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Introduction to Artificial Intelligence - Pengenalan Kecerdasan Buatan
The document provides an introduction to artificial intelligence (AI), its differentiation from machine learning and deep learning, and its applications in daily life. It also covers historical milestones in AI, including the Turing test and advancements in machine learning algorithms, particularly deep neural networks. The content highlights the significance of AI in the fourth industrial revolution and its growing impact across various industries.
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Introduction to Artificial Intelligence - Pengenalan Kecerdasan Buatan
- 1. www.ugm.ac.idLocally Rooted, Globally Respected Artificial Intelligence – Department of Electrical Engineering and Information Technology Dr. Sunu Wibirama Introduction toArtificial Intelligence Dr. Sunu Wibirama sunu@ugm.ac.id Department of Electrical Engineering and Information Technology Faculty of Engineering Universitas Gadjah Mada Short profile ▪ Dr. Sunu Wibirama Teknik Elektro, Universitas Gadjah Mada Yogyakarta, Indonesia (S.T.) – 2007 Dept. Electronics, King Mongkut’s Institute of Technology Ladkrabang, Bangkok, Thailand (M.Eng.) – 2010 Graduate School of Science and Technology, Tokai University, Tokyo, Japan (Dr.Eng.) – 2014 sunu@ugm.ac.id http://sunu.staff.ugm.ac.id http://bit.ly/gazetracking Affiliation: Intelligent Systems RG Dept. of Electrical Engineering & Information Technology Faculty of Engineering Universitas Gadjah Mada Area of research • eye-gaze tracking • computer vision • human-computer interaction • user experience • human factors and safety in 3D technology and virtual reality
- 2. http://sunu.staff.ugm.ac.id Goal of thisintroductory session • Understanding basic concept of artificial intelligence (AI) • Differentiating AI with machine learning and deep learning • Identifying various applications of AI that support daily activities • Pointing out some milestones in history of AI • Comparing basic differences of machine learning and deep learning
- 3. Overview of thelecture • Part 1: Industrial Revolution 4.0 and Artificial Intelligence • Part 2: History of Turing Machine and Current Status of Artificial Intelligence • Part 3: Introduction to Machine Learning • Part 4: The Rise of Deep Neural Network The Fourth Industrial Revolution
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- 5. What is ArtificialIntelligence? Your day-by-day activities
- 6. Artificial intelligence (AI) •Intelligence: the ability to acquire and apply knowledge • Artificial intelligence is created to simulates human intelligence processes by machines, especially computer systems. • These processes include learning, decision-making, and self-correction. Particular applications of AI include expert systems (e.g., Google Maps), speech recognition (e.g.,: Apple Siri) and machine vision (e.g., Facebook’s face recognition). Can you find one example of AI technology that you encounter in your life? Short quiz
- 7. End of Part1 www.ugm.ac.idLocally Rooted, Globally Respected Artificial Intelligence – Department of Electrical Engineering and Information Technology Dr. Sunu Wibirama Introduction to Artificial Intelligence (part 2) Dr. Sunu Wibirama sunu@ugm.ac.id Department of Electrical Engineering and Information Technology Faculty of Engineering Universitas Gadjah Mada
- 8. History of TuringMachine and Current Status of Artificial Intelligence AI - some years ago Alan Turing - The father of modern computer system The original Enigma machine used by Nazi squad — collection of Museum of Science and Industry, Chicago US (my personal photo collection © 2014)
- 9. AI - someyears ago Alan Turing has developed a Turing Test in 1950 while working in University of Manchester, UK. The "standard interpretation" of the Turing test, in which player C (the interrogator) is given the task of trying to determine which player – A or B – is a computer and which is a human. The interrogator is limited to using the responses to written questions to make the determination AI - some years ago IBM's Watson beat two Jeopardy champions in a special edition of game show in 2011
- 10. AI - GoogleI/O2018 What do you think? Has AI passed the Turing Test? Short quiz
- 11. End of Part2 www.ugm.ac.idLocally Rooted, Globally Respected Artificial Intelligence – Department of Electrical Engineering and Information Technology Dr. Sunu Wibirama Introduction to Artificial Intelligence (part 3a) Dr. Sunu Wibirama sunu@ugm.ac.id Department of Electrical Engineering and Information Technology Faculty of Engineering Universitas Gadjah Mada
- 12. Introduction to Machine Learning (MichaelCopeland, 2016)
- 13. Machine Learning “A computer program is said to learn from experience (E) with some class of tasks (T) and a performance measure (P) if its performance at tasks in T as measured by P improves with E” (Tom Mitchell, 1997) Some important terminologies • Training/Evolution set –Set of data to discover potentially predictive relationships. • Instances – A sample is an item to process (e.g. classify). It can be a document, a picture, a sound, a video, a row in database or CSV file, or whatever you can describe with a fixed set of quantitative traits. • Features / attributes – The number of features or distinct traits that can be used to describe each item in a quantitative manner. • Feature vector – is an n-dimensional vector of numerical features that represent some object. • Feature extraction – Preparation of feature vector – transforms the data in the high-dimensional space to a space of fewer dimensions.
