Artificial Intelligence Introduction.pptx
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Artificial intelligence is defined as a man-made thinking power. It exists when a machine can have human skills like learning, reasoning, and problem solving. Examples of AI include autonomous spacecraft planning, beating a chess grandmaster, driverless cars, language understanding, robotic surgery assistants, and monitoring the stock market. Problem-solving agents in AI use search techniques and algorithms to rationally solve problems and provide optimal results.
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Artificial Intelligence Introduction.pptx
Artificial intelligence is defined as a man-made thinking power, where machines can have human skills like learning, reasoning, and problem solving. Examples of AI include autonomous spacecraft planning, beating humans at chess, driverless cars, language understanding, robotic surgery assistants, and monitoring the stock market. In AI, problem-solving agents use search techniques and algorithms to rationally solve problems and provide optimal results.
ai hello ppt.pptx
Artificial Intelligence is composed of two words - Artificial and Intelligence. Artificial means 'man-made' and Intelligence means 'thinking power', so together AI means 'a man-made thinking power'. Artificial Intelligence exists when a machine can have human skills like learning, reasoning, and solving problems. Examples of AI include autonomous planning on spacecraft, beating Kasparov at chess, driverless cars, language understanding, robotic surgery assistants, and monitoring stock markets for insider trading. Problem-solving agents in AI use search techniques and algorithms to rationally solve problems and provide optimal results.
Artificial Intelligence Introduction.pptx.pdf
Artificial intelligence is defined as man-made thinking power. It exists when a machine can learn, reason, and solve problems like humans. Some applications of AI include autonomous spacecraft planning, beating humans at chess, driverless cars, language understanding, robotic surgery assistants, and monitoring the stock market. The goals of AI include problem solving using search techniques and algorithms to find the best solutions.
Copy of Artificial Intelligence Introduction.pptx
Artificial intelligence is defined as human-made thinking power. It involves machines that can learn, reason, and solve problems like humans. The history of AI began with early attempts at problem solving. Modern applications of AI include autonomous spacecraft, beating humans at chess, self-driving cars, language translation, robotic surgery assistants, and monitoring the stock market. The goals of AI are problem solving using search techniques and algorithms to find the best solutions.
Unit1_AI&ML (2).pptx
An agent that helps users complete tasks through natural language conversations. Examples include Siri, Alexa, Cortana.
Autonomous: An agent that acts independently in an environment to achieve goals. Self-driving cars are autonomous agents.
Bots: Software applications that run automated tasks over the internet. Examples include chatbots, web crawlers, trading bots.
Collaborative: Agents that work together with humans or other agents towards a common goal. Drones that assist firefighters are collaborative agents.
Adaptive: Agents that learn from their environment and experiences over time to improve their performance. Recommendation systems are adaptive agents.
So in summary, the key types are: Assistant, Autonomous, Bots,
Lecture 1
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.
Lecture 1. Introduction to AI and it's applications.ppt
This document provides an introduction to artificial intelligence, including definitions of AI, its goals, approaches, and applications. It defines AI as the science and engineering of making intelligent machines, and discusses goals like replicating human intelligence and developing systems that think and act rationally. The document outlines different approaches to AI like hard/strong AI, soft/weak AI, applied AI, and cognitive AI. It also discusses major components and applications of AI like perception, robotics, natural language processing, planning, and machine learning.
What is Ai ?
There is a big confusion between Ai and ML. The efforts towards achieving Ai will become futile due to the lack of understanding of the basic Ai
Recommended
Artificial Intelligence Introduction.pptx
Artificial intelligence is defined as a man-made thinking power, where machines can have human skills like learning, reasoning, and problem solving. Examples of AI include autonomous spacecraft planning, beating humans at chess, driverless cars, language understanding, robotic surgery assistants, and monitoring the stock market. In AI, problem-solving agents use search techniques and algorithms to rationally solve problems and provide optimal results.
ai hello ppt.pptx
Artificial Intelligence is composed of two words - Artificial and Intelligence. Artificial means 'man-made' and Intelligence means 'thinking power', so together AI means 'a man-made thinking power'. Artificial Intelligence exists when a machine can have human skills like learning, reasoning, and solving problems. Examples of AI include autonomous planning on spacecraft, beating Kasparov at chess, driverless cars, language understanding, robotic surgery assistants, and monitoring stock markets for insider trading. Problem-solving agents in AI use search techniques and algorithms to rationally solve problems and provide optimal results.
