1. The document introduces the topic of artificial intelligence (AI) including its evolution, branches, applications, and conclusions.
2. It defines AI as a branch of computer science dealing with symbolic and non-algorithmic problem solving and discusses strong vs weak AI.
3. Applications of AI discussed include expert systems, natural language processing, speech recognition, computer vision, robotics, and automatic programming.
Artificial intelligence (AI) aims to build intelligent machines that can perform tasks requiring human intelligence. The goals of AI are to better understand human intelligence by modeling it in computer programs, and to create useful programs that can perform expert tasks. Many disciplines contribute to AI including computer science, psychology, philosophy, linguistics, and biology. Typical AI problems involve both mundane tasks like shopping and expert tasks like medical diagnosis. Philosophical issues in AI include what intelligence is, whether machines can truly be intelligent, and if human intelligence can be reduced to rules and calculations. This module will cover AI programming, knowledge representation, search techniques, natural language processing, machine learning, intelligent agents, and knowledge engineering.
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What is Artificial Intelligence(AI)? , Evolution , Applications of AI? , Features of AI , What is Intelligence and its types?,
What are Agents and Environment? , Fear of AI , Machine Learning , Difference between AI, ML and Deep Learning ,
Applications of ML , Algorithms of AL and ML , Future of AI
Introduction Artificial Intelligence a modern approach by Russel and Norvig 1Garry D. Lasaga
This document provides an introduction to artificial intelligence. It discusses four views of AI: thinking like humans through cognitive modeling; acting like humans by passing the Turing test; thinking rationally through logical reasoning; and acting rationally by maximizing goals. The document also summarizes the history of AI from its foundations in philosophy, mathematics, and other fields to modern achievements like Deep Blue beating Kasparov at chess. It concludes with examples of state-of-the-art AI systems being used for logistics planning, spacecraft scheduling, and solving crossword puzzles.
This document provides an overview of an introductory artificial intelligence course. It describes the course topics which include search, logic, probability, and learning techniques. It also summarizes the current state of AI, highlighting successes in logistics, games, natural language processing, vision, robotics, and question answering. The course is intended for juniors and seniors and requires programming skills and exposure to algorithms, calculus, and probability.
This document provides an overview of artificial intelligence. It defines intelligence as the ability to plan, solve problems, reason, learn, understand new situations, and apply knowledge. AI is described as building intelligent systems that can think and act like humans or rationally. The history of AI is discussed, from its origins in the 1950s to current applications. Key concepts to be learned in the semester include problem solving, machine learning, evolutionary computation, robotics, and intelligent agents. Python and NetLogo will be used as tools.
This document provides an overview of an artificial intelligence course, including:
- The course covers introduction to AI history and applications, knowledge representation, problem solving using search and reasoning, machine learning, robotics, and advanced AI topics.
- Required materials include an AI textbook, CLIPS programming guide, and reference books on AI structures and complex problem solving.
- The document then provides definitions and discussions of intelligence, artificial intelligence, applications of AI, and the current capabilities and limitations of AI systems.
Sentient artificial intelligence could pose dangers if it develops self-awareness and human-level intelligence within the next decade. While AI has made progress in modeling human brains and matching human intelligence, creating truly sentient machines remains challenging. The Turing Test evaluates intelligence by assessing whether a machine can imitate human conversations, but has limitations in testing for general human-level cognition. Developing AI that thinks rationally based on logical rules or models human cognition remains an open area of research.
1. The document introduces the topic of artificial intelligence (AI) including its evolution, branches, applications, and conclusions.
2. It defines AI as a branch of computer science dealing with symbolic and non-algorithmic problem solving and discusses strong vs weak AI.
3. Applications of AI discussed include expert systems, natural language processing, speech recognition, computer vision, robotics, and automatic programming.
Artificial intelligence (AI) aims to build intelligent machines that can perform tasks requiring human intelligence. The goals of AI are to better understand human intelligence by modeling it in computer programs, and to create useful programs that can perform expert tasks. Many disciplines contribute to AI including computer science, psychology, philosophy, linguistics, and biology. Typical AI problems involve both mundane tasks like shopping and expert tasks like medical diagnosis. Philosophical issues in AI include what intelligence is, whether machines can truly be intelligent, and if human intelligence can be reduced to rules and calculations. This module will cover AI programming, knowledge representation, search techniques, natural language processing, machine learning, intelligent agents, and knowledge engineering.
About
What is Artificial Intelligence(AI)? , Evolution , Applications of AI? , Features of AI , What is Intelligence and its types?,
What are Agents and Environment? , Fear of AI , Machine Learning , Difference between AI, ML and Deep Learning ,
Applications of ML , Algorithms of AL and ML , Future of AI
Introduction Artificial Intelligence a modern approach by Russel and Norvig 1Garry D. Lasaga
This document provides an introduction to artificial intelligence. It discusses four views of AI: thinking like humans through cognitive modeling; acting like humans by passing the Turing test; thinking rationally through logical reasoning; and acting rationally by maximizing goals. The document also summarizes the history of AI from its foundations in philosophy, mathematics, and other fields to modern achievements like Deep Blue beating Kasparov at chess. It concludes with examples of state-of-the-art AI systems being used for logistics planning, spacecraft scheduling, and solving crossword puzzles.
This document provides an overview of an introductory artificial intelligence course. It describes the course topics which include search, logic, probability, and learning techniques. It also summarizes the current state of AI, highlighting successes in logistics, games, natural language processing, vision, robotics, and question answering. The course is intended for juniors and seniors and requires programming skills and exposure to algorithms, calculus, and probability.
