Marvin Minsky has long been one of the great human intelligences working in the field of artificial intelligence (AI). A professor at MIT, where he has worked since 1957 and cofounded the AI laboratory in 1959, Minsky is also an inventor, philosopher, and author. In recent years, Minsky has focused his formidable talents on trying to impart the human capacity for commonsense reasoning to machines. In this interview, conducted on November 3, 2010 by "Smartest Machine on Earth" producer Michael Bicks, hear Minsky's take on why it's important to recreate human intelligence, what a five-year-old can do that even the smartest machine cannot, and whether someone will ever invent a computer that laughs at Seinfeld. Marvin Minsky says that when it comes to designing a smart machine, "you mustn't look for a magic bullet"--that is, just a single way to solve all problems.

Nick Annetta, right, of Battelle, watches as Ian Burkhart, 24, plays a guitar video game using his paralyzed hand. A computer chip in Burkhart s brain reads his thoughts, decodes them, then sends signals to a sleeve on his arm, that allows him to move his hand. Six years ago, while swimming in the ocean surf, 24-year-old Ian Burkhart lost the ability to control his hands and legs. He dove under the surf, and the waves shoved him into a sandbar. But today, thanks to a computer chip implanted into the motor cortex of his brain that decodes his brain activity, he can move his fingers again.

A 25-year-old book about science has some explaining to do. Machines Who Think was conceived as a history of artificial intelligence, beginning with the first dreams of the classical Greek poets (and the nightmares of the Hebrew prophets), up through its realization as twentieth-century science. The interviews with AI's pioneer scientists took place when the field was young and generally unknown. They were nearly all in robust middle age, with a few decades of fertile research behind them, and luckily, more to come. Thus their explanations of what they thought they were doing were spontaneous, provisional, and often full of glorious fun.

Neil Heffernan was listening to his fiancée, Cristina Lindquist, tutor one of her students in mathematics when he had an idea. Heffernan was a graduate student in computer science, and by this point -- the summer of 1997 -- he had been working for two years with researchers at Carnegie Mellon University on developing computer software to help students improve their skills. But he had come to believe that the programs did little to assist their users. They were built on elaborate theories of the student mind -- attempts to simulate the learning brain. Then it dawned on him: what was missing from the programs was the interventions teachers made to promote and accelerate learning.

A free online course at Stanford University on artificial intelligence, to be taught this fall by two leading experts from Silicon Valley, has attracted more than 58,000 students around the globe -- a class nearly four times the size of Stanford's entire student body. The course is one of three being offered experimentally by the Stanford computer science department to extend technology knowledge and skills beyond this elite campus to the entire world, the university is announcing on Tuesday. The online students will not get Stanford grades or credit, but they will be ranked in comparison to the work of other online students and will receive a "statement of accomplishment." For the artificial intelligence course, students may need some higher math, like linear algebra and probability theory, but there are no restrictions to online participation. So far, the age range is from high school to retirees, and the course has attracted interest from more than 175 countries.

David E. Rumelhart, whose computer simulations of perception gave scientists some of the first testable models of neural processing and proved helpful in the development of machine learning and artificial intelligence, died Sunday in Chelsea, Mich. The cause was complications of Pick's disease, an Alzheimer's-like disorder from which he had suffered for more than a decade, his son Karl said. When Dr. Rumelhart, a psychologist, began thinking in the 1960s about how neurons process information, the field was split into two camps that had little common language: biologists, who focused on neurons and brain tissue; and cognitive psychologists, who studied far more abstract processes, like reasoning skills and learning strategies. By starting small -- showing, for instance, that the brain's ability to recognize a single letter was greatly influenced by the letters around it -- Dr. Rumelhart and his colleague Jay McClelland, around 1980, built computer programs that roughly simulated perception. Later, he devised an algorithm that allowed computer programs to learn how to perceive.

Oliver G. Selfridge, an innovator in early computer science and artificial intelligence, died on Wednesday in Boston. The cause was injuries suffered in a fall on Sunday at his home in nearby Belmont, Mass., said his companion, Edwina L. Rissland. Credited with coining the term "intelligent agents," for software programs capable of observing and responding to changes in their environment, Mr. Selfridge theorized about far more, including devices that would not only automate certain tasks but also learn through practice how to perform them better, faster and more cheaply. Eventually, he said, machines would be able to analyze operator instructions to discern not just what users requested but what they actually wanted to occur, not always the same thing. His 1958 paper "Pandemonium: A Paradigm for Learning," which proposed a collection of small components dubbed "demons" that together would allow machines to recognize patterns, was a landmark contribution to the emerging science of machine learning.

Dr. Saul Amarel, who helped develop the field of artificial intelligence and founded the computer science department at Rutgers University, died on Wednesday in Princeton, N.J., where he lived. The cause was complications of cancer, according to Rutgers. At Rutgers, Dr. Amarel developed computer time-sharing, and his laboratory became an early node on Arpanet, the precursor to the Internet. He took a leave in the 1980's to spend a few years directing a computer science program at the Pentagon, and returned to Rutgers in 1988. Among his peers, Dr. Amarel was perhaps best known for a paper he wrote in 1968, which put him at the vanguard of the artificial intelligence movement.

EARLY in the film ''A Beautiful Mind,'' the mathematician John Nash is seen sitting in a Princeton courtyard, hunched over a playing board covered with small black and white pieces that look like pebbles. He was playing Go, an ancient Asian game. Frustration at losing that game inspired the real Mr. Nash to pursue the mathematics of game theory, research for which he eventually won a Nobel Prize. In recent years, computer experts, particularly those specializing in artificial intelligence, have felt the same fascination -- and frustration. Programming other board games has been a relative snap.

The test is still experimental, unavailable to the public outside of clinical trials. Its developers say it needs further study in many more women to determine whether the early findings hold up. If it does come to market, it will not be for several years, and its use might initially be limited to women at high risk. Dr. Emanuel F. Petricoin, who helped create the test, said, ''I'm all too aware as an F.D.A. scientist of promising early results that start to fail as you go into the real world.'' Ovarian cancer is not common, but it is often deadly.