- 14. (class / label) (features) (instance) www.ugm.ac.idLocally Rooted, Globally Respected Artificial Intelligence – Department of Electrical Engineering and Information TechnologyDr. Sunu Wibirama Introduction to Artificial Intelligence (part 3b) Dr. Sunu Wibirama sunu@ugm.ac.id Department of Electrical Engineering and Information Technology Faculty of Engineering Universitas Gadjah Mada
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- 16. Now, what isthis? Human can make an inference almost effortlessly, but you cannot expect the same thing on computer. We train a computer with training data and we expect the computer to make inference over new (test) data. How machine learning works (simplified)
- 17. Machine Learning for Vehicle Plate Number Recognition DIP DIP DIP Researcher: D.Sihombing, H.A. Nugroho, S. Wibirama (2015) A. Prasetyo, S. Wibirama, N.A. Setiawan (2016) Machine learning Machine learning for traffic monitoring Researcher: D.A. Kurniawan, S. Wibirama, N.A. Setiawan (2016)
- 18. Machine learning inmedical eye tracking San Diego, US Industrial partner: Artificial Intelligence in Autonomous Navigation DARPA Grand Challenge Stanley autonomous car Google intelligent car
- 19. Let's see avideo about a mind blowing self-driving car....
- 20. If AI candrive a car, do you think that in future we do not need human drivers for public transports anymore? Short quiz End of Part 3
- 21. www.ugm.ac.idLocally Rooted, Globally Respected Artificial Intelligence – Department of Electrical Engineering and Information Technology Dr. Sunu Wibirama Introduction toArtificial Intelligence (part 4a) Dr. Sunu Wibirama sunu@ugm.ac.id Department of Electrical Engineering and Information Technology Faculty of Engineering Universitas Gadjah Mada Recent advance in Machine Learning: The Rise of Deep Neural Network
- 22. (Michael Copeland, 2016) Clickto start! Basic concept of neural network algorithm
- 23. Neural networks wasused to recognize hand writing in a bank check (LeCun,1999) The Hype is Real for Sure... Even the Twilight's girl has published a Deep Learning paper
- 24. The Rise ofDeep Learning in Silicon Valley • 2012 was the first year that neural nets grew to prominence • Alex Krizhevsky, Ilya Sutskever, and Geoffrey Hinton used them to win that year’s ImageNet competition (basically, it is the annual olympics of computer vision) • They dropped the classification error record from 26.2% to 15.3%, a remarkable improvement at the time. • Ever since then, a host of companies have been using deep learning at the core of their services: • Facebook uses neural nets for their automatic tagging algorithms • Google for their photo search • Amazon for their product recommendations • Pinterest for their home feed personalization • Instagram for their search infrastructure. Mind-blowing citations in 6 years 21645 papers have cited them since 2012
- 25. To whom youcan refer Dr. Yann LeCun Head, Facebook AI Lab Prof. Geoffrey Hinton Canadian Institute for Advanced Research / Google Brain Prof. Yoshua Bengio Montreal Institute for Learning Algorithm Dr. Andrew Ng Coursera, Baidu, Stanford University pic of andrew ng https://www.cifar.ca/research/learning-in-machine-and-brains/ Canadian Institute for Advanced Research (CIFAR)
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- 27. https://www.thestar.com/news/gta/2017/03/28/new-toronto-institute-aims-to-be- worldwide-supplier-of-artificial-intelligence-capability.html News on 28March 2017 Nvidia Deep Learning Institute
- 28. www.ugm.ac.idLocally Rooted, Globally Respected Artificial Intelligence – Department of Electrical Engineering and Information Technology Dr. Sunu Wibirama Introduction toArtificial Intelligence (part 4b) Dr. Sunu Wibirama sunu@ugm.ac.id Department of Electrical Engineering and Information Technology Faculty of Engineering Universitas Gadjah Mada Machine Learning vs. Deep Learning What are the core differences?
- 29. Workflow of TraditionalMachine Learning Most machine learning research works try to develop novel features for more accurate performance
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- 33. Pros and cons Source:Introducing Deep Learning with Matlab (Mathworks, 2018) Summary • Artificial intelligence has been used in so many applications. Practically, we are surrounded by AI technologies, in so many forms. • Machine learning is a sub-field of AI that focuses on giving ability to a computer to learn from data without explicitly being programmed by a human. • Deep-learning is a new form of neural network research. It is now the most popular algorithm of machine learning technology used in various companies.
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