This document provides an overview of artificial intelligence. It defines intelligence as the ability to plan, solve problems, reason, learn, understand new situations, and apply knowledge. AI is described as building intelligent systems that can think and act like humans or rationally. The history of AI is discussed, from its origins in the 1950s to current applications. Key concepts to be learned in the semester include problem solving, machine learning, evolutionary computation, robotics, and intelligent agents. Python and NetLogo will be used as tools.
This document provides an overview of an artificial intelligence course, including:
- The course covers introduction to AI history and applications, knowledge representation, problem solving using search and reasoning, machine learning, robotics, and advanced AI topics.
- Required materials include an AI textbook, CLIPS programming guide, and reference books on AI structures and complex problem solving.
- The document then provides definitions and discussions of intelligence, artificial intelligence, applications of AI, and the current capabilities and limitations of AI systems.
Sentient artificial intelligence could pose dangers if it develops self-awareness and human-level intelligence within the next decade. While AI has made progress in modeling human brains and matching human intelligence, creating truly sentient machines remains challenging. The Turing Test evaluates intelligence by assessing whether a machine can imitate human conversations, but has limitations in testing for general human-level cognition. Developing AI that thinks rationally based on logical rules or models human cognition remains an open area of research.
This document provides an overview of an artificial intelligence course taught at Jahan University in Kabul, Afghanistan. The course covers topics such as the history of AI, knowledge representation, machine learning, and robotics. It aims to help students understand different approaches to AI and implications for cognitive science. Learning outcomes include expanding knowledge of search techniques, planning algorithms, knowledge representation, and machine learning programming. Required materials include an AI textbook and reference books. The lecture discusses definitions of intelligence and AI, modern successes in the field, and the state of technologies like speech recognition, computer vision, and planning.
Most of the examples listed can currently be done to some degree by AI/robotic systems, though often with limitations compared to human capabilities. Here are a few highlights of what has and hasn't been fully achieved:
- Decent table tennis play has been achieved through computer vision, motion planning, and robotics, though not at a professional human level across all situations.
- Autonomous driving has progressed significantly in structured environments like highways, but unconstrained mountain roads with tight curves present greater challenges due to limitations in perception, prediction, and control for high-speed maneuvering.
- Driving autonomously through dense urban environments like city centers is extremely difficult given the complex interactions between many road users and need to understand and
This document provides an overview of an Intelligent Systems course. It outlines the course assignments and grading breakdown. It then discusses what AI is, including definitions and different views of AI like thinking humanly, acting humanly, thinking rationally, and acting rationally. It also provides a brief history of AI and discusses the current state of the art in applications like speech recognition, machine translation, robotics, and recommendation systems.
This document provides an introduction to artificial intelligence (AI) through summarizing the goals of an AI course, defining intelligence and AI, and outlining the history and applications of AI. The key topics covered include developing familiarity with AI techniques and applications, understanding the theory behind different techniques, and learning about both classic and current AI systems.
This document provides an overview of an introductory lecture on artificial intelligence and expert systems. It discusses the Turing Test, definitions of artificial intelligence, a brief history of AI including important figures and milestones, and examples of what current AI systems can and cannot do.
The document discusses the history and scope of artificial intelligence, including definitions of AI as designing intelligent systems, different perspectives on what constitutes intelligence, and approaches to AI such as strong AI, weak AI, applied AI, and cognitive AI. It also examines what current AI systems can and cannot do and provides examples of tasks that have been achieved as well as limitations.
The document is a syllabus for an Artificial Intelligence unit taught by Surbhi Saroha. The syllabus covers an introduction to AI, the foundations and history of AI, applications of AI, intelligent agents, the structure of intelligent agents, computer vision, and natural language processing. It provides an overview of key concepts that will be examined in each topic area.
The document provides an introduction to artificial intelligence, including definitions of AI, a brief history of the field, and the current state of the art. It discusses four views of AI: thinking humanly, thinking rationally, acting humanly, and acting rationally. The textbook advocates the view of "acting rationally" by designing agents that perceive and act to maximize goals. The document also outlines some of the key topics that will be covered in the course, including search, logic, planning, and learning.
Hpai class 12 - potpourri & perception - 032620 actualmelendez321
This document contains the notes from a class on human perspective in artificial intelligence. It discusses various topics that will be covered in the class, including memory, forgetting, perception, vision, sound, touch, smell, taste, language, programming, applications of AI, and the futurism of AI. It provides instructions and announcements for assignments, including changes to homework due dates. Students ask questions and provide comments on potential future topics, including emotions in video games, AI prosthetics, conscious transfer to other bodies or computers, and discussions of textbooks.
Understanding Artificial Intelligence with Pop CultureJaidev Deshpande
The document discusses artificial intelligence (AI) and what constitutes intelligence. It notes that AI is not the same as robotics, as robots may not be intelligent and intelligent machines need not be robots. It then lists several attributes that could be considered aspects of intelligence, such as logic, learning, communication, emotional knowledge, memory, planning and problem solving. The document goes on to discuss concepts like the singularity, why research in AI is pursued, examples of current AI projects, and differences between fast computers and true intelligence.