Artificial Intelligence Introduction.pptx.pdf
Artificial intelligence is defined as man-made thinking power. It exists when a machine can learn, reason, and solve problems like humans. Some applications of AI include autonomous spacecraft planning, beating humans at chess, driverless cars, language understanding, robotic surgery assistants, and monitoring the stock market. The goals of AI include problem solving using search techniques and algorithms to find the best solutions.
Copy of Artificial Intelligence Introduction.pptx
Artificial intelligence is defined as human-made thinking power. It involves machines that can learn, reason, and solve problems like humans. The history of AI began with early attempts at problem solving. Modern applications of AI include autonomous spacecraft, beating humans at chess, self-driving cars, language translation, robotic surgery assistants, and monitoring the stock market. The goals of AI are problem solving using search techniques and algorithms to find the best solutions.
Unit1_AI&ML (2).pptx
An agent that helps users complete tasks through natural language conversations. Examples include Siri, Alexa, Cortana.
Autonomous: An agent that acts independently in an environment to achieve goals. Self-driving cars are autonomous agents.
Bots: Software applications that run automated tasks over the internet. Examples include chatbots, web crawlers, trading bots.
Collaborative: Agents that work together with humans or other agents towards a common goal. Drones that assist firefighters are collaborative agents.
Adaptive: Agents that learn from their environment and experiences over time to improve their performance. Recommendation systems are adaptive agents.
So in summary, the key types are: Assistant, Autonomous, Bots,
Lecture 1
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.
Lecture 1. Introduction to AI and it's applications.ppt
This document provides an introduction to artificial intelligence, including definitions of AI, its goals, approaches, and applications. It defines AI as the science and engineering of making intelligent machines, and discusses goals like replicating human intelligence and developing systems that think and act rationally. The document outlines different approaches to AI like hard/strong AI, soft/weak AI, applied AI, and cognitive AI. It also discusses major components and applications of AI like perception, robotics, natural language processing, planning, and machine learning.
What is Ai ?
There is a big confusion between Ai and ML. The efforts towards achieving Ai will become futile due to the lack of understanding of the basic Ai
Understanding ai
The document provides an overview of artificial intelligence, including definitions of AI, different types of AI that focus on modeling how humans think and act or how ideal agents should think and act, areas of AI research, knowledge representation, and expert systems. It discusses challenges in acquiring and representing knowledge for expert systems and controlling reasoning.
Understanding ai
Thinking machines and artificial beings appear in Greek myths, such as Talos of Crete, the bronze robot of Hephaestus, and Pygmalion's Galatea.[14] Human likenesses believed to have intelligence were built in every major civilization: animated cult images were worshipped in Egypt and Greece[15] and humanoid automatons were built by Yan Shi, Hero of Alexandria and Al-Jazari.[16] It was also widely believed that artificial beings had been created by Jābir ibn Hayyān, Judah Loew and Paracelsus.[17] By the 19th and 20th centuries, artificial beings had become a common feature in fiction, as in Mary Shelley's Frankenstein or Karel Čapek's R.U.R. (Rossum's Universal Robots).[18] Pamela McCorduck argues that all of these are examples of an ancient urge, as she describes it, "to forge the gods".[7] Stories of these creatures and their fates discuss many of the same hopes, fears and ethical concerns that are presented by artificial intelligence.
Mechanical or "formal" reasoning has been developed by philosophers and mathematicians since antiquity. The study of logic led directly to the invention of the programmable digital electronic computer, based on the work of mathematician Alan Turing and others. Turing's theory of computation suggested that a machine, by shuffling symbols as simple as "0" and "1", could simulate any conceivable act of mathematical deduction.[19][20] This, along with concurrent discoveries in neurology, information theory and cybernetics, inspired a small group of researchers to begin to seriously consider the possibility of building an electronic brain.[21]
The field of AI research was founded at a conference on the campus of Dartmouth College in the summer of 1956.[22] The attendees, including John McCarthy, Marvin Minsky, Allen Newell and Herbert Simon, became the leaders of AI research for many decades.[23] They and their students wrote programs that were, to most people, simply astonishing:[24] computers were solving word problems in algebra, proving logical theorems and speaking English.[25] By the middle of the 1960s, research in the U.S. was heavily funded by the Department of Defense[26] and laboratories had been established around the world.[27] AI's founders were profoundly optimistic about the future of the new field: Herbert Simon predicted that "machines will be capable, within twenty years, of doing any work a man can do" and Marvin Minsky agreed, writing that "within a generation ... the problem of creating 'artificial intelligence' will substantially be solved".[28]
They had failed to recognize the difficulty of some of the problems they faced.[29] In 1974, in response to the criticism of Sir James Lighthill and ongoing pressure from the US Congress to fund more productive projects, both the U.S. and British governments cut off all undirected exploratory research in AI. The next few years, when funding for projects was hard to find, would later be called the "AI winter".[30]
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This document provides an introduction to artificial intelligence including definitions, history, types, and applications. It defines AI as making computers think intelligently like humans by studying brain patterns. The history of AI began in the 1940s and 50s with the term being coined in 1956. There are three main types: artificial narrow intelligence which performs single tasks; artificial general intelligence that can learn and think broadly like humans; and artificial super intelligence that is more potent than human intelligence. AI has many important applications and major branches including computer vision, robotics, and learning systems.
