ARTIFICIAL INTELLIGENCE INTRODUCTION PART #2
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The document provides an overview of artificial intelligence (AI), covering its current status, goals, approaches, branches, and tools. It highlights applications in various fields like medicine, aviation, and education, focusing on advancements such as machine learning and natural language processing. Additionally, it discusses the importance of decision-making, motion planning, and emotional intelligence in AI systems.
ARTIFICIAL INTELLIGENCE INTRODUCTION PART #2
- 1. ARTIFICIAL INTELLIGENCE OVERVIEW OF AI—Part 2
- 2. CONTENTS • CURRENTSTATUS • GOALS • APPROACHES • BRANCHES • TOOLS USED • GENERALAIAGENTS • RESEARCHAREAS • TASK CLASSIFICATION
- 3. Society Welfare : Analyse Satellite images to identify poverty areas. Aviation Industry : Gate allocation for flight Air traffic control, Autopilot and Ticket price estimation system. Teaching: Companies creating Robots as teachers Current Status of AI
- 4. Current Status of AI Medicine and Surgery: Robots designed for complex surgeries and researches. Car Manufacturing: Robotic arms are used in car manufacturing units. Algorithms for Market analysis , Trading, Recommendations and Data mining.
- 5. Goals of AI • Increase Retention • Increase Outcomes • Lowers Cost • Increase Access • Decrease Time to completion
- 7. Branches OF AI To make machine as thinking agent. To build machine with the capability of making working assumption and common sense. Knowledge Representation To develop algorithms that human use. Algorithms can require enormous computational resources and problem goes beyond a certain size. Deduction, Reasoning and Problem solving
- 8. To develop Decision making ability. Multi-agent planning uses the cooperation and competition of many agents to achieve the given goal. Learning Machine learning is the fundamental concept of AI search. Unsupervised learning :is the ability to find patterns in inputs stream . Supervised learning : includes both classification and numerical regression. Deep learning is subset of M/c learning has networks of learning unsupervised from unstructured data. Planning BRANCHEs of AI
- 9. : Natural Language Processinggives machines the ability to read and understand human language. Common method of processing meaning from natural language is through semantic indexing. Machine perception is the ability to use input from sensors to deduce aspects of the world. Natural language Processing Perception BRANCHEs of AI
- 10. Motion Planning & Mapping Intelligence is required for robots to handle tasks such as object manipulation and navigation. Affective computing is the development of systems that can recognize, interpret, simulate human affects. Emotion and social skills are important to an intelligent agent to understand others and to make better decisions.... Social Intelligence BRANCHEs of AI
- 11. • Various Search & Optimization methods. • Statistical Methods. • Probabilistic Methods. • Artificial Neural Networks. AI Tools
- 12. • Various Search & Optimization methods. • Statistical Methods. • Probabilistic Methods. • Artificial Neural Networks. AI Tools
- 14. Research Areas OF AI ARTFICIAL INTELLIGENCE Expert System Natural language processing Neural Network Robotics Fuzzy Logic System
- 15. Research Areas of AI Expert system: Flight Tracking system, Clinical system etc. Natural language Processing: Google Now feature. Neural Network: Pattern Recognition systems like Face identification, character, handwriting and biometric scanning system etc. Robotics: Industrial robots for moving, spraying, painting, precision, checking, cleaning, drilling etc. Fuzzy Logic system: Consumer electronics, Automobiles .
- 16. Task classification IN AI