Podcast
Questions and Answers
Which event marked the first instance of a computer defeating a world chess champion?
Which event marked the first instance of a computer defeating a world chess champion?
What year did AI first enter the home environment with a consumer product?
What year did AI first enter the home environment with a consumer product?
Which AI application is known for its ability to engage in a debate with human debaters?
Which AI application is known for its ability to engage in a debate with human debaters?
What distinguishes Narrow AI from other forms of AI?
What distinguishes Narrow AI from other forms of AI?
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What significant AI development did Google introduce in 2012?
What significant AI development did Google introduce in 2012?
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What does the term 'Artificial' in Artificial Intelligence signify?
What does the term 'Artificial' in Artificial Intelligence signify?
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Which of the following is NOT a known goal of Artificial Intelligence?
Which of the following is NOT a known goal of Artificial Intelligence?
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Which of the following skills is NOT associated with Artificial Intelligence?
Which of the following skills is NOT associated with Artificial Intelligence?
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How does Artificial Intelligence differ from traditional programming?
How does Artificial Intelligence differ from traditional programming?
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What role can AI play concerning environments that may pose risks to human survival?
What role can AI play concerning environments that may pose risks to human survival?
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Which statement about the historical context of Artificial Intelligence is accurate?
Which statement about the historical context of Artificial Intelligence is accurate?
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What aspect does knowledge representation in AI primarily concern?
What aspect does knowledge representation in AI primarily concern?
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What is one significant benefit of Artificial Intelligence in practical applications?
What is one significant benefit of Artificial Intelligence in practical applications?
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Which of the following is a feature of AI systems in terms of reliability?
Which of the following is a feature of AI systems in terms of reliability?
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Why is it advantageous to use AI in risky situations?
Why is it advantageous to use AI in risky situations?
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What is one application of AI that enhances everyday activities?
What is one application of AI that enhances everyday activities?
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How does AI contribute to public utility services?
How does AI contribute to public utility services?
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Which statement accurately describes the accuracy of AI systems?
Which statement accurately describes the accuracy of AI systems?
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What distinguishes AI systems in terms of operational hours compared to humans?
What distinguishes AI systems in terms of operational hours compared to humans?
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Which of the following is NOT an advantage of using AI?
Which of the following is NOT an advantage of using AI?
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In what area does AI excel, making a notable impact?
In what area does AI excel, making a notable impact?
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Which of the following describes AI's interaction with human language?
Which of the following describes AI's interaction with human language?
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What major capabilities does AI facilitate in planning processes?
What major capabilities does AI facilitate in planning processes?
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Which learning model primarily depends on labeled datasets?
Which learning model primarily depends on labeled datasets?
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How does AI promote creativity?
How does AI promote creativity?
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What characterizes the learning process for AI systems?
What characterizes the learning process for AI systems?
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What is a major goal of AI in terms of continuous learning?
What is a major goal of AI in terms of continuous learning?
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What does AI primarily analyze for complex problem-solving in astronomy?
What does AI primarily analyze for complex problem-solving in astronomy?
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What components are integral in defining human intelligence that AI attempts to replicate?
What components are integral in defining human intelligence that AI attempts to replicate?
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Which of the following options does NOT contribute to AI's procedural planning?
Which of the following options does NOT contribute to AI's procedural planning?
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Which statement is true regarding machine learning's role in AI?
Which statement is true regarding machine learning's role in AI?
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What is one significant disadvantage of using artificial intelligence?
What is one significant disadvantage of using artificial intelligence?
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What effect does increasing reliance on AI have on human abilities?
What effect does increasing reliance on AI have on human abilities?
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Which invention in the history of artificial intelligence proposed a model of artificial neurons?
Which invention in the history of artificial intelligence proposed a model of artificial neurons?
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What major issue is raised due to AI replacing human jobs?
What major issue is raised due to AI replacing human jobs?
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What is a critical limitation of AI regarding innovation?
What is a critical limitation of AI regarding innovation?
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What does the term 'Hebbian learning' refer to?
What does the term 'Hebbian learning' refer to?
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In what year did Alan Turing publish his influential work on machine learning?
In what year did Alan Turing publish his influential work on machine learning?
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What is a potential economic impact of increased AI implementation?
What is a potential economic impact of increased AI implementation?
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What is a benefit of AI machines compared to human workers?
What is a benefit of AI machines compared to human workers?
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Which statement reflects a characteristic disadvantage of AI systems?
Which statement reflects a characteristic disadvantage of AI systems?