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This document provides an overview of an artificial intelligence course. The course aims to help students understand basic AI concepts, apply concepts to solve problems, and design algorithms to address real-world issues. Assessment includes assignments, quizzes, midterms, and a final exam. The textbook is "Artificial Intelligence: A Modern Approach." Topics covered include intelligent agents, problem solving, search techniques, constraint satisfaction, knowledge representation, planning, uncertainty, learning, neural networks, perception, and robotics.
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The document introduces artificial intelligence (AI), defining it as human-made thinking power. It describes the history and eras of AI development, different types and approaches of AI including weak AI, strong AI, and super AI. Furthermore, it discusses applications of AI and factors influencing recent advancement, and identifies areas of ongoing AI research focus.
Intro artificial intelligence
Artificial intelligence (AI) is concerned with designing intelligent systems, with two key aspects - intelligence and an artificial device. There are different views on what constitutes intelligence - emulating human thought processes, passing the Turing test of indistinguishability from humans, focusing on logical reasoning abilities, or acting rationally to achieve goals. AI research involves problems like perception, reasoning, learning, language understanding, problem-solving and robotics. While today's AI can achieve limited success in tasks like computer vision, robotics, translation and games, it still cannot match human-level abilities in areas like language understanding, planning, learning or exhibiting true autonomy. The history of AI began in the 1950s and has progressed through periods focused on games
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Artificial intelligence (AI) is defined as the intelligence exhibited by machines or software. It involves the study and design of intelligent agents that can perceive their environment and take actions to maximize their success. There are four schools of thought on AI: thinking humanly, thinking rationally, acting humanly, and acting rationally. AI draws from many fields including mathematics, computer science, philosophy, linguistics, psychology, economics, and sociology. Some applications of AI include smart search algorithms, natural language processing for tasks like machine translation and summarization, knowledge bases for expert systems and medical diagnosis, and machine learning for tasks like face recognition and autonomous vehicles.
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The document discusses artificial intelligence and defines it as systems that can act rationally, think rationally, think like humans, or act like humans. It notes approaches of AI include acting humanly, thinking humanly, thinking rationally, and acting rationally. The goals of AI are to make computers more useful by automating dangerous or tedious tasks and to understand principles of human intelligence. Current applications discussed include autonomous vehicles, speech recognition, game playing, logistics planning, robotics, and machine translation.
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The document discusses different types of artificial intelligence including narrow AI, general AI, and super AI. It provides examples of narrow AI systems like Siri, Watson, self-driving cars, and algorithms for tasks like chess-playing or image recognition. General AI aims to achieve human-level intelligence across all domains but currently does not exist. Super AI could potentially surpass human abilities but is still hypothetical. The document also covers reactive systems, limited memory systems, and potential future developments in theory of mind and self-aware AI.
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This document explains a brief introduction to Artificial Intelligence. This document can help university students in their studies.
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Given above is a PowerPoint Presentation on Artificial Intelligence (AI). Ideal for activities, school projects, essays etc. Hope it is accommodating.
Thank you.
You can also find out my other presentations on Technology.