Artificial intelligence (AI) is software that allows computers and robots to perform tasks in a way that mimics human intelligence. John McCarthy first proposed the term "artificial intelligence" in 1956. AI uses techniques like machine learning, natural language processing, and computer vision to perform tasks previously only done by humans, such as playing games, recognizing speech, and understanding language. While AI has advantages like efficiency, reliability, and ability to handle complex tasks, it also has drawbacks like limited ability and lack of complete human traits. The ultimate goal of AI research is to solve problems humans cannot.
This document provides an introduction to artificial intelligence. It outlines topics that will be covered, including problems and search, knowledge representation, and machine learning. It then discusses definitions of AI, the foundations of AI in fields like philosophy and psychology. A brief history of AI is presented, from its origins in the 1940s to current state-of-the-art capabilities like game playing and robotics. Different task domains for AI are listed. The document concludes with exercises analyzing definitions of artificial intelligence.
This document provides an overview of an AI course titled "Human Perspective in Artificial Intelligence". It includes the course professor's information, upcoming class topics such as linguistics and inner voice, exam and assignment details, and summaries of class content. The document outlines an upcoming class discussion on inner voice that will involve analyzing a letter from Albert Einstein describing his thought processes without speaking out loud as primarily visual and some muscular in nature. It also announces an open question and answer session to help prepare for an upcoming exam.
In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans.
This document provides an overview of the CS3243 Foundations of Artificial Intelligence course from NUS for the 2003/2004 semester. It outlines the course details including the textbook, instructor, grading breakdown, and course topics. The course will cover introduction to AI concepts like agents, search, logic, planning, uncertainty, learning, and natural language processing. It also provides background on the history and state of the art in AI, including definitions of what AI is from different perspectives.
The document outlines the objectives, outcomes, and learning outcomes of a course on artificial intelligence. The objectives include conceptualizing ideas and techniques for intelligent systems, understanding mechanisms of intelligent thought and action, and understanding advanced representation and search techniques. Outcomes include developing an understanding of AI building blocks, choosing appropriate problem solving methods, analyzing strengths and weaknesses of AI approaches, and designing models for reasoning with uncertainty. Learning outcomes include knowledge, intellectual skills, practical skills, and transferable skills in artificial intelligence.
This document discusses several key topics in philosophy of AI:
1. It examines debates around whether machines can think intelligently and behave like humans. Philosophers disagree on issues like consciousness and emotions in machines.
2. It outlines Asimov's Three Laws of Robotics which propose ethical guidelines for robots to not harm humans and obey human orders.
3. It lists areas where AI is applied like knowledge representation, reasoning, games, and robotics. Academic disciplines related to AI research are also mentioned.
Hello beautiful people, i hope you all are doing great. Here I'm sharing a short PPT on Artificial Intelligence. if you found it helpful. say thanks it's appreciated.
Hpai class 14 - brain cells and memory - 031620melendez321
This document outlines the topics and agenda for a course on human perspectives in artificial intelligence. It discusses upcoming topics like perception, language, human vs artificial memory, and how human memory works. It describes a virtual roundtable discussion on human memory attributes. It also covers a discussion on how learning has changed with easy internet access. The document outlines an exam, project report, and homework due dates. It provides information on neurons, glia, and the structure and function of brain cells like dendrites and astrocytes. It diagrams the action potential process in neurons and describes cytosol, cytoplasm, and the nucleus in cells.
Virtual reality is a computer-generated simulation that can be interacted with physically. It has been an idea since the 1950s but gained popularity in the 1980s and 90s. There are three types of VR systems - non-immersive desktop systems, semi-immersive projection systems, and fully immersive head-mounted display systems. VR has applications in architecture, military, and healthcare. However, it is limited by high costs and space requirements for equipment such as head-mounted displays.
This document discusses applications of virtual reality (VR) technology. It describes how VR can be used to allow workers to complete dangerous tasks remotely through teleoperation. It also discusses how VR is used in scientific visualization, such as allowing geologists to analyze planetary surfaces remotely. Additionally, the document outlines how VR can be used in medicine for training and experimental research. It provides examples of VR systems, including non-immersive, augmented reality, and immersive systems. Input and output devices for VR are also described.
This document provides an overview of an artificial intelligence course taught at Jahan University in Kabul, Afghanistan. The course covers topics such as the history of AI, knowledge representation, machine learning, and robotics. It aims to help students understand different approaches to AI and implications for cognitive science. Learning outcomes include expanding knowledge of search techniques, planning algorithms, knowledge representation, and machine learning programming. Required materials include an AI textbook and reference books. The lecture discusses definitions of intelligence and AI, modern successes in the field, and the state of technologies like speech recognition, computer vision, and planning.
Most of the examples listed can currently be done to some degree by AI/robotic systems, though often with limitations compared to human capabilities. Here are a few highlights of what has and hasn't been fully achieved:
- Decent table tennis play has been achieved through computer vision, motion planning, and robotics, though not at a professional human level across all situations.
- Autonomous driving has progressed significantly in structured environments like highways, but unconstrained mountain roads with tight curves present greater challenges due to limitations in perception, prediction, and control for high-speed maneuvering.
- Driving autonomously through dense urban environments like city centers is extremely difficult given the complex interactions between many road users and need to understand and
This document provides an overview of an Intelligent Systems course. It outlines the course assignments and grading breakdown. It then discusses what AI is, including definitions and different views of AI like thinking humanly, acting humanly, thinking rationally, and acting rationally. It also provides a brief history of AI and discusses the current state of the art in applications like speech recognition, machine translation, robotics, and recommendation systems.
