Artificial Intelligence (AI) is the simulation of human intelligence by computing machines. This is accomplished by using technology to process information, recognize patterns and make decisions or predictions based on the information given. AI uses multiple sets of step-by-step instructions (algorithms) and abstract mathematical representations of systems and/or problems (mathematic models) to do this. To put it simply, AI is built on statistics and probability.
- AI uses statistics to recognize patterns
- Ai uses probability to predict outcomes
- AI uses statistics for accuracy
- AI uses probability for incomplete information
- AI uses statistics for correlation
- AI uses probability for causation
The history of AI begins with 'The Turing Test' developed by Alan Turing in 1949. Turing helped break the coding of the Enigma Machine, the secret code machine used by the Germans in World War 2. Turing's test pitted a machine against a human. Both would answer a set of questions based on a conversation and give those answers to a human judge. The judge would then try to identify the machine. The machine would pass if the judge couldn't reliably tell it apart from the human. The term 'artificial intelligence' was coined by John McCarthy in 1956 at Dartmouth University and is considered the birth of the field. AI research focused on symbolic reasoning and problem solving through the sixties. AI research dwindled during the seventies, but renewed interest in the eighties led to mimicking human learning, also known as machine learning. As the 21st century began, the cost of computing came down. Machines became faster and cheaper. Machine Learning hit its stride, Today, Generative AI is being used to create original content based on historical information.