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COSC 4121: Deep Learning and Applications Lecture 1 Introduction to Deep Learning COSC-4121 DL and Applications Shahzad Hussain Lecturer Today’s Lecture outline 1. Course Evaluation Detail 2. Artificial Intelligence, Learning, and Deep Learning 1. 2. 3. 4. 5. 6. 7. 2 Machine Artificial Intelligence Machine Learning Learning Representation from Data The “Deep” in deep Learning Understanding how deep learning works, in three figures Don’t believe the short-term hype The promise of AI Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology COSC-4121 DL and Applications 1. Course Evaluation Procedure COSC-4121 DL and Applications Course Evaluation Procedure • Mid Term 30% • Final Term 50% • Sessional 20% – Quizzes 5% – Assignments 5% – Term Project 10% – Presentations – Class behavior • Attendance must be maintained as per rule (>=75%) 4 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology COSC-4121 DL and Applications Recommended Book • Deep Learning with python Francis Chollet Practical Implementation & Reference Book • Deep Learning Ian Goodfellow Yoshua Bengio Aaron Courville • Grokking Deep Learning Andrew W. Trask 5 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology COSC-4121 DL and Applications 2. Artificial Intelligence, Machine Learning, and Deep Learning COSC-4121 DL and Applications 6 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology Artificial Intelligence, Machine Learning and Deep Learning • Promised future of intelligent chatbots, selfdriving cars, and virtual assistants where deep learning will play crucial roles. COSC-4121 DL and Applications 7 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology Artificial Intelligence, Machine Learning and Deep Learning • The field of artificial intelligence: the effort to automate intellectual tasks normally performed by humans COSC-4121 DL and Applications 8 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology Artificial Intelligence, Machine Learning and Deep Learning • The dominant paradigm in AI from 1950s to the late 1980s: Expert System (known as symbolic AI). – Intractable to figure out explicit rules for solving complicated rules (e.g., image classification, speech recognition, language translation) COSC-4121 DL and Applications An example of a rule-based system 9 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology Artificial Intelligence, Machine Learning and Deep Learning • Machine learning system is trained rather than explicitly programmed – Many examples (data) are needed for finding out the rules automatically Rules Data Data Answers Classical Programming Machine Learning Answers Rules Machine Learning a new Programming Paradigm 10 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology COSC-4121 DL and Applications Artificial Intelligence, Machine Learning and Deep Learning • To do machine learning we need three things: – Input data points. – Examples of the expected output (=labels) – A measure for goodness (objective function) • Machine learning models are all about finding appropriate representations for input data – e.g., coordinate change COSC-4121 DL and Applications 11 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology Artificial Intelligence, Machine Learning and Deep Learning • The “deep” in deep learning – Specifically, deep learning learns representations automatically by involving successive layers of increasingly meaningful representations. COSC-4121 DL and Applications Better representation 12 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology Artificial Intelligence, Machine Learning and Deep Learning • The layers are parameterized by weights o Weights are called ‘parameters’ of layers o Learning means finding a set of values for the weights of all layers such that the network will correctly map example inputs to their associated targets Input X Goal: finding the right values for weights Weights Layer (data transformation) Weights Layer (data transformation) Figure 1.7 A neural network is parameterized by its weights 13 Prediction Y’ Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology COSC-4121 DL and Applications Artificial Intelligence, Machine Learning and Deep Learning • Loss function (= objective function) o Measuring how far the predictions are from the true targets (quality of prediction) Input X Weights Layer (data transformation) Weights Layer (data transformation) Figure 1.8 A loss function measures the quality of the network’s output Loss Score 14 Prediction Y’ COSC-4121 DL and Applications True targets Y Loss Function Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology Artificial Intelligence, Machine Learning and Deep Learning • Optimizer adjusts the weights with respect to minimizing the loss Input X Weights Layer (data transformation) Weights Layer (data transformation) COSC-4121 DL and Applications Weights update Prediction Y’ Optimizer Loss Score True targets Y Loss Function Figure 1.8 A loss score is used as a feedback signal to adjust the weights 15 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology Artificial Intelligence, Machine Learning and Deep Learning • What deep learning has achieved so far: o Near-human-level image classification o Near-human-level speech