This document provides an introduction to artificial intelligence (AI) through summarizing the goals of an AI course, defining intelligence and AI, and outlining the history and applications of AI. The key topics covered include developing familiarity with AI techniques and applications, understanding the theory behind different techniques, and learning about both classic and current AI systems.
This document provides an overview of an introductory lecture on artificial intelligence and expert systems. It discusses the Turing Test, definitions of artificial intelligence, a brief history of AI including important figures and milestones, and examples of what current AI systems can and cannot do.
The document discusses the history and scope of artificial intelligence, including definitions of AI as designing intelligent systems, different perspectives on what constitutes intelligence, and approaches to AI such as strong AI, weak AI, applied AI, and cognitive AI. It also examines what current AI systems can and cannot do and provides examples of tasks that have been achieved as well as limitations.
The document is a syllabus for an Artificial Intelligence unit taught by Surbhi Saroha. The syllabus covers an introduction to AI, the foundations and history of AI, applications of AI, intelligent agents, the structure of intelligent agents, computer vision, and natural language processing. It provides an overview of key concepts that will be examined in each topic area.
The document provides an introduction to artificial intelligence, including definitions of AI, a brief history of the field, and the current state of the art. It discusses four views of AI: thinking humanly, thinking rationally, acting humanly, and acting rationally. The textbook advocates the view of "acting rationally" by designing agents that perceive and act to maximize goals. The document also outlines some of the key topics that will be covered in the course, including search, logic, planning, and learning.
Hpai class 12 - potpourri & perception - 032620 actualmelendez321
This document contains the notes from a class on human perspective in artificial intelligence. It discusses various topics that will be covered in the class, including memory, forgetting, perception, vision, sound, touch, smell, taste, language, programming, applications of AI, and the futurism of AI. It provides instructions and announcements for assignments, including changes to homework due dates. Students ask questions and provide comments on potential future topics, including emotions in video games, AI prosthetics, conscious transfer to other bodies or computers, and discussions of textbooks.
Understanding Artificial Intelligence with Pop CultureJaidev Deshpande
The document discusses artificial intelligence (AI) and what constitutes intelligence. It notes that AI is not the same as robotics, as robots may not be intelligent and intelligent machines need not be robots. It then lists several attributes that could be considered aspects of intelligence, such as logic, learning, communication, emotional knowledge, memory, planning and problem solving. The document goes on to discuss concepts like the singularity, why research in AI is pursued, examples of current AI projects, and differences between fast computers and true intelligence.
Artificial intelligence (AI) is software that allows computers and robots to perform tasks in a way that mimics human intelligence. John McCarthy first proposed the term "artificial intelligence" in 1956. AI uses techniques like machine learning, natural language processing, and computer vision to perform tasks previously only done by humans, such as playing games, recognizing speech, and understanding language. While AI has advantages like efficiency, reliability, and ability to handle complex tasks, it also has drawbacks like limited ability and lack of complete human traits. The ultimate goal of AI research is to solve problems humans cannot.
This document provides an introduction to artificial intelligence. It outlines topics that will be covered, including problems and search, knowledge representation, and machine learning. It then discusses definitions of AI, the foundations of AI in fields like philosophy and psychology. A brief history of AI is presented, from its origins in the 1940s to current state-of-the-art capabilities like game playing and robotics. Different task domains for AI are listed. The document concludes with exercises analyzing definitions of artificial intelligence.
This document provides an overview of an AI course titled "Human Perspective in Artificial Intelligence". It includes the course professor's information, upcoming class topics such as linguistics and inner voice, exam and assignment details, and summaries of class content. The document outlines an upcoming class discussion on inner voice that will involve analyzing a letter from Albert Einstein describing his thought processes without speaking out loud as primarily visual and some muscular in nature. It also announces an open question and answer session to help prepare for an upcoming exam.
In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans.
This document provides an overview of the CS3243 Foundations of Artificial Intelligence course from NUS for the 2003/2004 semester. It outlines the course details including the textbook, instructor, grading breakdown, and course topics. The course will cover introduction to AI concepts like agents, search, logic, planning, uncertainty, learning, and natural language processing. It also provides background on the history and state of the art in AI, including definitions of what AI is from different perspectives.
The document outlines the objectives, outcomes, and learning outcomes of a course on artificial intelligence. The objectives include conceptualizing ideas and techniques for intelligent systems, understanding mechanisms of intelligent thought and action, and understanding advanced representation and search techniques. Outcomes include developing an understanding of AI building blocks, choosing appropriate problem solving methods, analyzing strengths and weaknesses of AI approaches, and designing models for reasoning with uncertainty. Learning outcomes include knowledge, intellectual skills, practical skills, and transferable skills in artificial intelligence.
This document discusses several key topics in philosophy of AI:
1. It examines debates around whether machines can think intelligently and behave like humans. Philosophers disagree on issues like consciousness and emotions in machines.
2. It outlines Asimov's Three Laws of Robotics which propose ethical guidelines for robots to not harm humans and obey human orders.
3. It lists areas where AI is applied like knowledge representation, reasoning, games, and robotics. Academic disciplines related to AI research are also mentioned.
Hello beautiful people, i hope you all are doing great. Here I'm sharing a short PPT on Artificial Intelligence. if you found it helpful. say thanks it's appreciated.