The links are given below-
https://www.slideshare.net/GursheenKaurChawla/all-about-the-internetpptx and https://www.slideshare.net/GursheenKaurChawla/impact-of-online-gamespptx
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https://medium.com/@Artificialintelligencecourse/artificial-intelligence-course-in-janakpuri-84ee9caaddb
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Artificial intelligence has developed over decades through the work of many researchers. While the concept dates back to ancient times, AI as a scientific field began taking shape in the mid-20th century. John McCarthy is considered the father of AI, coining the term in 1956 and helping establish it as a field along with scientists like Turing, Newell, and Simon. AI involves simulating human intelligence with machines and has applications in areas like expert systems, language processing, and machine vision. Examples include manufacturing robots, self-driving cars, smart assistants, and automated investing. Tests of AI include the Turing test and imitation game. While AI promises benefits, concerns exist around job losses, costs, and how humans will relate to
Artificial intelligence introduction
Artificial intelligence (AI) is the ability of machines to mimic human intelligence and behavior. The document discusses the history and foundations of AI, including attempts to define intelligence and understand how the human brain works. It outlines four approaches to AI: systems that act humanly by passing the Turing test, systems that think humanly by modeling cognitive processes, and systems that act or think rationally. The document also discusses intelligent agents, knowledge-based systems, and applications of AI such as game playing and machine translation.
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Thinking machines and artificial beings appear in Greek myths, such as Talos of Crete, the bronze robot of Hephaestus, and Pygmalion's Galatea.[14] Human likenesses believed to have intelligence were built in every major civilization: animated cult images were worshipped in Egypt and Greece[15] and humanoid automatons were built by Yan Shi, Hero of Alexandria and Al-Jazari.[16] It was also widely believed that artificial beings had been created by Jābir ibn Hayyān, Judah Loew and Paracelsus.[17] By the 19th and 20th centuries, artificial beings had become a common feature in fiction, as in Mary Shelley's Frankenstein or Karel Čapek's R.U.R. (Rossum's Universal Robots).[18] Pamela McCorduck argues that all of these are examples of an ancient urge, as she describes it, "to forge the gods".[7] Stories of these creatures and their fates discuss many of the same hopes, fears and ethical concerns that are presented by artificial intelligence.
Mechanical or "formal" reasoning has been developed by philosophers and mathematicians since antiquity. The study of logic led directly to the invention of the programmable digital electronic computer, based on the work of mathematician Alan Turing and others. Turing's theory of computation suggested that a machine, by shuffling symbols as simple as "0" and "1", could simulate any conceivable act of mathematical deduction.[19][20] This, along with concurrent discoveries in neurology, information theory and cybernetics, inspired a small group of researchers to begin to seriously consider the possibility of building an electronic brain.[21]
The field of AI research was founded at a conference on the campus of Dartmouth College in the summer of 1956.[22] The attendees, including John McCarthy, Marvin Minsky, Allen Newell and Herbert Simon, became the leaders of AI research for many decades.[23] They and their students wrote programs that were, to most people, simply astonishing:[24] computers were solving word problems in algebra, proving logical theorems and speaking English.[25] By the middle of the 1960s, research in the U.S. was heavily funded by the Department of Defense[26] and laboratories had been established around the world.[27] AI's founders were profoundly optimistic about the future of the new field: Herbert Simon predicted that "machines will be capable, within twenty years, of doing any work a man can do" and Marvin Minsky agreed, writing that "within a generation ... the problem of creating 'artificial intelligence' will substantially be solved".[28]
They had failed to recognize the difficulty of some of the problems they faced.[29] In 1974, in response to the criticism of Sir James Lighthill and ongoing pressure from the US Congress to fund more productive projects, both the U.S. and British governments cut off all undirected exploratory research in AI. The next few years, when funding for projects was hard to find, would later be called the "AI winter".[30]
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Artificial intelligence (AI)
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This document provides an introduction to artificial intelligence including definitions, history, types, and applications. It defines AI as making computers think intelligently like humans by studying brain patterns. The history of AI began in the 1940s and 50s with the term being coined in 1956. There are three main types: artificial narrow intelligence which performs single tasks; artificial general intelligence that can learn and think broadly like humans; and artificial super intelligence that is more potent than human intelligence. AI has many important applications and major branches including computer vision, robotics, and learning systems.
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This document provides an overview of an artificial intelligence course. The course aims to help students understand basic AI concepts, apply concepts to solve problems, and design algorithms to address real-world issues. Assessment includes assignments, quizzes, midterms, and a final exam. The textbook is "Artificial Intelligence: A Modern Approach." Topics covered include intelligent agents, problem solving, search techniques, constraint satisfaction, knowledge representation, planning, uncertainty, learning, neural networks, perception, and robotics.
Artificial intelligence
The document provides an introduction to artificial intelligence (AI), including definitions of AI, descriptions of the eras of AI development, types of AI approaches, and applications of AI. It discusses factors that have influenced recent advancement in AI and identifies areas of AI research focus. The summary is:
The document introduces artificial intelligence (AI), defining it as human-made thinking power. It describes the history and eras of AI development, different types and approaches of AI including weak AI, strong AI, and super AI. Furthermore, it discusses applications of AI and factors influencing recent advancement, and identifies areas of ongoing AI research focus.