recognition o Near-human-level handwriting transcription o Improved machine translation o Improved text-to-speech conversion o Digital assistants such as Google Now and Amazon Alexa o Near-human-level autonomous driving o Improved ad targeting, as used by Google, Baidu, Bing o Improved search results on the web o Ability to answer natural-language questions o Superhuman Go playing (defeating tophuman players) 16 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology COSC-4121 DL and Applications Artificial Intelligence, Machine Learning and Deep Learning • Don’t believe the short-term hype o Talk of human-level general intelligence should not be taken too seriously. • Too much data are required for training • Too expensive in computation • Too much expectations for AI COSC-4121 DL and Applications 17 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology Artificial Intelligence, Machine Learning and Deep Learning • The promise of AI – Although we may have unrealistic short-term expectations for AI, the long-term picture is looking bright • Similarly to Internet (most people didn’t see how the internet was relevant to them and how it was going to change their lives) – AI will answer your questions, help educate your kids, and watch over your health COSC-4121 DL and Applications 18 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology Conversational Agents COSC-4121 DL and Applications Idea: Conversational Agent • HAL 9000 is a fictional artificial intelligence character and the main antagonist in Arthur C. Clarke's Space Odyssey series. • First appearing in the 1968 film 2001: A Space Odyssey, HAL is a sentient computer that controls the systems of the Discovery One spacecraft and interacts with the ship's astronaut crew 20 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology COSC-4121 DL and Applications Digital Personal Assistants and Chatbots COSC-4121 DL and Applications Digital Personal Assistants and Chatbots Google Assistant: Google Assistant was launched in 2016 and is one of the most advanced chatbots available. It can be found in a variety of appliances such as telephones, headphones, speakers, washers, TVs, and refrigerators. 22 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology COSC-4121 DL and Applications Digital Personal Assistants and Chatbots Amazon Alexa: Alexa is a virtual assistant developed and marketed by Amazon. It can interact with users by voice and by executing commands such as playing music, creating to-do lists, setting up alarms, playing audiobooks, and answering basic questions. 23 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology COSC-4121 DL and Applications Digital Personal Assistants and Chatbots Apple Siri: Siri can accept user voice commands and a natural language user interface to answer questions, make suggestions, and perform actions by parsing these voice commands and delegating these requests to a set of internet services. The software can adapt to users' individual language usage, their searches, and preferences. The more it is used the more it learns and the better it gets. 24 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology COSC-4121 DL and Applications Digital Personal Assistants and Chatbots Microsoft Cortana: Cortana is another digital virtual assistant, designed and created by Microsoft. Cortana can set reminders and alarms, recognize natural voice commands, and it answers questions using information. 25 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology COSC-4121 DL and Applications Personal Chauffeur COSC-4121 DL and Applications Google’s Waymo COSC-4121 DL and Applications 27 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology Google’s Waymo • As of 2018, Waymo's autonomous cars have driven eight million miles on public roads as well as five billion miles in simulated environments. • In the next few years, it is all but a certainty that we will be able to purchase a car capable of full driving autonomy. • Tesla, among others, already offers driver assistance with their Autopilot feature and possibly will be the first company to offer full selfdriving capabilities. • Waymo launched the first commercial driverless service in 2018 in Arizona, USA with plans to expand nationally and worldwide. 28 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology COSC-4121 DL and Applications Shipping and Warehouse Management COSC-4121 DL and Applications Shipping and Warehouse Management • An Amazon sorting facility is one of the best examples of the symbiotic relationship that is forming between humans, computers, and robots. Computers take customer orders and decide where to route merchandise, the robots act as mules carrying the pallets and inventory around the warehouse. • Even Scott Anderson, Amazon's director of robotics fulfillment acknowledged in May 2019 that a fully automated warehouse is at least 10 years away. • So, we will continue to see this configuration in warehouses across the world for a little longer. 30 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology COSC-4121 DL and Applications Human Health COSC-4121 DL and Applications Human Health 1. 2. 3. 4. 5. 6. 7. 