 the future will enable artificial intelligence. Although the terms are often used interchangeably, there is a difference between machine learning and artificial intelligence. Machine learning uses microchips to compare stored images to new images to detect anomalies and patterns of data. It can be thought of as computerized pattern detection in existing data and identification of similar patterns in future data. Microchips compare billions of images and phrases and words to find anomalies and to perform tasks formerly done by people. For example, graphic processing units (GPUs) chips are able to process and store complex mathematical algorithms that represent images. Google is training its machine learning system to recognize a picture with a car in it. The machine learning system is shown a large number of pictures with a car in it. Telling the system if there is a car in the picture or not enables the computer to later recognize the visual qualities associated with cars. Machine learning is also used in facial recognition software used by police departments. Artificial intelligence solves problems by using reasoning, logical deduction, searching, and trial and error. Artificial intelligence has the ability to imitate a human brain's functions. Although media articles claim that certain applications and cloud computing services use artificial intelligence, they are actually powered by machine learning. Artificial intelligence applications that mimic human intelligence are not currently available. The following are examples of machine learning: Mass General Hospital in Boston's radiology department is planning to use Nvidia's graphical processing units on chips to analyze a library of 10 billion x-rays, CT scans, and MRI images that will be compared with new images to identify images indicating the presence of cancer and Alzheimer's. Medical applications analyze large amounts information in medical journals and textbooks to assist physicians in making a diagnosis. www.TechnicalPDF.com In the future, self-driving