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AI is OK at recognizing simple images in isolation, but when asked to make sense of complex terrain—like a busy city intersection—it’s not so great. That’s a problem for self-driving car technology. So NYU researchers are working on an algorithm to help AI systems learn from their environment, inspired by how humans and animals process cluttered scenes. Their method, PooDLe, captures both foreground images (e.g., pedestrians crossing the street) and background images (distant cross streets) usin