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Introduction to Artificial Intelligence
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This lesson covers: Introduction to Artificial Intelligence.

Roman Saini is teaching live on Unacademy Plus

Roman Saini
Part of a great founding team at Unacademy with Gaurav, Hemesh. Movies, Guitar, Books, Teaching.

U
Unacademy user
mam saare chapters nhi hai...
sir plz come live on YouTube channel to give some tips to aspirants for upsc pre 2019 plz sir its my request
india should develop AI from both perspectives as,Elon Musk says AI can far more dangerous than Nukes, for our two dear neighbours,China,Pak )as well as for the good purpose!!!
You are a great teacher sir but why you are not making the plus course like mains answer writing course sir
please continue with this course ..It's a superb topic and u r an awesome teacher and human being.
G
sir you are great teacher
  1. Artificial Intelligence Lesson-1 Presented By: Roman Saini


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  4. In This Lesson Artificial Intelligence Introduction Global Developments


  5. Artificial Intelligence (Al) Al refers to the ability of machines to perform cognitive tasks like thinking, perceiving, learning, problem solving and decision making Initially conceived as a technology that could mimic human intelligence, Al has evolved in ways that far exceed its original conception. . With incredible advances made in data collection, processing and computation power, intelligent systems can now be deployed to take over a variety of tasks, enable connectivity and enhance productivity. As Al's capabilities have dramatically expanded, so have its utility in a growing number of fields


  6. Artificial Intelligence (Al) Al might just be the single largest technology revolution of our live times, with the potential to disrupt almost all aspects of human existence. . .Andrew Ng, Co-founder of Coursera and formerly head of Baidu Al Group / Google Brain, compares the transformational impact of Al to that of electricity 100 years back With many industries aggressively investing in cognitive and Al solutions, global investments are forecast to achieve a compound annual growth rate (CAGR) of 50.1% to reach USD 57.6 billion in 2021. .Al is not a new phenomenon, with much of its theoretical and technological underpinning developed over the past 70 years by computer scientists such as Alan Turing, Marvin Minsky and John McCarthy.


  7. Artificial Intelligence (Al) Al has already existed to some degree in many industries and governments. . Now, thanks to virtually unlimited computing power and the decreasing costs of data storage, we are on the cusp of the exponential age of Al as organisations learn to unlock the value trapped in vast volumes of data. Al is a constellation of technologies that enable machines to act with higher levels of intelligence and emulate the human capabilities of sense, comprehend and act. Thus, computer vision and audio processing can actively perceive the world around them by acquiring and processing images, sound and speech. . The natural language processing and inference engines can enable Al systems to analyse and understand the information collected. .


  8. Artificial Intelligence (Al) An Al system can also take action through technologies such as expert systems and inference engines or undertake actions in the physical world. These human capabilities are augmented by the ability to learn from experience and keep adapting over time. Al systems are finding ever-wider application to supplement these capabilities across enterprises as they grow in sophistication. Irrespective of the type of Al being used, however, every application begins with large amounts of training data.


  9. Artificial Intelligence (Al) In the past, this kind of performance was driven by rules-based data analytics programs, statistical regressions, and early "expert systems." .But the explosion of powerful deep neural networks now gives Al something a mere program doesn't have: the ability to do the unexpected. The big change today is that we are in an unprecedented period of technology innovation across so many different fields that gives us the belief that the "Al Spring" has not only arrived but is here to stay. . Key developments responsible for this optimism are: Unlimited access to computing power Huge fall in cost of storing data Explosion in data that is digitised


  10. Artificial Intelligence (Al) Al gets categorised in different ways and it may be useful to understand the various categories, their rationale and the implications. a) Weak Al vs. Strong Al: Weak Al describes "simulated" thinking. That is, a system which appears to behave intelligently, but doesn't have any kind of consciousness about what it's doing. For example, a chatbot might appear to hold a natural conversation, but it has no sense of who it is or why it's talking to yo Strong Al describes "actual" thinking. That is, behaving intelligently, thinking as human does, with a conscious, subjective mind. For example, when two humans converse, they most likely know exactly who they are, what they're doing, and why.


  11. Global Developments Artificial Intelligence (AlI) Countries around the world are becoming increasingly aware of the potential economic and social benefits of developing and applying Al For example, China and UK. estimate that 26% and 10% of their GDPs respectively in 2030 will be sourced from Al-related activities and businesses. . There has been tremendous activity concerning Al policy positions and the development of an Al ecosystem in different countries over the last 18 to 30 months. The US published its Al report in December 2016, France published the Al strategy in January 2017 followed by a detailed policy document in March 2018, Japan released a document in March 2017 .China published the Al strategy in July 2017 and U.K. released its industrial strategy in November 2017.


  12. Artificial Intelligence (Al) Off late, Chinese universities, especially Peking and Tsinghua Universities have caught on to the race by utilising large scale public funding and extensive research partnerships with private companies. . For building the future workforce for Al, countries are also significantly increasing the allocation of resources for Science, Technology, Engineering and Maths (STEM) talent development through investment in universities, mandating new courses (e.g., Al and law), and offering schemes to retrain people. . .For instance, U.K. has planned to build over 1,000 government supported PhD researchers by 2025 and set up a Turing fellowship to support an initial cohort of Al fellows while China has launched a five-year university program to train at least 500 teachers and 5,000 students working on Al technologies.