AI (artificial intelligence) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using the rules to reach approximate or definite conclusions) and self-correction. Particular applications of AI include expert systems, speech recognition and machine vision.
AI was coined by John McCarthy, an American computer scientist, in 1956 at The Dartmouth Conference where the discipline was born. Today, it is an umbrella term that encompasses everything from robotic process automation to actual robotics. It has gained prominence recently due, in part, to big data, or the increase in speed, size and variety of data businesses are now collecting. AI can perform tasks such as identifying patterns in the data more efficiently than humans, enabling businesses to gain more insight out of their data.
AI applications
- AI in healthcare. The biggest bets are on improving patient outcomes and reducing costs. Companies are applying machine learning to make better and faster diagnoses than humans. One of the best known healthcare technologies is IBM Watson. It understands natural language and is capable of responding to questions asked of it. The system mines patient data and other available data sources to form a hypothesis, which it then presents with a confidence scoring schema. Other AI applications include chatbots, a computer program used online to answer questions and assist customers, to help schedule follow-up appointments or aiding patients through the billing process, and virtual health assistants that provide basic medical feedback.
- AI in business. Robotic process automation is being applied to highly repetitive tasks normally performed by humans. Machine learning algorithms are being integrated into analytics and CRM platforms to uncover information on how to better serve customers. Chatbots have been incorporated into websites to provide immediate service to customers. Automation of job positions has also become a talking point among academics and IT consultancies such as Gartner and Forrester.
- AI in education. AI can automate grading, giving educators more time. AI can assess students and adapt to their needs, helping them work at their own pace. AI tutors can provide additional support to students, ensuring they stay on track. AI could change where and how students learn, perhaps even replacing some teachers.
- AI in finance. AI applied to personal finance applications, such as Mint or Turbo Tax, is upending financial institutions. Applications such as these could collect personal data and provide financial advice. Other programs, IBM Watson being one, have been applied to the process of buying a home. Today, software performs much of the trading on Wall Street.
- AI in law. The discovery process, sifting through of documents, in law is often overwhelming for humans. Automating this process is a better use of time and a more efficient process. Startups are also building question-and-answer computer assistants that can sift programmed-to-answer questions by examining the taxonomy and ontology associated with a database.
- AI in manufacturing. This is an area that has been at the forefront of incorporating robots into the workflow. Industrial robots used to perform single tasks and were separated from human workers, but as the technology advanced that changed.
Artificial Intelligence Courses
1. EdX's Artificial Intelligence:What do self-driving cars, face recognition, web search, industrial robots, missile guidance, and tumor detection have in common?
They are all complex real world problems being solved with applications of intelligence (AI).
This course will provide a broad understanding of the basic techniques for building intelligent computer systems and an understanding of how AI is applied to problems.
You will learn about the history of AI, intelligent agents, state-space problem representations, uninformed and heuristic search, game playing, logical agents, and constraint satisfaction problems.
Hands on experience will be gained by building a basic search agent. Adversarial search will be explored through the creation of a game and an introduction to machine learning includes work on linear regression.
2. Udacity’s Intro to Artificial Intelligence:
The course is expected to teach you AI’s “representative applications.” It is a part of its Machine Learning Engineer Nanodegree Program. Instructors Sebastian Thrun and Peter Norvig will take you through the fundamentals of AI, which include Bayes networks, statistics, and machine learning, and AI applications such as NLP, robotics, and image processing. Students are expected to know linear algebra and probability theory.
3. Artificial Intelligence: Principles and Techniques
This Stanford course talks about how AI uses math tools to deal with complex problems such as machine translation, speech and face recognition, and autonomous driving. You can access the comprehensive lecture outline—machine learning concepts; tree search, dynamic programming, heuristics; game playing; Markov decision processes; constraint satisfaction problems; Bayesian networks; and logic— and assignments.4. Udacity's Artificial Intelligence for Robotics by Georgia Tech
Offered by Udacity, this course talks about programming a robotic car the way Stanford and Google do it. It is a part of the Deep Learning Nanodegree Foundation course. Sebastian Thrun will talk about localization, Kalman and Particle filters, PID control, and SLAM. Strong grasp of math concepts such as linear algebra and probability, knowledge of Python, and programming experience are good-to-have.M.TECH AI (artificial intelligence) colleges in india
- .DON BOSCO UNIVERSITY-DBU ,ASSAM
- UNIVERSITY OF HYDERABAD,ANDHRA PRADESH
- UNIVERSITY OF PETROLEUM AND ENERGY STUDIES-UPES, UTTARAKHAND