Hpai class 14 - brain cells and memory - 031620melendez321
This document outlines the topics and agenda for a course on human perspectives in artificial intelligence. It discusses upcoming topics like perception, language, human vs artificial memory, and how human memory works. It describes a virtual roundtable discussion on human memory attributes. It also covers a discussion on how learning has changed with easy internet access. The document outlines an exam, project report, and homework due dates. It provides information on neurons, glia, and the structure and function of brain cells like dendrites and astrocytes. It diagrams the action potential process in neurons and describes cytosol, cytoplasm, and the nucleus in cells.
Virtual reality is a computer-generated simulation that can be interacted with physically. It has been an idea since the 1950s but gained popularity in the 1980s and 90s. There are three types of VR systems - non-immersive desktop systems, semi-immersive projection systems, and fully immersive head-mounted display systems. VR has applications in architecture, military, and healthcare. However, it is limited by high costs and space requirements for equipment such as head-mounted displays.
This document discusses applications of virtual reality (VR) technology. It describes how VR can be used to allow workers to complete dangerous tasks remotely through teleoperation. It also discusses how VR is used in scientific visualization, such as allowing geologists to analyze planetary surfaces remotely. Additionally, the document outlines how VR can be used in medicine for training and experimental research. It provides examples of VR systems, including non-immersive, augmented reality, and immersive systems. Input and output devices for VR are also described.
Virtual reality is a computer-simulated environment that can recreate sensory experiences like sight, sound, and touch. The history of VR began in the 1960s and has since been used in various fields like education, medicine, business, and the military. While VR offers many applications, it also faces challenges in causing simulation sickness and disorientation when users cannot see the real world. As the technology advances, VR is expected to become more integrated into daily life and human activities.
3D technology creates the illusion of depth by displaying stereoscopic images that mimic human binocular vision. The earliest techniques for 3D imaging were developed in the 1830s, but modern 3D became popular through 3D movies seen with red-blue or polarized glasses. Today, 3D is used in movies, TVs, video games, and simulations by projecting two offset images separately to each eye. This allows the brain to process depth cues and perceive 3D. While 3D brings content to life, it can cause eyestrain, motion sickness, and has privacy and health implications that require consideration.
Cryptography is the science of using mathematics to encrypt and decrypt data.
Cryptography enables you to store sensitive information or transmit it across insecure networks so that it cannot be read by anyone except the intended recipient.
Virtual reality is a user interface that involves real-time simulation and interactions through sensory channels to immerse users in virtual environments. It has its origins in flight simulators from the 1950s and early prototypes in the 1960s, with commercial development beginning in the late 1980s. Current applications of VR include movies, video games, and education/training. Emerging technologies like Project Natal, CAVE systems, and the Nintendo Wii are pushing the boundaries of VR by enabling more natural physical interaction. While the future is uncertain, VR is expected to continue evolving entertainment and other industries through immersive experiences.
The document discusses artificial intelligence, including its history, applications, and languages. It provides an overview of AI, noting that it aims to recreate human intelligence through machine learning and problem solving. The document then covers key topics like the philosophy of AI, limits on machine intelligence, and comparisons between human and artificial brains. It also gives brief histories of AI and machine learning. The document concludes by discussing popular AI programming languages like Lisp and Prolog, as well as various applications of AI technologies.
Artificial intelligence is the study and design of intelligent agents, with no single goal. It aims to put the human mind into computers by developing machines that can achieve goals through computation. The origins of AI began in the 1940s with the development of electronic computers. Significant early developments included the first stored program computer in the 1950s, the Dartmouth Conference which coined the term "artificial intelligence" in the 1950s, and the development of the LISP programming language. In the following decades, AI research expanded and led to applications in fields like expert systems, games, and military systems. While progress has been made, the full extent of intelligence and the future of AI remains unknown.
This Presentation will give you an overview about Artificial Intelligence : definition, advantages , disadvantages , benefits , applications .
We hope it to be useful .
A Guide to SlideShare Analytics - Excerpts from Hubspot's Step by Step Guide ...SlideShare
This document provides a summary of the analytics available through SlideShare for monitoring the performance of presentations. It outlines the key metrics that can be viewed such as total views, actions, and traffic sources over different time periods. The analytics help users identify topics and presentation styles that resonate best with audiences based on view and engagement numbers. They also allow users to calculate important metrics like view-to-contact conversion rates. Regular review of the analytics insights helps users improve future presentations and marketing strategies.
- The document discusses artificial intelligence, including its history, key areas such as knowledge representation and learning, and applications in areas like consumer marketing, identification technologies, predicting stock markets, and machine translation.
- While progress has been made in areas like recognition and learning, challenges remain in full natural language understanding, human-level planning and decision making. AI is being applied across many industries but remains an active area of research.
1) Artificial intelligence (AI) is the study of intelligent machines that can perform functions like human thought. AI research dates back to ancient times but expanded in the 20th century with advances in computing.
2) Early milestones included simulating human thinking on computers in 1956 and the first AI conference that year, which inspired research emulating human reasoning, language, communication and more.
3) AI has many applications today including financial services, healthcare, transportation and more, but still faces limitations, especially in areas like natural language understanding. Fully realizing human-level AI may take decades more of research focused on language, environmental interaction and other challenges.
This document provides an overview of an introductory course on artificial intelligence. It discusses four views of AI: thinking humanly, thinking rationally, acting humanly, and acting rationally. The textbook advocates the view of "acting rationally" by designing agents that maximize goal achievement given available information. A brief history of AI is also provided, from early work in philosophy, mathematics, and the sciences to landmark developments like Turing's 1950 paper posing the question "Can machines think?". The state of the art in AI is summarized with examples like Deep Blue defeating Kasparov at chess in 1997 and autonomous vehicles driving 98% of the time across the US.
