The complexity of artificial intelligence

IMAGE: SMU Assistant Professor Sun Qianru says highly diverse training data is critical to ensure the machine sees a wide range of examples and counterexamples that cancel out spurious patterns. SMU Office of Research and Tech Transfer - Artificial Intelligence, or AI, makes us look better in selfies, obediently tells us the weather when we ask Alexa for it, and rolls out self-drive cars. It is the technology that enables machines to learn from experience and perform human-like tasks. As a whole, AI contains many subfields, including natural language processing, computer vision, and deep learning. Most of the time, the specific technology at work is machine learning, which focuses on the development of algorithms that analyses data and makes predictions, and relies heavily on human supervision.