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Artificial Intelligence (A.I) and Its Application -Seminar

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Artificial Intelligence (A.I) and Its Application -Seminar

  1. 1. A Seminar on Artificial Intelligence BY : BIJAY KUMAR NAYAK
  2. 2. • Introduction • Branches • Workflow • Why AI • Structural Design/Components • Advantages & Disadvantages • Applications • Future Scope • Conclusion Contents
  3. 3. Artificial intelligence is a study that aims to create intelligent machines. It has become an essential part of the technology industry. Definition What is an Intelligent machine Machine Capable of learning and implementing itself. Artificial Intelligence
  4. 4. Brain VS Computer
  5. 5. Branches
  6. 6. Neural Networks Neural Network uses the examples to automatically infer rules for recognizing handwritten digits
  7. 7. Machine Learning Machine learning is a field of computer science that uses statistical techniques to give computer systems the ability to "learn" with data, without being explicitly programmed
  8. 8. With deep networks we can perform feature extraction and classification in one shot, which means we only have to design one model Machine Learning
  9. 9. •Cognitive computing : is a subfield of AI that strives for a natural, human-like interaction with machines. Using AI and cognitive computing, the ultimate goal is for a machine to simulate human processes through the ability to interpret images and speech – and then speak coherently in response. •Computer vision : relies on pattern recognition and deep learning to recognize what’s in a picture or video. When machines can process, analyze and understand images, they can capture images or videos in real time and interpret their surroundings. •Natural language processing (NLP) : is the ability of computers to analyze, understand and generate human language, including speech. The next stage of NLP is natural language interaction, which allows humans to communicate with computers using normal, everyday language to perform tasks. Cont.
  10. 10. How AI Works AI works by combining large amounts of data with fast, iterative processing and intelligent algorithms, allowing the software to learn automatically from patterns or features in the data Neural Network Deep learning Cognitive computing Computer vision Natural language processing Machine learning
  11. 11. WHY AI? WHY NOW? • Automated • Error Free • Efficiency • Better Data Processing • Low latency • Time Saving
  12. 12. COMPONENTS USED TPU Rasphberry Pi
  13. 13. • Dynamic • Reprogrammable • Self Awareness • Self correction • No Movement • Static • Movable • Single Use • No Self Control
  14. 14. Source:
  15. 15. Pros & Cons: • Error Reduction • Difficult Exploration • Daily Application • Digital Assistants • No breaks • Increase Work Efficiency • Reduce cost of training and operation • High Cost • No Replicating Humans • Lesser Jobs • Lack of Personal Connections • Addiction • Efficient Decision Making
  16. 16. Security Features A.I is more secure with Banking level security uses 2014 bit encryption. So it will take billions of year to decode a single letter with out actual key.
  17. 17. Applications • Self driving Vehicle • Aviation • Computer science • Education • Finance • Satellite Data Processing • Heavy industry • Hospitals and medicine • Human resources and recruiting • Marketing • Media • Music • News, publishing and writing • Online and telephone customer service • Toys and games • Transportation
  18. 18. A.I In Electrical Engineering • Diagnosis of Electrical machines and drives • Synchronous Control over electrical machine. • Reduced Fault rate
  19. 19. Typical problems to which AI methods are applied • Optical character recognition • Handwriting recognition • Speech recognition • Face recognition • Artificial creativity • Computer vision, Virtual reality, and Image processing • Photo and Video manipulation • Diagnosis (artificial intelligence) • Game theory and Strategic planning • Game artificial intelligence and Computer game bot • Natural language processing, Translation and Chatterbots • Nonlinear control and Robotics Other fields in which AI methods are implemented • Artificial life • Automated reasoning • Automation • Biologically inspired computing • Concept mining • Data mining • Knowledge representation • Semantic Web • E-mail spam filtering • Robotics • Behavior-based robotics • Cognitive • Cybernetics • Developmental robotics (Epigenetic) • Evolutionary robotics • Hybrid intelligent system • Intelligent agent • Intelligent control • Litigation
  20. 20. Future Scope • Soaring Demand for AI Professionals • Novel Career Paths • Earning Potential • Cyber Security Since Its started, Industries are switching over to AI based solution with every small task to save time and engaged their engineers with AI features development. In future AI also can replace human in some common tasks with more security and speed
  21. 21. 1. https://ieeexplore.ieee.org/document/1201096/ 2. https://ieeexplore.ieee.org/document/260875/ 3. https://data-flair.training/blogs/artificial-intelligence-advantages-disadvantages/ 4. https://www.pantechsolutions.net/blog/machine-learning-projects-and-ideas/ 5. https://www.sas.com/en_us/insights/analytics/what-is-artificial-intelligence.html 6. http://www-formal.stanford.edu/jmc/whatisai/node3.html 7. https://en.wikipedia.org/wiki/Applications_of_artificial_intelligence 8. Artificial Intelligence: A Modern Approach by Peter Norvig and Stuart J. Russell 9. https://searchenterpriseai.techtarget.com/definition/AI-Artificial-Intelligence 10. https://ai.google/education/ References

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