Artificial Intelligence (AI) is an interdisciplinary research field focused on the mechanization of human-like intelligence[2]. AI systems use a combination of capabilities, including learning, reasoning, problem-solving, and understanding language and visual signals[1]. AI systems can learn by repetition or by being programmed to perform specific tasks[1]. They can also understand context, sort information, and make decisions based on a level of uncertainty[5].

AI works by combining large datasets with intelligent, iterative algorithms that can learn patterns and relationships within the data to make predictions and decisions[3]. These algorithms can be used to perform tasks such as identifying images, diagnosing diseases, and predicting and preventing Opioid deaths[1]. AI systems can improve their performance over time by finding patterns or trends in the data[1].

AI has five types of technologies[4]:

  1. Thinking machines: Computerized symbols use Boolean algebra and neurons to solve problems and make predictions.
  2. Human-AI Interaction: Computers use AI to recognize human emotions, understand natural language, and artistically create culture.
  3. Vision and Perception: Computer vision and machine vision help AI realize how things look and where they are.
  4. Uncertainty and Probability: Mathematics, probability, and statistics measure uncertainty, helping AI handle imprecise or unpredictable situations.
  5. Learning: AI systems can learn by comparing reinforcement actions/decisions with perfect decisions and making decisions[4].

AI has various applications, including security and intelligence, personal quality of life, and fantastic but unrealistic concepts like AI for drug development, diagnostics, nurse bots, surgical robots, and Independence Day salt destroyers[3].