The document introduces an artificial intelligence course, discussing why AI is studied, potential benefits, and definitions of AI. It explores different approaches to AI like systems that act intelligently by passing the Turing test or thinking rationally. The document also provides a brief history of AI, discussing pioneers in the field and important questions and challenges in developing intelligent systems.
The document introduces an artificial intelligence course, discussing why AI is studied, potential benefits, and definitions of AI. It explores different approaches to AI like systems that act intelligently by passing the Turing test or thinking rationally. The document also provides a brief history of AI, discussing pioneers in the field and important questions and challenges in developing intelligent systems.
This document provides an introduction to an artificial intelligence course. It discusses why AI is an important field of study and provides definitions of AI from several experts. It also explores different approaches to AI like acting humanly by passing the Turing test, thinking humanly by understanding brain function, thinking rationally through logic, and acting rationally to achieve goals. The document examines key issues and questions in AI and outlines important foundations and history. It analyzes components of AI systems and properties of different environments agents can operate in.
This document provides information about the COMPSCI 570: Artificial Intelligence course at Duke University taught by Professor Vincent Conitzer. It includes basic course details like meeting times, prerequisites, grading, and an overview of topics to be covered. It also briefly discusses some successes in AI like game playing as well as challenges and concerns regarding superintelligence, consciousness, technological unemployment, and autonomous weapons.
Artificial intelligence and machine learning are discussed. AI is defined as making computers intelligent like humans through understanding, reasoning, planning, communication and perception. Machine learning is a subset of AI that allows machines to learn from experience without being explicitly programmed. The document provides background on AI and ML, including definitions, history, and discussions of intelligence and applications.
The document provides an overview of artificial intelligence (AI), including its main areas of study, progress made, applications, and ongoing challenges. It discusses how AI involves automated perception, learning, reasoning and planning. While recognition and learning have advanced, planning and general reasoning remain challenging. The document outlines applications in industries like finance, medicine and transportation, but notes that many problems remain unsolved, making AI an active area of research.
This document provides an overview of artificial intelligence including:
- It defines four approaches to AI: acting humanly through the Turing test, thinking humanly through cognitive modeling, thinking rationally through symbolic logic, and acting rationally as intelligent agents.
- It then summarizes the history of AI from its origins in the 1940s through developments in knowledge-based systems, connectionism, and the emergence of intelligent agents using large datasets.
- Finally, it briefly discusses recent applications of AI such as algorithms used by Facebook, TikTok, and noise cancellation in Zoom calls.
THE PHILOSOPHY OF AI: iNTRODUCTION, HISTORY AND FUTUREchuruihang
1. The document summarizes key topics from a class on the history and philosophy of artificial intelligence, including important people, events, current areas of research, and debates around whether we can and should create intelligent machines.
2. It discusses pioneers in AI from the 1940s onward and important milestones like the Dartmouth conference, expert systems, and the Turing test.
3. Philosophical questions are raised about what constitutes intelligence, whether we will know it when we create it, and the ethical implications of building intelligent systems that could potentially behave in uncontrolled or harmful ways.
This document provides an overview of key concepts in artificial intelligence including definitions of AI, subfields and problems, types of agents, and related careers. It discusses definitions of AI that focus on thinking and acting like humans or thinking and acting rationally. It also outlines several subfields and problems in AI such as reasoning and problem solving, knowledge representation, planning, learning, natural language processing, robotics, computer vision, and speech recognition. The document concludes by listing different types of agents from reflex agents to goal-based and utility-based agents and providing examples of AI-related careers.
This document discusses artificial intelligence (AI) and defines it as making computers do intelligent tasks like humans. It explains that AI works using artificial neurons in artificial neural networks and scientific theorems. Neural networks are composed of interconnected artificial neurons that mimic biological neurons. The document also outlines the history of AI and some applications like medical diagnosis systems. It compares human and artificial intelligence, noting machines can process large data quickly while humans have intuition and common sense. Finally, it argues AI is important for supplementing human work and labor.
1. Artificial Intelligence aims to understand and build intelligent systems by studying human intelligence and behavior.
2. There are different approaches to defining AI such as thinking rationally, acting rationally, thinking humanly, and acting humanly.
3. The foundations of AI draw from various fields including philosophy, mathematics, economics, neuroscience, psychology, and computer engineering.
The document discusses artificial intelligence and provides definitions of AI from various sources. It examines different approaches to AI such as systems that act humanly by passing the Turing test, think humanly by modeling the brain, think rationally by using logic, and act rationally by achieving goals. The document also discusses the history and components of AI systems, including agents, environments, and the PEAS framework for describing tasks.
This document provides an overview of an Artificial Intelligence course, including:
- The course covers topics such as strong and weak AI, knowledge representation, problem solving using search techniques, machine learning, and more.
- The learning outcomes are to understand different approaches to AI and implications for cognitive science, expand knowledge of search and learning algorithms, and understand basic planning and reasoning methods.
- Required materials include an AI textbook and reference books, as well as a programming language for AI applications.
This document provides an overview of an introductory course on artificial intelligence. It outlines the topics that will be covered in the course, which include propositional logic, predicate logic, reasoning, search methods, planning, software agents, rule learning, inductive logic programming, neural networks, and the semantic web. It then discusses some of the key concepts and theories in AI, such as the definitions of intelligence and artificial intelligence, the Turing test for machine intelligence, symbolic vs subsymbolic approaches to AI, and the development of knowledge-based systems.