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Study Notes
Unit-1 Introduction to Artificial Intelligence
- Introduction of Artificial Intelligence: Definition, Goals of AI, Applications areas of AI
- Importance of Artificial Intelligence
- History of Artificial Intelligence
- Types of Artificial Intelligence
- Intelligent agents and environment
Unit-2 Searching
- Searching: Search algorithm terminologies, properties for search algorithms
- Search Algorithms
- Uninformed Search Algorithms
- Informed Search Algorithms
- Hill Climbing Algorithm
- Means-Ends Analysis
Unit-3 Knowledge
- Knowledge-Based Agent
- Architecture of knowledge-based agent
- Inference system
- Operations performed by Knowledge-Based Agent
- Knowledge Representation
- Types of Knowledge
- Approaches to knowledge representation
- Knowledge Representation Techniques
Unit-4 Logic
- Propositional Logic
- Rules of Inference
- The Wumpus world
- Knowledge-base for Wumpus World
- First-order logic
- Knowledge Engineering in FOL
- Inference in First-Order Logic
- Unification in FOL
- Resolution in FOL
- Forward Chaining
- Backward Chaining
- Backward Chaining vs forwarding Chaining
- Reasoning in AI
- Inductive vs. Deductive reasoning
Textbooks
- Introduction to Artificial Intelligence & Expert Systems' by Dan W. Patterson
- ‘Artificial Intelligence' by Elaine Rich, Kevin Knight, Shivashankar B Nair
- ‘Artificial Intelligence A Modern Approach, ‘by Stuart J. Russell and Peter Norvig
Contents of Unit 1
- Introduction of Artificial Intelligence: Definition, Goals of AI, and Applications areas of AI
- Importance of Artificial Intelligence
- History of Artificial Intelligence
- Types of Artificial Intelligence
- Intelligent agents and environment
What is Artificial Intelligence?
- Artificial Intelligence is composed of two words: Artificial and Intelligence
- Artificial defines "man-made" and intelligence defines "thinking power"
- Hence AI means "a man-made thinking power."
- AI is a branch of computer science.
- Through AI, we can create intelligent machines capable of behaving like humans.
- AI machines can think like humans and make decisions
- AI exists when a machine has human skills such as learning, reasoning, and problem-solving.
- With AI, you don't need to preprogram to do some work, but you can create a machine that can work with its own algorithms and intelligence.
Why Artificial Intelligence?
- AI can be used to create software or devices that solve real-world problems with accuracy and ease.
- Examples include health issues, marketing, and traffic issues
- AI can create your personal virtual assistants, such as Cortana, Google Assistant, and Siri
- AI can be used to build robots for environments where human survival may be at risk.
Goals of Artificial Intelligence
- Create Expert Systems that exhibit intelligent behavior, learn, demonstrate, explain, and advise users.
- Implement Human Intelligence in Machines. Machines that understand, think, learn, and behave like humans
- Improve Problem-solving skills through the potential of AI in solving complex problems, making lives easier, by designating complex duties to AI systems
Goals of Artificial Intelligence (continued)
- Include knowledge representation. This involves representing what is known to machines using objects, relations, and concepts to represent real-world data. A computer can then use this to solve complicated real-world problems such as diagnosing medical conditions or communicating naturally with humans.
- Facilitate Planning. This includes data analytics, forecasting, and optimization models for Al-driven planning to create procedural actions to help reach goals and optimize performance. A main goal of AI is to employ prediction.
Goals of Artificial Intelligence (continued)
- Allow continuous learning to improve knowledge through observing and processing past experiences, and using input-output pairs to predict outputs.
- Promote creativity. Help humans accomplish tasks more effectively by augmenting and strengthening creativity and developing novel ideas and concepts. AI can generate interior design options for example.
What Comprises to AI?
- Artificial Intelligence is not just a part of computer science, but includes various fields such as computer science, sociology, psychology, maths, philosophy, and biology.
- To create AI, we need to understand how intelligence is composed.
- It is an abstract concept that involves reasoning, problem-solving, perception, and language understanding.
Application areasof AI
- Astronomy to solve complex universe problems
- Healthcare to improve diagnosis and treatment speed and accuracy and reaching patients before hospitalisation.
- Gaming through playing strategic games like chess.
- Finance to develop automation, chatbots, and algorithm trading.
- Data Security to improve, automate, and enhance data safety in the digital world.
- Social Media for managing user profiles and analyzing trends.
- Travel & Transport to make travel arrangements, suggest hotels and other useful travel related options.
- Automotive to deliver virtual assistance through self-driving cars.
- Robotics to perform repetitive tasks with AI powered experiences.
- Entertainment to offer entertainment based on recommendations.
- Agriculture for agriculture robotics, monitoring, and predictive analysis.
- E-commerce to provide competitive advantages.
- Education to automate grading and provide student assistance (virtual tutors).
History of Artificial Intelligence
- 1943: Warren McCulloch & Walter Pitts developed a model of artificial neurons
- 1949: Donald Hebb demonstrated an updating rule for modifying connection strength between neurons (Hebbian learning).
- 1950: Alan Turing proposed the Turing test to evaluate machine intelligence.
- 1955: Allen Newell & Herbert A. Simon created the Logic Theorist, one of the first AI programs.
- 1956: John McCarthy coined the term Artificial Intelligence at the Dartmouth Conference
- 1966: Joseph Weizenbaum created ELIZA, an early chatbot.