32 Drug Discovery Insurance pricing Patient Diagnosis Medical Image Interpretation Psychiatric Analysis Smart Health Records Disease Detection and Prediction Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology COSC-4121 DL and Applications Knowledge Search COSC-4121 DL and Applications Knowledge Search • Google Search, is most often used for exploring information. • Early in 2015, as was reported by Bloomberg, Google began using a deep learning system called RankBrain to assist in generating search query responses. 34 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology COSC-4121 DL and Applications Recommendation Systems COSC-4121 DL and Applications Recommendation Systems • Recommendation systems are another example of AI technology that has been weaved into our everyday lives. • Amazon, YouTube, Netflix, LinkedIn, and Facebook all rely on recommendation technology and we don't even realize we are using it. • Netflix Prize • Pandora • Robo-Advisors – betterment 36 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology COSC-4121 DL and Applications The Smart Home COSC-4121 DL and Applications The Smart Home • Home Monitoring: – Ring Video Doorbell – Amazon – Google Nest Thermostat • Vacucmming and mopping – Roomba – Brava – Packbot – Bomb disposal robot • Picking up your mess • Personal Chef – Moley Robotic Kitchen 38 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology COSC-4121 DL and Applications Gaming COSC-4121 DL and Applications StartCraft 2 • StarCraft II is considered one of the hardest, though it is an ancient game by video game standards. • The team at DeepMind introduced a program dubbed AlphaStar, defeat a top professional player, in December 2018, AlphaStar whooped a team put together by Grzegorz "MaNa" Komincz, one of the world's strongest professional StarCraft players with a score of 50. 40 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology COSC-4121 DL and Applications IBM Watson – Question Answering Machine • IBM and the Watson team made history in 2011 when they devised a system that was able to beat two of the most successful Jeopardy champions. • Watson is a questionanswering system that can answer questions posed in natural language. • It was initially created by IBM's DeepQA research team, led by principal investigator David Ferrucci. 41 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology COSC-4121 DL and Applications Chess • The Deep Blue team went back to the drawing board, made a lot of enhancements to the software, and played Kasparov in 1997. • Deep Blue won the second round against Kasparov winning the sixgame rematch by a score of 3½– 2½. • It then became the first computer system to beat a current world champion in a match under standard chess tournament rules and time controls. 42 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology COSC-4121 DL and Applications AlphaGo • There is great example of a powerful program that can play the game of Go also developed by DeepMind called AlphaGo. • March 2016, it beat Lee Sedol in a five-game match. This became the first time a Go program beat a 9-dan professional without handicaps. Although AlphaGo lost to Lee Sedol in the fourth game, Lee resigned in the final game, giving a final score • of 4 games to 1. 43 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology COSC-4121 DL and Applications Movie Making COSC-4121 DL and Applications Movie Making • Deepfakes – A deepfake is a portmanteau, or blend of “deep learning” and “fake”. – It an AI technique to merge video images. – Common application is to overlap someone’s face onto another. – Used to create fake news or hoaxes. Example: – Zao – developed by Chinese Company Momo, allows you to overlap someone’s face over short movie clips like Titanic and the results are impressive. 45 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology COSC-4121 DL and Applications Movie Making • Movie Script Generation – One of the most famous examples is Sunspring, award winning. – Sunspring is an experimental fiction short film released in 2016. – Written by using deep learning techniques. – Script was created by LSTM (Long short-term memory) model dubbed Benjamin. 46 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology COSC-4121 DL and Applications Data Cleaning and Transformation COSC-4121 DL and Applications Data Cleaning and Transformation • Clean and Accurate data is paramount to producing consistent, reproducible, and accurate AI models. • Data scientist spends about 80% of their time cleaning, preparing and transforming their input data and 20% for optimizing their models. • Example: image data sets Image Net and MS COCO. • Amazon Lake formation, August 2019, automates some steps of creation of a data lake including collection, cleansing, deduplication, cataloging, and publication of data. 48 Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology COSC-4121 DL and Applications Today’s Lecture Summary • Course Evaluation Detail • Artificial Intelligence, Machine Learning, and Deep Learning – – – – – – – 49 Artificial Intelligence Machine Learning Learning Representation from Data The “Deep” in deep Learning Understanding how deep learning works, in three figures Don’t believe the short-term hype The promise of AI Shahzad Hussain, Lecturer, Khawaja Fareed University of Engineering and Information Technology COSC-4121 DL and Applications