PPT ON INTRODUCTION TO AI- UNIT-1-PART-1.pptxRaviKiranVarma4
This document provides an introduction to artificial intelligence, including definitions, history, and applications. It discusses four main categories of AI: systems that think like humans through cognitive modeling, systems that act like humans by passing the Turing test, and systems that think and act rationally as intelligent software agents. The document also outlines foundations of AI from various academic disciplines and provides a brief history of milestones in the field from the 1940s to modern applications.
Artificial intelligence (AI) is defined as intelligence demonstrated by machines in contrast to the natural intelligence displayed by humans. AI is the study of ideas that enable computers to be intelligent by learning new concepts and tasks, reasoning and drawing useful conclusions, and understanding natural language. The evolution of AI has progressed slowly over time with advances in technology. There are different approaches to creating AI systems and various applications of AI in fields such as computer science, aviation, finance, and more.
Here are three possible interpretations of the phrase "Time flies like an arrow":
1. The passage of time seems to go by very quickly, in the same way that an arrow flies through the air.
2. Certain types of insects that lay their eggs on decaying matter, known as flies, move through the air in a similar way to arrows.
3. The idiom is using "flies" to refer to time passing quickly in an abstract sense, similar to an arrow moving swiftly through space.
The key challenges with natural language understanding are ambiguity and context. Even a short phrase like this one could have multiple meanings without additional context clues. Determining the intended interpretation requires commonsense reasoning abilities that computers still lack
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
আমাদের সবার জন্য খুব খুব গুরুত্বপূর্ণ একটি বই ..বিসিএস, ব্যাংক, ইউনিভার্সিটি ভর্তি ও যে কোন প্রতিযোগিতা মূলক পরীক্ষার জন্য এর খুব ইম্পরট্যান্ট একটি বিষয় ...তাছাড়া বাংলাদেশের সাম্প্রতিক যে কোন ডাটা বা তথ্য এই বইতে পাবেন ...
তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
বিসিএস ও ব্যাংক এর লিখিত পরীক্ষা ...+এছাড়া মাধ্যমিক ও উচ্চমাধ্যমিকের স্টুডেন্টদের জন্য অনেক কাজে আসবে ...
How to Make a Field Mandatory in Odoo 17Celine George
In Odoo, making a field required can be done through both Python code and XML views. When you set the required attribute to True in Python code, it makes the field required across all views where it's used. Conversely, when you set the required attribute in XML views, it makes the field required only in the context of that particular view.
How to Fix the Import Error in the Odoo 17Celine George
An import error occurs when a program fails to import a module or library, disrupting its execution. In languages like Python, this issue arises when the specified module cannot be found or accessed, hindering the program's functionality. Resolving import errors is crucial for maintaining smooth software operation and uninterrupted development processes.
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
Walmart Business+ and Spark Good for Nonprofits.pdfTechSoup
"Learn about all the ways Walmart supports nonprofit organizations.
You will hear from Liz Willett, the Head of Nonprofits, and hear about what Walmart is doing to help nonprofits, including Walmart Business and Spark Good. Walmart Business+ is a new offer for nonprofits that offers discounts and also streamlines nonprofits order and expense tracking, saving time and money.
The webinar may also give some examples on how nonprofits can best leverage Walmart Business+.
The event will cover the following::
Walmart Business + (https://business.walmart.com/plus) is a new shopping experience for nonprofits, schools, and local business customers that connects an exclusive online shopping experience to stores. Benefits include free delivery and shipping, a 'Spend Analytics” feature, special discounts, deals and tax-exempt shopping.
Special TechSoup offer for a free 180 days membership, and up to $150 in discounts on eligible orders.
Spark Good (walmart.com/sparkgood) is a charitable platform that enables nonprofits to receive donations directly from customers and associates.
Answers about how you can do more with Walmart!"
The simplified electron and muon model, Oscillating Spacetime: The Foundation...RitikBhardwaj56
Discover the Simplified Electron and Muon Model: A New Wave-Based Approach to Understanding Particles delves into a groundbreaking theory that presents electrons and muons as rotating soliton waves within oscillating spacetime. Geared towards students, researchers, and science buffs, this book breaks down complex ideas into simple explanations. It covers topics such as electron waves, temporal dynamics, and the implications of this model on particle physics. With clear illustrations and easy-to-follow explanations, readers will gain a new outlook on the universe's fundamental nature.
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This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
This presentation was provided by Steph Pollock of The American Psychological Association’s Journals Program, and Damita Snow, of The American Society of Civil Engineers (ASCE), for the initial session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session One: 'Setting Expectations: a DEIA Primer,' was held June 6, 2024.
ISO/IEC 27001, ISO/IEC 42001, and GDPR: Best Practices for Implementation and...PECB
Denis is a dynamic and results-driven Chief Information Officer (CIO) with a distinguished career spanning information systems analysis and technical project management. With a proven track record of spearheading the design and delivery of cutting-edge Information Management solutions, he has consistently elevated business operations, streamlined reporting functions, and maximized process efficiency.
