In the background of image recognition software that can ID our friends on social media and wildflowers in our yard are neural networks, a type of artificial intelligence inspired by how own our brains process data.
While neural networks sprint through data, their architecture makes it difficult to trace the origin of errors that are obvious to humans—like confusing a Converse high-top with an ankle boot—limiting their use in more vital work like health care image analysis or research. A new tool developed at Purdue University makes finding those errors as simple as spotting mountaintops from an airplane.
