Unit 1: Introduction to AI

Unit 1: Introduction to AI

• Artificial Intelligence (AI) is the technology capable of activities that normally require human intelligence, including learning, thinking, problem-solving, perception, speech recognition, and language comprehension. AI enables robots to simulate human cognitive processes.

• AI is a branch of computer science that creates intelligent machines that can behave, think, and make decisions like humans.

• AI's goals include replicating human intelligence, solving knowledge-intensive tasks, connecting perception and action, and building machines that perform tasks requiring human intelligence (e.g., proving theorems, playing chess, surgical planning, driving). AI further aims to create systems that exhibit intelligent behavior, learn, demonstrate, explain, and advise users.

AI Advantages

• High accuracy with fewer errors
• High speed
• High reliability
• Usefulness in risky areas
• Function as a digital assistant
• Useful as a public utility

AI Disadvantages

• High cost
• Limited ability to think outside the box
• Lack of emotions
• Increased dependency on machines
• Inability to generate original creativity

History of AI

• John McCarthy researched automata theory, neural nets, and the study of intelligence at Dartmouth College, coining the term "computational rationality" for AI. The Dartmouth workshop marked a pivotal moment in AI development.

• Key milestones in AI history include Alan Turing's test, Joseph Weizenbaum's chatbot, Sony's AIBO robot dog, Apple's Siri, Amazon's Alexa, the development of question-answering computers like Watson and GPT-3, and advancements in robotic vacuum cleaners like Roomba.

AI Growth - Example 1: Simple Mechanical Intelligent Systems

• Traditional mechanical systems, like water taps or washing machines, utilize simple sensors for decision-making. Early systems utilized an overflow method to control water flow, as illustrated in Figure 1.1.
• Further advancements introduced fuzzy logic to dynamically adjust water levels based on factors like the quantity of clothing, showing development in intelligent systems.

AI Growth - Example 2: Traffic Signals

• Traffic signal evolution from traditional, manually controlled systems to increasingly advanced computer-controlled signals, demonstrating the progressive evolution from simpler to more sophisticated AI-enabled systems, as demonstrated across time periods illustrated in Figure 1.2.