"Living in the IT Era" refers to the current period in which Information Technology, Slides of Information Technology

Download "Living in the IT Era" refers to the current period in which Information Technology and more Slides Information Technology in PDF only on Docsity! LITE | Chapter 4 ARTIFICIAL INTELLIGENCE What is Artificial Intelligence1 AI Structure2 History of AI3 Types of AI4 Examples of AI5 Contents Importance of AI6 Automation is about setting up robots to follow a set of pre-defined rules. Artificial Intelligence is about setting up robots to make their own decisions (though still based on human input). AI can be used in automation, but most automation uses conventional software to transfer data from one location to another. difference between AI and automatic machine Learning1 Reasoning2 Problem-solving3 Perception4 Language5 Components of Intelligence STRUCTURE OF ARTIFICIAL INTELLIGENCE Kahkashan, Rehman & Ahirwar, Dr. Anamika. (2020). Depiction the Artificial Intelligence with Machine Learning. Solid State Technology. 63. 4734-4739. a subset of AI the science of programming machines to think and act like humans without being explicitly programmed to aims to enable computers to learn automatically without human intervention and adjust actions uses algorithms that can make predictions through pattern recognition mACHINE LEARNING SUPERVISED Learning creating models that can learn from marked datasets to make predictions eg. spam filtering and face recognition REINFORCEMENT Learning uses feedback data to improve the performance of a model eg. games like Chess and Go mACHINE LEARNING CategorieS UNSUPERVISED Learning given an unlabeled dataset, the algorithm must find some way to learn without the guidance of humans eg. fraud transactions application of Machine Learning that uses complex algorithms and artificial neural networks (ANN; which structures and functions like brain neurons) to train a model, where data and patterns can be better perceived DEEP LEARNING Predictive Analytics As a subset of AI, predictive analytics is a statistics-based method that data analysts use to make assumptions and test records in order to predict the likelihood of a given future outcome. Analysts capture historical trends and apply these patterns to current data, then compute a specific value at a future point in time. AI is completely autonomous while predictive analytics relies on human interaction to query data, identify trends, and test assumptions. Banking Healthcare Human Resources (HR) Marketing and Sales Supply Chain Applications are: Predictive Analytics Natural Language Processing (NLP) is a subfield of AI that focuses on enabling machines to understand and interpret human language. NLP is used in applications such as chatbots, virtual assistants, and language translation. Natural Language Processing With NLP, PCs can decode, display and generate human language and communicate. Its ultimate aim is to make predictable organized attempts with the computers we use every day by teaching systems to understand the human language and to react intelligently. CaDet (Cancer Decision Support Tool) is used to identify cancer in its earliest stages. DENDRAL helps chemists identify unknown organic molecules. DXplain is a clinical support system that diagnoses various diseases. MYCIN identifies bacteria such as bacteremia and meningitis, and recommends antibiotics and dosages. PXDES determines the type and severity of lung cancer a person has. R1/XCON is an early manufacturing expert system that automatically selects and orders computer components based on customer specifications. Examples of expert systems planning, scheduling and optimisation A system based on AI uses planning to determine ‘what steps to take’ (planning) and ‘when to carry out a certain step’ (scheduling) in order to achieve a goal. The common term given to an intelligent system that implements planning is ‘agent’. The plan implemented by the agent enables it to search through each and every possible action or route to reach the set goal. robotics Robotics is a field of AI that involves designing, building, and programming robots to perform tasks. Robots are used in various applications such as manufacturing, healthcare, and space exploration. AI-powered robots are augmented with a variety of sensors (including vision devices such as 2D/3D cameras, vibration sensors, proximity sensors, accelerometers, and other environmental sensors,) that feed them with sensing data they can analyze and act upon in real-time. HISTORY OF ARTIFICIAL INTELLIGENCE Alan Turing developed John McCarthy coined the Joseph Weizenbaum at Stanford Research Institute the “Turing Test” term ‘Artificial Intelligence’ MIT built ELIZA developed Shakey, a robot First computer Apple introduced iRobot launched Roomba Deep Blue Chess controlled autonomous Personal Assistant Siri vacuum cleaner Program vehicle, Stanford Cart Amazon launched Tesla introduces Hanson Robotics introduced Sophia Sophia becomes citizen Alexa Autodrive feature the first Al based humanoid robot of Saudi Arabia In a