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Date: May 29, 2024
Tags: Information Security, ISO/IEC 27001, ISO/IEC 42001, Artificial Intelligence, GDPR
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Executive Directors Chat Leveraging AI for Diversity, Equity, and InclusionTechSoup
Let’s explore the intersection of technology and equity in the final session of our DEI series. Discover how AI tools, like ChatGPT, can be used to support and enhance your nonprofit's DEI initiatives. Participants will gain insights into practical AI applications and get tips for leveraging technology to advance their DEI goals.
2. Artificial Intelligence"
•
•
•
•
Lecturer: Phạm Bảo Sơn!
Email: sonpb@vnu.edu.vn!
Consultations: via email or after lecture.!
Course website: bbc.vnu.edu.vn !
!www.coltech.vnu.edu.vn/~sonpb/AI !
AI 2011
2
3. Readings"
• Textbook: !
– S. Russel and P. Norvig: Artificial Intelligence: A
Modern Approach. Prentice-Hall, Second edition. !
• Reference books: !
– Ben Coppin: Artificial Intelligence Illuminated,
Jones and Bartlett Publishers 2004. !
AI 2011
3
5. Assessment"
• C: Class mark:!
– Assignments!
– Attendance and participation. !
• E: Exam!
• F: Final mark!
!F = C*40% + E*60%!
AI 2011
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6. Policy "
• Encourage discussion but assignments
must be your individual work!
• Codes copied from books or other
libraries but be explicitly acknowledged!
• Sharing or copying codes is strictly
prohibited. !
AI 2011
6
8. AI Systems
"
• Watson is a Question answering (QA) computing system built by
IBM.[2] IBM describes it as "an application of advanced Natural
Language Processing, Information Retrieval, Knowledge
Representation and Reasoning, and Machine Learning
technologies to the field of open domain question answering"
which is "built on IBM's DeepQA technology for hypothesis
generation, massive evidence gathering, analysis, and scoring.!
AI 2011
8
9. What is AI?"
• The exciting new effort to make computers think …
machine with minds, in the full and literal sense.!
• The study of mental faculties through the use of
computational models!
• The art of creating machines that perform functions
that require intelligence when performed by people.!
• AI … is concerned with intelligent behaviour in
artifacts.!
AI 2011
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10. What is AI?"
Views of AI fall into four categories:!
rationality vs. human (human are not
perfect)!
acting vs. thinking!
!Thinking humanly!Thinking rationally !
!Acting humanly !Acting rationally !
AI 2011
10
11. Acting humanly: Turing Test"
• Turing (1950) "Computing machinery and intelligence":!
• "Can machines think?" à "Can machines behave intelligently?"!
• Operational test for intelligent behavior: the Imitation Game!
!
!
• Predicted that by 2000, a machine might have a 30% chance of
fooling a lay person for 5 minutes!
• Suggested major components of AI: knowledge, reasoning,
language understanding, learning!
!
AI 2011
11
12. Thinking humanly: cognitive
modeling"
!
• Requires scientific theories of internal activities of the
brain!
– Introspection!
– Psychological experiments !
• -- How to validate? Requires !
1) Predicting and testing behavior of human subjects (topdown)!
or 2) Direct identification from neurological data (bottom-up)!
• Both approaches (roughly, Cognitive Science and
Cognitive Neuroscience) are now distinct from AI!
!
AI 2011
12
13. Thinking rationally: Laws of
thought"
• Aristotle: what are correct arguments/thought
processes?!
• Several Greek schools developed various forms of
logic: notation and rules of derivation for thoughts;
may or may not have proceeded to the idea of
mechanization!
• Direct line through mathematics and philosophy to
modern AI!
• Problems: !
1. Not all intelligent behavior is mediated by logical deliberation!
2. What is the purpose of thinking? What thoughts should I
have out of all the thoughts that I could have?!
!
AI 2011
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14. Acting rationally"
• Rational behavior: doing the right thing!
• The right thing: that which is expected
to maximize goal achievement, given
the available information!
• Doesn't necessarily involve thinking –
e.g., blinking reflex – but thinking
should be in the service of rational
action!
!
AI 2011
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15. Abridged history of AI"
•
•
•
•
•
•
•
•
•
•
•
1943
1950
1956!
1950s
!
!
1958!
1966—73
!
1969—79
1980-1986-!
1987-1995--
!McCulloch & Pitts: Boolean circuit model of brain!
!Turing's "Computing Machinery and Intelligence"!
!Dartmouth meeting: "Artificial Intelligence" adopted!
!Early AI programs, including Samuel's checkers
!program, Newell & Simon's Logic Theorist,
!Gelernter's Geometry Engine!
!McCarthy invented LISP programming language.!
!AI discovers computational complexity: scaling up prob.
!Neural network research almost disappears!
!Early development of knowledge-based systems!
!AI becomes an industry !
!Neural networks return to popularity: back-propagation
!learning algorithm!
!AI becomes a science !
!The emergence of intelligent agents!
AI 2011
15
16. State of the art"
•
Deep Blue defeated the reigning world chess champion Garry
Kasparov in 1997.!
• Deep Fritz defeated Kramnik in 2006.!
• Watson defeated best human player in Jeopardy! In 2011. !
• Proved a mathematical conjecture (Robbins conjecture) unsolved for
decades !
• No hands across America (driving autonomously 98% of the time from
Pittsburgh to San Diego) !
• During the 1991 Gulf War, US forces deployed an AI logistics planning
and scheduling program that involved up to 50,000 vehicles, cargo, and
people !
• NASA's on-board autonomous planning program controlled the
scheduling of operations for a spacecraft !
• Proverb solves crossword puzzles better than most humans!
AI 2011
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