There's an urban legend about the early days of machine vision, the subfield of artificial intelligence (AI) concerned with teaching machines to detect and interpret images. In 1966, Marvin Minsky was a young professor at MIT, making a name for himself in the emerging field of artificial intelligence.[1] Deciding that the ability to interpret images was a core feature of intelligence, Minsky turned to an undergraduate student, Gerald Sussman, and asked him to "spend the summer linking a camera to a computer and getting the computer to describe what it saw."[2] This became the Summer Vision Project.[3] Needless to say, the project of getting computers to "see" was much harder than anyone expected, and would take a lot longer than a single summer.

The new system, described in a study published in JAMA Network Open, helps interpret medical images used to diagnose breast cancer that can be difficult for the human eye to classify, and it does so nearly as accurately or better as experienced pathologists. "It is critical to get a correct diagnosis from the beginning so that we can guide patients to the most effective treatments," said Dr. Joann Elmore, the study's senior author and a professor of medicine at the David Geffen School of Medicine at UCLA. A 2015 study led by Elmore found that pathologists often disagree on the interpretation of breast biopsies, which are performed on millions of women each year. That earlier research revealed that diagnostic errors occurred in about one out of every six women who had ductal carcinoma in situ (a noninvasive type of breast cancer), and that incorrect diagnoses were given in about half of the biopsy cases of breast atypia (abnormal cells that are associated with a higher risk for breast cancer). "Medical images of breast biopsies contain a great deal of complex data and interpreting them can be very subjective," said Elmore, who is also a researcher at the UCLA Jonsson Comprehensive Cancer Center.

The Food and Drug Administration has approved the first artificial intelligence software that can decide, without a clinician's involvement, whether a patient might have a certain disease, the agency announced Wednesday. The software, called IDx-DR, looks for diabetic retinopathy, an eye disease that afflicts individuals with diabetes. With minimal training, health care providers can use a special camera to take a picture of the back of the patient's retina, which an algorithm then analyzes to look for the disease. If the software finds evidence of the disease, it recommends that a patient see an eye specialist. A computer program that can analyze medical images could save time and money, cutting down on unnecessary, expensive trips to specialists.

Like many kids, Antonio Torralba began playing around with computers when he was 13 years old. Unlike many of his friends, though, he was not playing video games, but writing his own artificial intelligence (AI) programs. Growing up on the island of Majorca, off the coast of Spain, Torralba spent his teenage years designing simple algorithms to recognize handwritten numbers, or to spot the verb and noun in a sentence. But he was perhaps most proud of a program that could show people how the night sky would look from a particular direction. Or you could move to another planet, and it would tell you how the stars would look from there, he says.