Turing test, the interrogator must determine which respondent is a computer and which is a human. originally called the imitation game; a test of a machine's ability to exhibit intelligent behavior equivalent to, or indistinguishable from, that of a human. "Can machines think?" TURING TEST Alan Turing (1950) known as the Father of Artificial Intelligence In the early 1950s, the study of “thinking machines” had various names like cybernetics, automata theory, and information processing. He wanted a new, neutral umbrella term that could collect and organize these disparate research efforts into a single field focused on developing machines that could simulate every aspect of intelligence. "ARTIFICIAL INTELLIGENCE" John Mccarthy (1956) was originally built to simulate a remote-controlled moon rover had a 45 year career of ups and downs, including redesigning and configurations In 1979, the cart successfully crossed a chair-filled room without human intervention in about five hours. STANford Cart Stanford AI LAboratory (1979) chess-playing expert system run on a unique purpose-built IBM supercomputer development began in 1985 at Carnegie Mellon University On May 11, 1997, it beat the world chess champion, Garry Kasparov, after a six- game match: two wins for IBM, one for the champion and three draws. The match lasted several days and received massive media coverage around the world. It was the classic plot line of man vs. machine. DEEP BLUE International Business Machines corporation (IBM) mobile robot for vacuuming floors a series of autonomous robotic vacuum cleaners which a have a set of sensors that enable them to navigate the floor area of a home By 2004, a million Roombas had been sold. ROOMBA iRobot (2002) Tesla Version 7.0 software was released, enabling Autopilot as a feature for Model S drivers a combination of adaptive cruise control and Autosteer, a lane centering function designed to keep Tesla vehicles within painted lane lines. "Autopilot is not a self-driving system and that “the driver is still responsible for, and ultimately in control of, the car,” but it also reiterates that Tesla vehicles are equipped with hardware “to allow for the incremental introduction of self-driving technology.” tesla autopilot tesla (2015) the humanoid robot has simulations of every major muscle in the human face, allowing her to generate expressions of joy, grief, curiosity, confusion, contemplation, sorrow, frustration, among other feelings. In 2017, Sophia was given Saudi Arabian citizenship, becoming the first robot to receive citizenship of any country. One month later, Sophia was named the United Nations Development Program's first Innovation Champion. Sophia hanson robotics (2016) Types of Artificial Intelligence Based on Capabilities Based on Functionalities Lice ey General Al Reactive Self- Machine awareness Near Limited Theory of Memory attire examples of Artificial Intelligence Media streaming Chatbots Smart assistants E-commerce Search engines Social media feeds Smart cars Navigation apps Facial recognition Text editors Chat-based Generative Pre-trained Transformer, ChatGPT (OpenAI) 1 ChatSonic (Writesonic)2 Bing Chat (Microsoft)3 Jasper Chat (Jasper)4 Replika (by Eugenia Kuyda)5 Chatbots Socratic (Google)6 - uses artificial intelligence to generate text or answer queries based on user input Siri (Apple)1 Cortana (Microsoft)2 Alexa (Amazon)3 Google Assistant (Google)4 Fireflies.ai (Fireflies)5 Smart Assistants - capable of carrying out many of the same tasks as human assistants, such as reading text, taking dictation, making calls, etc. Bing and Edge (Microsoft)1 You.com (Bryan McCann and Richard Socher) 2 Perplexity AI (Aravind Srinivas)3 Neeva (Sridhar Ramaswamy)4 Search engines - employ powerful artificial intelligence algorithms to decipher the meaning of search queries and provide the most accurate and relevant results Netflix1 Amazon Prime2 Spotify3 FireStick App4 MEdia streaming - study people’s viewing history, preferences, and behaviors to provide tailor-made, enjoyable experiences Tesla (Austin, Texas)1 Nauto (Palo Alto, California)2 SapientX (San Cruz, California)3 Rethink Robotics (Bochum, Germany)4 Smart cars - include industrial robots constructing a vehicle and autonomous cars navigating traffic with machine learning and vision 6 Motional (Boston, Massachusetts)5 Waymo (Mountain View, California) Jasper1 Writesonic2 Article Forge3 Grammarly4 Text editors - make it simple and easy to autogenerate content for your blog, website, or social media profiles Quillbot5 Facebook (DeepText and DeepFace) 1 Twitter (IBM Watson and NLP) 2 SnapChat (ML Models and AR Technology) 3 Instagram (Big Data and AI) 4 SOCIAL media feeds - automate many tedious tasks related to social media management and can do social media monitoring at scale It automates repetitive learning and discovery through data. 1 It adds intelligence to existing products.2 It adapts through progressive learning algorithms.3 It analyzes more and deeper data.4 It achieves incredible accuracy .5 Why is ai important? It gets the most out of data.6