Intro artificial intelligence
Artificial intelligence (AI) is concerned with designing intelligent systems, with two key aspects - intelligence and an artificial device. There are different views on what constitutes intelligence - emulating human thought processes, passing the Turing test of indistinguishability from humans, focusing on logical reasoning abilities, or acting rationally to achieve goals. AI research involves problems like perception, reasoning, learning, language understanding, problem-solving and robotics. While today's AI can achieve limited success in tasks like computer vision, robotics, translation and games, it still cannot match human-level abilities in areas like language understanding, planning, learning or exhibiting true autonomy. The history of AI began in the 1950s and has progressed through periods focused on games
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Artificial intelligence (AI) is defined as the intelligence exhibited by machines or software. It involves the study and design of intelligent agents that can perceive their environment and take actions to maximize their success. There are four schools of thought on AI: thinking humanly, thinking rationally, acting humanly, and acting rationally. AI draws from many fields including mathematics, computer science, philosophy, linguistics, psychology, economics, and sociology. Some applications of AI include smart search algorithms, natural language processing for tasks like machine translation and summarization, knowledge bases for expert systems and medical diagnosis, and machine learning for tasks like face recognition and autonomous vehicles.
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The document discusses different types of artificial intelligence including narrow AI, general AI, and super AI. It provides examples of narrow AI systems like Siri, Watson, self-driving cars, and algorithms for tasks like chess-playing or image recognition. General AI aims to achieve human-level intelligence across all domains but currently does not exist. Super AI could potentially surpass human abilities but is still hypothetical. The document also covers reactive systems, limited memory systems, and potential future developments in theory of mind and self-aware AI.
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This document explains a brief introduction to Artificial Intelligence. This document can help university students in their studies.
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Given above is a PowerPoint Presentation on Artificial Intelligence (AI). Ideal for activities, school projects, essays etc. Hope it is accommodating.
Thank you.
You can also find out my other presentations on Technology.
The links are given below-
https://www.slideshare.net/GursheenKaurChawla/all-about-the-internetpptx and https://www.slideshare.net/GursheenKaurChawla/impact-of-online-gamespptx
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This document provides an overview of artificial intelligence (AI), including its history, applications, advantages, and disadvantages. It discusses early milestones in AI like the Turing Test (1950) and Logic Theorist (1956). Applications mentioned include agriculture, astronomy, gaming, robotics, and more. Advantages are high speed, reliability in risky situations. Disadvantages include high costs, inability to think outside programmed tasks, and lack of emotions. The conclusion states AI could solve many problems and unlock a future where computers make more informed decisions based on understanding our world through data.
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This document provides an introduction to artificial intelligence. It defines intelligence as the ability to solve problems, think, plan, learn, recognize patterns, and handle ambiguous situations. The document then asks if machines can exhibit these intelligent behaviors such as searching meshes, solving sequences, developing plans, diagnosing issues, answering questions, recognizing fingerprints, understanding concepts, and perceiving the world. It states that the goal of AI is to create systems that can learn, think, perceive, analyze and act like humans. Early work in AI included the development of programs that used logic to solve problems like humans. Current areas of AI research include computer vision, natural language processing, expert systems, robotics, and creating human-like robots.
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AI is based on the idea of creating intelligent machines that can perform tasks that typically require human intelligence. To achieve this, machines are designed and programmed to learn from data and experience, and then make decisions based on that learning. This is done through algorithms and mathematical models that simulate human thought processes and enable machines to learn and make predictions or decisions based on that learning.
https://medium.com/@Artificialintelligencecourse/artificial-intelligence-course-in-janakpuri-84ee9caaddb
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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.
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What is Artificial Intelligence(AI)? , Evolution , Applications of AI? , Features of AI , What is Intelligence and its types?,
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The document provides an overview of artificial intelligence (AI), including definitions, components, types, applications, and levels. It defines AI as using computer science to create intelligent machines that can behave and think like humans. Intelligence involves reasoning, learning, problem-solving, perception, and language understanding. AI systems are composed of agents that perceive their environment and act on it. Examples of AI applications include autonomous vehicles, medical diagnosis, games, and online assistants. Machine learning is an advanced form of AI that allows machines to learn from experience rather than being explicitly programmed. The document also discusses the history of AI and describes six levels and two main types.
