Artificial intelligence
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This document provides an overview of artificial intelligence, including its history, approaches, tools, applications, advantages, and disadvantages. It discusses early approaches like statistical and cybernetics methods as well as modern symbolic and cognitive simulation techniques. The document also evaluates progress in AI using criteria from fields like science, engineering, mathematics, and philosophy. It describes current AI platforms and their economic impact. In conclusion, the document notes that while AI can solve problems intelligently, it also poses risks that must be carefully managed.
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Artificial intelligence
- 2. CONTENTS INTRODUCTION HISTORY APPROACHES TOOLS EVALUATING PROGRESS APPLICATIONS ADVANTAGES DISADVANTAGES FUTURE ASPECTS CONCLUSION
- 3. Artificial + Intelligence • Intelligence- Capacity to think and solve problems. • Artifcial Intelligence- Simulation of human intelligence by machine. a. Ability to solve problems b. Ability to act like humans c. Ability to think rationally.
- 8. Cybernetics and brain stimulation
- 9. Symbolic artificial intelligence is the term for the collection of all methods in artificial intelligence research that are based on high-level "symbolic" (human-readable) representations of problems, logic and search. John Haugeland gave the name GOFAI ("Good Old- Fashioned Artificial Intelligence") to symbolic AI in his 1985 book Artificial Intelligence: The Very Idea, which explored the philosophical implications of artificial intelligence research.
- 10. Cognitive simulation is an approach at computer science and design to manipulate artificial intelligence to think, behave and feel. The importance of this process is that it differs highly from previous approaches. CS takes into account human performance and error, and our ability to problem-solve. Straying from algorithms which can only calculate a single motive, either the ability to succeed or fail, CS takes the human approach to solving real world problems.
- 11. Once search for something with the use of the AI/SEO technology, the result displayed will remember a number of considerations like area, search history, favorite websites, and what other customers clicked on for the same query. Work based on logics and arguments provided to it. Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. Overview. Artificial neural networks (ANNs) are statistical models directly inspired by, and partially modeled on biological neural networks. They are capable of modeling and processing nonlinear relationships between inputs and outputs in parallel.
- 12. EVALUATING PROGRESS IN ARTIFICIAL INTELLIGENCE Most intellectual disciplines have standard, unquestioned criteria for what counts as progress. Artificial intelligence is an exception. It has always borrowed criteria, approaches, and specific methods from at least six fields: • 1. Science 2. Engineering 3. Mathematics 4. Philosophy 5. Design 6. Spectacle
- 14. PLATFORM OF AI
- 22. Economic impact
- 27. Conclusion AI is like two edged sword, on one hand they are able to solve problems intelligently and makes work more easier whereas on other hand they pose a problem themselves. So its our duty to handle them properly and with care, the sentence “MAN IS A MACHINE” supports the fact “MACHINE IS A MAN ” also.
- 28. THANK YOU