Lecture 1 Artificial-Intelligence-An-Overview.pptx

Foundations of Artificial Intelligence: An Overview Dr. Ravinder Kaur Assistant Professor DEIE  What Is Artificial Intelligence (AI)? Artificial Intelligence is composed of two words Artificial and Intelligence, where Artificial def...

Foundations of Artificial Intelligence: An Overview Dr. Ravinder Kaur Assistant Professor DEIE  What Is Artificial Intelligence (AI)? Artificial 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”. So, we can define AI as: "It is a branch of computer science by which we can create intelligent machines which can behave like a human, think like humans, and able to make decisions.“ Artificial intelligence is “The science and engineering of making intelligent machines, especially intelligent computer programs”. Artificial Intelligence is making a computer, a computer-controlled robot, or software to think intelligently, as the intelligent humans think. AI is accomplished by studying how the human brain thinks and how humans learn, decide, and work while trying to solve a problem, and then using the outcomes of this study as a basis of developing intelligent software and systems. What is Artificial Intelligence ? Making computers/machines that think? The automation of activities we associate with human thinking, like decision making, learning... ? The art of creating machines that perform functions that require intelligence when performed by people ? So, AI is defined as: –AI is the study of ideas that enable computers to be intelligent. –AI is the part of computer science concerned with design of computer systems that exhibit human intelligence(From the Concise Oxford Dictionary) From the above two definitions, we can see that AI has two major roles: –Study the intelligent part concerned with humans. –Represent those actions using computers. Goals of AI To make computers more useful by letting them take over dangerous or tedious tasks from human Understand principles of human intelligence  The Foundations of AI Philosophy (423 BC - present): -Logic, methods of reasoning. Mind as a physical system. -Foundations of learning, language, and rationality. Mathematics (c.800 - present): - Formal representation and proof. - Algorithms, computation, decidability, tractability. - Probability. Psychology (1879 - present): - Adaptation. - Phenomena of perception and motor control. -Experimental techniques. Linguistics (1957 - present): - Knowledge representation. - Grammar.  Artificial intelligence is a science and technology based on disciplines such as Computer Science, Biology, Psychology, Linguistics, Mathematics, and Engineering. A major thrust of AI is in the development of computer functions associated with human intelligence, such as reasoning, learning, and problem solving. Historical Foundation of Artificial Intelligence 1 1950s The term "artificial intelligence" is coined. Early AI research focuses on problem-solving and symbolic reasoning. 2 1960s-1970s Development of expert systems and early forms of machine learning, but progress is limited by computational power. 3 1980s-1990s Renewed interest in AI with the advent of neural networks and the rise of personal computers. 4 2000s-Present The "AI boom" with advances in deep learning, big data, and cloud computing, leading to widespread applications.  1950: Alan Turing develops the Turing test to see if a machine is perceived as intelligent. 1956: Scientific conference – the first time that simulated machines are referred to as "artificial intelligence". 1966: First Chatbot "ELIZA" is developed. 1972: MYCIN – Artificial intelligence is applied to mainstream medicine. A computer-based consultation system designed to assist physicians in the diagnosis of and therapy selection for patients with bacterial infections. 1997: Deep Blue – AI-based chess machine beats the world chess champion. 2011: Artificial intelligence is omnipresent – voice assistants are integrated into smartphones. 2023: ChatGPT revolutionizes the application field of chatbots. 20xx: Today, we can't quite imagine what AI will AI can be achieved in many ways- SCOPE OF AI Types of Artificial Intelligence  AI type-1: Based on Capabilities Weak AI or Narrow AI: Narrow AI is a type of AI which is able to perform a dedicated task with intelligence. The most common and currently available AI is Narrow AI in the world of Artificial Intelligence. Narrow AI cannot perform beyond its field or limitations, as it is only trained for one specific task. Hence it is also termed as weak AI. Narrow AI can fail in unpredictable ways if it goes beyond its limits. Apple Siri is a good example of Narrow AI, but it operates with a limited pre-defined range of functions. IBM's Watson supercomputer also comes under Narrow AI, as it uses an Expert system approach combined with Machine learning and natural language processing. Some Examples of Narrow AI are playing chess, purchasing suggestions on e-commerce site, self-driving cars, speech recognition, and image recognition. General AI: General AI is a type of intelligence which could perform any intellectual task with efficiency like a human. The idea behind the general AI to make such a system which could be smarter and think like a human by its own. Currently, there is no such system exist which could come under general AI and can perform any task as perfect as a human. The worldwide researchers are now focused on developing machines with General AI. As systems with general AI are still under research, and it will take lots of efforts and time to develop such systems. Super AI: Super AI is a level of Intelligence of Systems at which machines could surpass human intelligence, and can perform any task better than human with cognitive properties. It is an outcome of general AI. Some key characteristics of strong AI include capability include the ability to think, to reason,solve the puzzle, make judgments, plan, learn, and communicate by its own. Super AI is still a hypothetical concept of Artificial Intelligence. Development of such systems in real is still world changing task.  Artificial Intelligence type-2: Based on functionality Reactive Machines Purely reactive machines are the most basic types of Artificial Intelligence. Such AI systems do not store memories or past experiences for future actions. These machines only focus on current scenarios and react on it as per possible best action. IBM's Deep Blue system is an example of reactive machines. Google's AlphaGo is also an example of reactive machines, AlphaGo is a computer program that plays the board game Go.. (Go is an abstract strategy board game for two players in which the aim is to capture more territory than the opponent by fencing off empty space.) Limited Memory Limited memory machines can store past experiences or some data for a short period of time. These machines can use stored data for a limited time period only. Self-driving cars are one of the best examples of Limited Memory systems. These cars can store recent speed of nearby cars, the distance of other cars, speed limit, and other information to navigate the road. Theory of Mind Theory of Mind AI should understand the human emotions, people, beliefs, and be able to interact socially like humans. This type of AI machines are still not developed, but researchers are making lots of efforts and improvement for developing such AI machines. Self-Awareness Self-awareness AI is the future of Artificial Intelligence. These machines will be super intelligent, and will have their own consciousness, sentiments, and self-awareness. These machines will be smarter than human mind. Self-Awareness AI does not exist in reality still and it is a hypothetical concept.  Applications of AI Artificial Intelligence has various applications in today's society. It is becoming essential for today's time because it can solve complex problems with an efficient way in multiple industries, such as Healthcare, entertainment, finance, education, etc. AI is making our daily life more comfortable and fast.  KEY RESEARCH AREAS IN AI  Problem solving, planning, and search --- generic problem solving  architecture based on ideas from cognitive science (game playing, robotics).  Knowledge Representation – to store and manipulate information (logical and probabilistic representations)  Automated reasoning / Inference – to use the stored information to answer questions and draw new conclusions  Machine Learning – intelligence from data; to adapt to new  circumstances and to detect and extrapolate patterns  Natural Language Processing – to communicate with the machine  Computer Vision --- processing visual information  Robotics --- Autonomy, manipulation, full integration of AI capabilities  Advantages of AI More powerful and more useful computers New and improved interfaces Solving new problems Better handling of information Relieves information overload Conversion of information into knowledge Reduction in Human Error  Disadvantages of AI Increased costs Difficulty with software development - slow and expensive Few experienced programmers Lack of Transparency and Explain ability\ Ethical problems Lack of emotion and creativity THANK YOU