Public Cloud and cloud security

Problem Solving with Knowledge

From Artificial Intelligence To Machine Learning

Kyung Eun Park, D.Sc.

Augusta Ada King, Countess of Lovelace

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ContentsAI OverviewHow AI is implemented?From AI to Machine LearningMachine Learning Examples of AI and Machine LearningBehavior Training with BCI and Motion RecognitionConclusion

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What is Artificial Intelligence?D E F I N I T I O N

It is the science and engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand human intelligence, but AI does not have to confine itself to methods that are biologically observable, by John McCarthy, 1956.Broadly, AI is the computer-based exploration of methods for solving challenging tasks that have traditionally depended on people for solution. Such tasks include complex logical inference, diagnosis, visual recognition, comprehension of natural language, game playing, explanation, and planning by Eric Horvitz, 1990.

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AI Timeline

Ada (1842)Alan Turing (1950)Turing testArtificial IntelligenceGeneral Problem SolverThe first conference onAI by John McCarthy, Marvin Minsky (1956)Demonstrated by Newell (1957)Programmable mechanical calculating machineUnimations working on GE (1961)Industrial robotJoseph Weizenbaum (1965), E. Geigenbaum (1965)Chess-playing program byGreenblatt at MIT (1968)Jack Myers Harry Pople (1979)ELIZA & The First Expert SystemMacHackKnowledge-based medical diagnosis program

Commercial expert system1980s

Polly: Behavior-based RoboticsIan Horswill(1993)

Recommendation TechnologyTiVo Suggestions (2005)

Mobile Recommendation Apps: Siri, Now, CortanaApple, Google, Micorsoft(2011)

Machine Learning, Deep Learning(2013 ~)

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Knowledge in AIHuman knowledge Converted into a format suitable for use by an AI systemAI generated/learned knowledgeGenerated by an AI systemBy gathering data and information, and By analyzing data, information, and knowledge at its disposal

Knowledge acquisition process is pretty similar to the normal learning procedure.

In brief, AI stores and uses the knowledge to solve problems.

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Predicate Logic

Object Properties: Is-a relationship Instance-of relationshipex) isSymptomOf: maybeSymptomOf: mayHaveSymptom: shouldHaveSymptom:

Knowledge Representation by Healthcare Example

Classes: SuperclassOf SubclassOfex) Disease Class Symptom Class

Object: Sym Tachycardia Subject: Hypo perfusionshouldHaveSymptompredicate

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Semantic NetworkBuilding relationship between Diseases and SymptomsConstructing semantic graph with Nodes (instance objects) and Edges (object properties)Sym Tachycardia Congestive HeartFailureHeatStrokeHypo perfusionOverdoseAcute Myocardial InfarctionshouldHaveSymptommaybe SymptomOfmaybe SymptomOfmaybe SymptomOfmaybe SymptomOf

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This details of the individual object properties with their domain and range information.

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Minskys Insights into Human and Machine IntelligenceComputers role in this context:It will help us to understand our own brains, to learn what is the nature of knowledge.It will teach us how we learn to think and feel.This knowledge will change our views of Humanity and enable us to change ourselves.

in an interview in 1998, Sabbatini

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From Artificial Intelligence To Machine LearningIBMs Watson (2011)

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Machine learns by itself.SELF STUDY

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Machine LearningD E F I N I T I O N

Machine learning is a type of artificial intelligence that provides computers with the ability to learn without being explicitly programmed. Machine learning focuses on the development of computer programs that can teach themselves to grow and change when exposed to new data

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In 1956, he wanted this computer to beat him at checkers. He made the computer play against itself thousands of times and learn how to play checkers, and indeed IT WORK! By 1962 this computer had beaten the Connecticut state champion.Arthur Samuel

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Machine LearningNOW

Machine learning is actively being used today. The search engineThe spam filterThe recommender systemThe face/handwriting /fingerprint recognitionThe location/context-based security systemThe disease diagnosis & predictionThe weather forecast, etc.

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Self-Driving Car

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Diagnosis & Prediction

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Turning data via information into knowledgeA tool that can be applied to many problems.Uses statistics for solving the problem of not being able to model the problem fully.ex) Maximize humans happinessFor these problems, we need to use some tools from statistics.

