mam diane

• Agent


  An entity that takes action in response to percept from an environment
• Intelligence


  • The capacity to acquire and apply knowledge
  • The faculty of thought and reason
  • The ability to comprehend and profit from experience
  • The ability to apply knowledge in order to perform better in an environment
• AI


  • The study of agents that receives percept from the environment and perform actions
  • A branch of science that studies the computational requirement for tasks such as perception, reasoning and learning & develop systems to perform those tasks
  • The field of AI strives to understand and build intelligent entities
• AI Technology Components


  • Learning
  • Reasoning and decision making
  • Problem solving
  • Perceptions
• Five Branches of AI

  • Machine Learning
  • Deep Learning
  • Natural Language Processing
  • Robotics
  • Fuzzy Logic
• Machine Learning


  • A subset of AI
  • The ability of machines to learn from data and algorithms automatically
  • It uses the essential components of AI to make decisions without being explicitly programmed by a human
• Deep Learning


  • Uses artificial neural networks (ANNs) inspired by the human brain, to extract abstract features from the data, leading to better performance than machine learning and often more powerful representations
  • With DL, there's even less human intervention than with ML, however, you need much greater volume of data than ML
• Natural Language Processing


  • The aspect of AI that allows computers to understand spoken words and written text
  • It is arguably the most commonly used AI as its intertwined in many of today's digital assistants, chatbots, virtual assistants and spam detection
  • It is also used to generate sentiment analysis, which analyzes texts and extracts the emotions and attitudes about a product or service
• Robotics


  • Utilizes AI to develop and design robots or machines capable of performing tasks autonomously or semi-autonomously
  • Generally, robotics involves other components of AI technology, such as NLP, ML or perception
  • AI-based robots are already in many industries, such as healthcare, retail, and manufacturing and can be used to help develop products
• Fuzzy Logic


  • The world is not always binary, making it difficult for AI devices to recognize whether a condition is true or false- hence fuzziness
  • Fuzzy logic helps solve issues or statements and recognize if they're true or false
  • AI can learn this fuzzy logic if-then statements or rules and applying linguistic variables and fuzzy rules to represent and process uncertain or imprecise information
• Components of AI Programming

  • Natural language processing
  • Machine learning
  • Computer vision
  • Robotics
  • Deep learning
  • Data processing
  • Deployment
• Brief History of AI

  • 5th century BC: Aristotle invents syllogistic logic, the first formal deductive reasoning system
  • 16th century AD: Rabbi Loew supposedly invents the Golem, an artificial man made out of clay
  • 17th century: Descartes proposes animals are machines and founds a scientific paradigm that will dominate for 250 years
  • 17th century: Pascal creates the first mechanical calculator in 1642
  • 18th century: Wolfgang von Kempelen "invents" fake chess-playing machine, The Turk
  • 19th century: George Boole creates a binary algebra to represent "laws of thought"
  • 19th century: Charles Babbage and Lady Lovelace develop sophisticated programmable mechanical computers, precursor to modern electronic computers
  • 20th century: Karel Kapek writes "Rossum's Universal Robots", coining the English word "robot"
  • 20th century: Warren McCulloch and Walter Pitts lay partial groundwork for neural networks
  • 20th century: Turing writes "Computing Machinery and Intelligence" – proposal of Turing test
  • 1956: John McCarthy coins phrase "artificial intelligence"
  • 1952-62: Arthur Samuel writes the first AI game program to challenge a world champion, in part due to learning
  • 1950's-60's: Masterman et. al at Cambridge create semantic nets that do machine translation
  • 1961: James Slagle writes first symbolic integrator, SAINT, to solve calculus problems
  • 1963: Thomas Evan's writes ANALOGY, which solves analogy problems like the ones on IQ tests
  • 1965: J. A. Robinson invents Resolution Method using formal logic as its representation language
  • 1971: Terry Winograd demonstrates a program that can understand English commands in the word of blocks
  • 1972: Alain Colmerauer writes Prolog
  • 1974: Ted Shortliffe creates MYCIN, the first expert system which showed the effectiveness of rule-based knowledge representation for medical diagnosis
  • 1978: Herb Simon wins Nobel Prize for theory of bounded rationality
  • 1983: James Allen creates Interval Calculus as a formal representation for events in time
  • 1980's: Backpropagation (invented 1974) rediscovered and sees wide use in neural networks
  • 1985: ALVINN, "an autonomous land vehicle in a neural network" navigates across the country (2800 miles)
  • Early 1990's: Gerry Tesauro creates TD-Gammon, a learning backgammon agent that vies with championship players
  • 1997: Deep Blue (a chess playing computer developed by IBM) defeats Garry Kasparov
  • Modern Times (post-Cartesian): Robopets, Widespread viruses, security holes aplenty, AI-powered CRM, Faster—and many more—computers