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Artificial intelligence has developed over decades through the work of many researchers. While the concept dates back to ancient times, AI as a scientific field began taking shape in the mid-20th century. John McCarthy is considered the father of AI, coining the term in 1956 and helping establish it as a field along with scientists like Turing, Newell, and Simon. AI involves simulating human intelligence with machines and has applications in areas like expert systems, language processing, and machine vision. Examples include manufacturing robots, self-driving cars, smart assistants, and automated investing. Tests of AI include the Turing test and imitation game. While AI promises benefits, concerns exist around job losses, costs, and how humans will relate to
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Artificial intelligence (AI) is the ability of machines to mimic human intelligence and behavior. The document discusses the history and foundations of AI, including attempts to define intelligence and understand how the human brain works. It outlines four approaches to AI: systems that act humanly by passing the Turing test, systems that think humanly by modeling cognitive processes, and systems that act or think rationally. The document also discusses intelligent agents, knowledge-based systems, and applications of AI such as game playing and machine translation.
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This document describes using machine learning techniques to detect heart disease. It discusses applying data analytics methods like SVM and genetic algorithms to large datasets to better predict, prevent, and manage cardiovascular diseases. The proposed system aims to use these machine learning methods to predict heart attacks and reduce treatment costs by providing effective treatments. It evaluates models based on accuracy, elapsed time, and energy consumption to determine the best optimized prediction model.
Breast Cancer Detection.pptx
1) The document discusses a project on breast cancer detection using machine learning techniques. It aims to distinguish between malignant and benign tumors faster and more efficiently than existing methods.
2) The methodology uses a CNN classifier to automatically extract important features from images without preprocessing. It selects important features to reduce data complexity and size while increasing accuracy.
3) The results show the model can predict cancerous and non-cancerous cases accurately, helping detect breast cancer at earlier stages to improve treatment outcomes. It achieves over 97.4% accuracy.
Breast Cancer detection.pptx
This document discusses using machine learning for breast cancer detection. It begins with an introduction on breast cancer prevalence and existing machine learning methods. It then discusses breast cancer conditions in India, noting rising case numbers. Key factors in late diagnosis are identified as lack of awareness programs and low participation. The proposed methodology uses CNN for automated feature extraction to distinguish malignant from benign tumors faster. It describes preprocessing, augmentation, model testing and accuracy evaluation. Risk factors, signs, and prevention strategies are outlined. A schematic diagram and steps of the detection process are provided. The conclusion notes high accuracy achieved and potential for early detection to improve outcomes.
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Dive into the realm of operating systems (OS) with Pravash Chandra Das, a seasoned Digital Forensic Analyst, as your guide. 🚀 This comprehensive presentation illuminates the core concepts, types, and evolution of OS, essential for understanding modern computing landscapes.
Beginning with the foundational definition, Das clarifies the pivotal role of OS as system software orchestrating hardware resources, software applications, and user interactions. Through succinct descriptions, he delineates the diverse types of OS, from single-user, single-task environments like early MS-DOS iterations, to multi-user, multi-tasking systems exemplified by modern Linux distributions.
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The narrative then shifts to a captivating exploration of prominent desktop OSs, Windows, macOS, and Linux. Windows, with its globally ubiquitous presence and user-friendly interface, emerges as a cornerstone in personal computing history. macOS, lauded for its sleek design and seamless integration with Apple's ecosystem, stands as a beacon of stability and creativity. Linux, an open-source marvel, offers unparalleled flexibility and security, revolutionizing the computing landscape. 🖥️
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Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
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In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
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Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
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The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
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Artificial Intelligence Introduction.pptx
- 1. 1 Artificial Intelligence- An Introduction
- 2. 2 oArtificial Intelligence is composed of two words Artificial and Intelligence, where Artificial defines "man-made," and intelligence defines "thinking power", hence AI means "a man-made thinking power.“ oArtificial Intelligence exists when a machine can have human based skills such as learning, reasoning, and solving problems
- 3. 3
- 4. 4 •Autonomous planning and scheduling of tasks aboard a spacecraft •Beating Gary Kasparov in a chess match •Steering a driver-less car •Understanding language •Robotic assistants in surgery •Monitoring trade in the stock market to see if insider trading is going on
- 5. 5
- 6. 6 6/34 Problem solving oProblem-solving agents: oIn Artificial Intelligence, Search techniques are universal problem-solving methods. Rational agents or Problem-solving agents in AI mostly used these search strategies or algorithms to solve a specific problem and provide the best result.