- 1972: The first intelligent humanoid robot (WABOT-1) was built in Japan.
- 1974 - 1980: First AI winter (funding shortage).
- 1980: Rise of expert systems
- 1987 - 1993: Second AI winter (expert systems, XCON)
- 1997: IBM's Deep Blue beats world chess champion
- 2002: AI enters homes (Roomba)
- 2006: AI in business world (Facebook, Twitter, Netflix)
- 2011: IBM's Watson wins Jeopardy
- 2012: Google's "Google Now"
- 2014: Chatbot "Eugene Goostman" (Turing test)
- 2018: IBM's Project Debater
Types of Artificial Intelligence (Based on Capabilities)
- Weak AI/Narrow AI (dedicated tasks, limitations): examples- Siri, IBM's Watson, playing chess, purchasing suggestions
- General AI (any intellectual task with human-like efficiency): lacks such a system at the moment
- Super AI (surpasses human intelligence, cognitive properties)
Types of Artificial Intelligence (Based on Functionality)
- Reactive Machines (most basic, no memory for past experiences, current scenarios): examples- IBM's Deep Blue, Google's AlphaGo
- Limited Memory (store past experiences, but only for a limited time): examples- self-driving cars
- Theory of Mind (understand human emotions, beliefs)
- Self-Awareness (own consciousness, sentiments): currently a hypothetical concept
What is an Agent?
- An agent is anything that perceives its environment through sensors and acts through actuators.
- Agents interact with their environment in cycles, perceiving, thinking, and acting.
- An Agent can be a human, robot, or software program
- Human Agents - use their organs (eyes ears etc) as sensors, and hands, legs, and speech as actuators
- Robotic Agents- (camera infrared range finder, natural language processing for sensors, and motors for actuators)
- Software agents - use keystrokes, files, contents as inputs and display outputs on a screen.
Intelligent Agents
- An intelligent agent is an autonomous entity acting within an environment to achieve goals.
- A thermostat is an example
- Rules for AI agents
- Rule 1: Perceive the environment
- Rule 2: Use observation for decision making
- Rule 3: Decisions must result in action
- Rule 4: Action must be rational
Rational Agent
- Rational agents have clear preferences, model uncertainty, and act in ways that maximize performance with all possible actions.
- A rational agent performs the right thing to achieve a goal.
- In AI, the rational choice is important in reinforcement learning algorithms, as correct actions provide positive rewards and incorrect actions negative rewards.
Rationality
- Rationality of an agent is determined by its performance measure.
- Success criterion is defined by performance measure
- Agent's prior knowledge of the environment
- The sequence of percepts for actions.
Structure of an AI Agent
- AI agent structures are a combination of architecture and agent programs, viewed as Agent = Architecture + Agent Program.
- Architecture is the machinery, while the Agent Function maps percepts to actions.
- The Agent Program is the implementation of the agent function.
PEAS Representation
- PEAS stands for Performance measure, Environment, Actuators, and Sensors.
- It's a model of an AI agent's properties
- Performance measure is a success criterion.
- Example- A self-driving car agent's performance measure may value safety, time, and comfort.
- The environment provides the situation where the agent lives and works (road conditions, other vehicles etc).
PEAS for self-driving cars
- Performance: Safety, time, comfort
- Environment: Roads, other vehicles, road signs, pedestrians
- Actuators: Steering, accelerator, brake, signal, horn
- Sensors
Example of Agent with PEAS representation
- Agents with properties described under the PEAS model (Performance measure, Environment, Actuators, Sensors) are given for Medical Diagnose, Vacuum Cleaner, Part picking.
Agent Environment in AI
- The environment is everything around an agent, but not part of the agent.
- It describes the situation where the agent lives.
- The environment provides the agent with something to sense and act upon.
Types of AI Agents
- Simple Reflex Agent: Takes decisions based on current percepts.
- Model-based reflex agent: works in partially observable environments
- Goal-based Agents: agents are concerned with goal information
- Utility-based agents: agents are interested in achieving goals in appropriate means
- Learning Agents: learn from past experiences, adapting to the environment.
Simple Reflex Agent
- These agents are the simplest, taking decisions based on current percepts, ignoring past experiences, and succeeding in fully observable environments.
Model-based Reflex Agent
- These agents work in partially observable environments, tracking the situation through a model, having an Internal state representing the current state based on percept history.
Goal-based Agents
- Goal-based agents go beyond the current state to consider desirable situations and actions to achieve goals, potentially a long sequence of actions.
Utility-based Agents
- Utility-based agents expand upon goal-based agents by evaluating the utility of different actions, mapping each state to a real number to examine how efficiently an action achieves the goal
Learning Agents
- Learning agents have a learning element, a critic (with a performance standard), a problem generator that suggests new experiences, and a performance element for selecting actions.
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Description
Test your knowledge on the significant events and milestones in the development of artificial intelligence. From chess matches against champions to consumer products, this quiz covers key moments and features of AI. Challenge yourself and learn about the evolution of AI technologies.
