intended to spark interest in developing self-driving cars. The contests led to significant technology advances, including "Traffic Jam Assist" for slow-speed highway driving; "Super Cruise" for automated freeway driving, already demonstrated by General Motors and others; and self-parking, a feature already available from a number of car manufacturers.
Recently General Motors and Nissan have said they will introduce completely autonomous cars by the end of the decade. In a blend of artificial-intelligence software and robotics, Mobileye, a small Israeli manufacturer of camera technology for automotive safety that was founded by Mr. Shashua, has made considerable progress. While Google and automotive manufacturers have used a variety of sensors including radars, cameras and lasers, fusing the data to provide a detailed map of the rapidly changing world surround a moving car, Mobileye researchers are attempting to match that accuracy with just video cameras and specialized software.
At a preschool near the University of California, San Diego, a child-size robot named Rubi plays with children. It listens to them, speaks to them and understands their facial expressions.
Rubi is an experimental project of Prof. Javier Movellan, a specialist in machine learning and robotics. Professor Movellan is one of a number of researchers now working on a class of computers that can interact with humans, including holding conversations.
Computers that understand our deepest emotions hold the promise of a world full of brilliant machines. They also raise the specter of an invasion of privacy on a scale not previously possible, as they move a step beyond recognizing human faces to the ability to watch the array of muscles in the face and decode the thousands of possible movements into an understanding of what people are thinking and feeling.
These developments are based on the work of the American psychologist Paul Ekman, who explored the relationship between human emotion and facial expression. His research found the existence of "micro expressions" that expose difficult-to-suppress authentic reactions. In San Diego, Professor Movellan has founded a company, Emotient, that is one of a handful of start-ups pursuing applications for the technology. A near-term use is in machines that can tell when people are laughing, crying or skeptical -- a survey tool for film and television audiences.
Farther down the road, it is likely that applications will know exactly how people are reacting as the conversation progresses, a step well beyond Siri, Apple's voice recognition system.
Harry Potter fans, stand by.
This article originally appeared in The New York Times. First Published October 15, 2013 2:00 PM