Unit-1 Introduction to Artificial Intelligence (AI) PDF

Unit-1 Introduction to Artificial Intelligence (AI) Intelligence: According to researchers, intelligence is the ‘ability to perceive or infer information, and to retain it as knowledge to be applied towards adaptive behaviors within an environment or context.’ Following are the abilities that are...

Unit-1 Introduction to Artificial Intelligence (AI) Intelligence: According to researchers, intelligence is the ‘ability to perceive or infer information, and to retain it as knowledge to be applied towards adaptive behaviors within an environment or context.’ Following are the abilities that are involved in intelligence: a) Mathematical Logical Reasoning: A person's ability to regulate, measure, and understand numerical symbols, abstraction and logic. b) Linguistic Intelligence: Language processing skills both in terms of understanding or implementation in writing or verbally. c) Spatial Visual Intelligence: It is defined as the ability to perceive the visual world and the relationship of one object to another. d) Kinesthetic Intelligence: Ability that is related to how a person uses his limbs in a skilled manner. e) Musical Intelligence: As the name suggests, this intelligence is about a person's ability to recognize and create sounds, rhythms, and sound patterns. f) Intrapersonal Intelligence: Describes how high the level of self-awareness someone has is. Starting from realizing weakness, strength, to his own feelings.  g) Existential Intelligence: An additional category of intelligence relating to religious and spiritual awareness. h) Naturalist Intelligence: An additional category of intelligence relating to the ability to process information on the environment around us. i) Interpersonal intelligence: Interpersonal intelligence is the ability to communicate with others by understanding other people's feelings & influence of the person. To summarize, we may define intelligence as: Ability to interact with the real world Reasoning and planning Learning and adaptation What is Artificial Intelligence? When a machine possesses the ability to mimic human traits, i.e., make decisions, predict the future, learn and improve on its own, it is said to have artificial intelligence. In other words, you can say that a machine is artificially intelligent when it can accomplish tasks by itself - collect data, understand it, analyze it, learn from it, and improve it. How do machines become Artificially Intelligent? Humans become more and more intelligent with time as they gain experiences during their lives. Similarly, machines also become intelligent once they are trained with some information which helps them achieve their tasks. AI machines also keep updating their knowledge to optimize their output. Applications of Artificial Intelligence around us 1.) Google Search: Google always responds to us with accurate answers. It also suggests and auto corrects our typed sentences. 2.) Pocket Assistants: Alexa, Google Assistant, Cortana, Siri are some very common examples of the voice assistants which are a major part of our digital devices.  3.) Maps: apps like UBER and Google Maps now comes in phone. Thus, one no longer needs to stop repeatedly to ask for directions. 4.) AI Enabled Games: A lot of games nowadays are backed up with AI which helps in enhancing the graphics, come up with new difficulty levels, encourage gamers, etc. 5.) E-Commerce Sites: Platforms like Netflix, Amazon, Spotify, YouTube etc. show us recommendations on the basis of what we like. 6.) Social media platforms: apps like Facebook and Instagram send us customized notifications about our online shopping details, auto-create playlists according to our requests and so on. Taking selfies was never this fun as Snapchat filters make them look so cool. 7.) Biometric security systems like the face locks we have in our phones 8.) Real-time language translators, weather forecasts and many more. KWLH Chart: 1. What I Know? 2. What I Want to know? 3. What have I learned? 4. How I learnt this? AI, ML & DL: Artificial Intelligence (AI): Refers to any technique that enables computers to mimic human intelligence. It gives the ability to machines to recognize a human’s face; to move and manipulate objects; to understand the voice commands by humans, and also do other tasks. The AI-enabled machines think algorithmically and execute what they have been asked for intelligently. Machine Learning (ML): It is a subset of Artificial Intelligence which enables machines to improve at tasks with experience (data). The intention of Machine Learning is to enable machines to learn by themselves using the provided data and make accurate Predictions/ Decisions. Deep Learning (DL): It enables software to train itself to perform tasks with vast amounts of data. In Deep Learning, the machine is trained with huge amounts of data which helps it in training itself around the data. Such machines are intelligent enough to develop algorithms for themselves. Deep Learning is the most advanced form of Artificial Intelligence out of these three. Introduction to AI Domains Artificial Intelligence becomes intelligent according to the training which it gets. For training, the machine is fed with datasets. With respect to the type of data fed in the AI model, AI models can be broadly categorised into three domains: Data Sciences Computer Vision Natural Language Processing Let’s understand each in brief: Data Sciences: Data sciences is a domain of AI related to data systems and processes, in which the system collects numerous data, maintains data sets and derives meaning/sense out of them. Example of Data Science: (i) Price Comparison Websites (These websites are being driven by lots and lots of data. PriceGrabber, PriceRunner, Junglee, Shopzilla, DealTime are some examples of price comparison websites.) (ii) Social Media Sites: These websites store the information regarding our likes and dislikes, activities, etc and based on this data, they provide us with the recommended stories. Computer Vision: Computer Vision, abbreviated as CV, is a domain of AI that depicts the capability of a machine to get and analyse visual information and afterwards predict some decisions about it. The entire process involves image acquiring, screening, analysing, identifying and extracting information. The main objective of this domain of AI is to teach machines to collect information from pixels. Examples of Computer Vision : (i) Self-Driving cars/ Automatic Cars (CV systems scan live objects and analyse them, based on whether the car decides to keep running or to stop.) (ii) Face Lock in Smartphones (The front camera detects and captures the face and saves its features during initiation. Next time onwards, whenever the features match, the phone is unlocked. ) Natural Language Processing: Natural Language Processing, abbreviated as NLP, is a branch of artificial intelligence that deals with the interaction between computers and humans using the natural language. The ultimate objective of NLP is to read, decipher, understand, and make sense of the human languages in a manner that is valuable. Examples of Natural Language Processing: (i) Email filters (Email filters are one of the most basic and initial applications of NLP online that filters emails by uncovering certain words or phrases that signal a spam message (ii) Smart assistants (Smart assistants like Apple’s Siri and Amazon’s Alexa recognize patterns in speech, then infer meaning and provide a useful response.) AI Ethics (i) Moral Issues: here the morality of the developer gets transferred into the machine as what according to him/her is right would have a higher priority and hence would be the selection made by the machine. (ii) Data Privacy: The world of Artificial Intelligence revolves around Data. Every company whether small or big is mining data from as many sources as possible. Therefore, it is a big question that whether allowing the data access is safe or not. (iii) AI Bias: Another aspect to AI Ethics is bias. Everyone has a bias of their own no matter how much one tries to be unbiased, we in some way or the other have our own biases even towards smaller things. Any bias can transfer from the developer to the machine while the algorithm is being developed. (iv) AI Access: The people who can afford AI enabled devices make the most of it while others who cannot are left behind. Because of this, a gap has emerged between these two classes of people and it gets widened with the rapid advancement of technology. (v) AI creates unemployment: Maybe in the coming years, AI enabled machines will replace all the people who work as labourers. This may start an era of mass unemployment where people having little or no skills may be left without jobs and others who keep up with their skills according to what is required, will flourish. (vi) AI for kids: Is it safer to provide full access of technology to children or this could actually stop them working hard.