Machine Learning Process

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Human-created data from the World Wide WebMore non-human generated data coming onlineChallenge & Opportunity: How to connect the data to the WWW and use them?Sensors and Data Deluge

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Key Terminologies by ExampleBird Classification System

Expert system: ornithologistFeatures (or attributes): Weight, Wingspan, Webbed feet, Back colorTarget variable: Species (predicted)Instance: each row made up of featuresThe first two features: numericThe 3rd feature: binary (0 or 1)The 4th feature: enumeration (integer)

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How do we decide if a bird is an Ivory-Billed Woodpecker or something else? Classification task is needed!Many machine learning algorithms good at classification Choose a machine learning algorithm (Classifier) to useTrain the classifier Feed it quality data known as a training set Classification as a Machine Learning AlgorithmBird Classification

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Training set of data and a separate dataset, called a test setMulti-step Machine Learning TRAINING/LEARNING TESTING USINGTesting a Machine Learning AlgorithmRaw Data(Training Set)ClassifierFeatureRaw Data(Test Set)ClassifierFeatureFeatureExtractionFeedDataAcquisitionDataAcquisitionFeatureExtractionTrainingFeedClassificationResultTraining Phase:Testing Phase:KnowledgeRepresentation

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Key Tasks of Machine LearningIn the previous classification task, The job is to predict what class an instance should fall into.Another task, regression, The prediction of a numeric numberBoth classification and regression are examples of Supervised Learning We are telling the algorithm what to predict.Unsupervised Learning Theres no label or target value given for the dataClustering Group of similar items in unsupervised learningDensity estimation Statistical values that describe data in unsupervised learning

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Supervised learning tasksClassificationRegressionk-Nearest NeighborsLinearNave BayesLocally weighted linearSupport vector machinesRidgeDecision treesLassoUnsupervised learning tasksClusteringDensity estimationk-MeansExpectation maximizationDBSCANParzen window

Machine Learning Algorithms

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Behavior Training Platform

NeuroSky InterfaceNarrative Contents ManagerInteractive Intervention ControllerSensor & Intervention Data CenterScene ManagerKinect InterfaceBrainwaves & Motion Recognition Interface

Sensor & InterventionData Repository Scene 3BrainwavesScene 2Scene 1. . . Motion

Character,Space,Action, Item, Quest, Contexts, etc.

Behavior Training Platform

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Motion Recognition Learning

Skeletal tracking with Kinect:recognizing 22 different motionsHead tracking with Kinect:recognizing 6 different motions

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Brainwave Recognition LearningData CenterBrainwaves

MindWave InterfaceCollect and Save brainwavesCollect event logsSend to database

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Interactive Game ScenarioScenePurposeGraphicCharacterSpaceItemActionTextInteractive Intervention

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Go to the sea with fishing bag on the shoulderVia Kinect: Monitors the players motion and has the character pause when the player moves.

Via MindWave:Increase the characters moving speed when the attention level increases.Lets go to the sea for fishing.

Can you help me with the fishing bag?

You sit still and see the way to go.

Walking or running

Fishing bag

Mountain path to the sea

Fisherman(Example: a set of fairy tale contents within a scene)

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Motion Recognition

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Behavior Training with Intervention34

Normal playing with the player sitting in placePaused upon recognizing the players motion

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Interactive Intervention

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SummaryProblem solving with knowledge from through AI to through Machine Learning Knowledge learned by machine itself using Big data of IoT/IoEAI Machine Learning Deep Learning

THE MAJORITY OF USRELY ON AI DAILYInternet of Everything

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R E F E R E N C E SJohn McCarthy, What is Artificial Intelligence? http:// www. formal. Stanford. EDU/ jmc/ whatisai/Wiki, Timeline of Artificial Intelligence, http://en.wikipedia.org/wiki/Timeline_of_artificial_intelligenceEric Horvitz, Computation and action under bounded resources, 1990David Moursund, Brief Introduction to Educational Implications of Artificial Intelligence, 2005, 2006Peter Harrington, Machine Learning in Action, Manning Publications, 2012Henrik Brink, Joseph W. Richards, "Real-World Machine Learning,Manning Publications, 2015IBM Watson, http://www.ibm.com/smarterplanet/us/en/ibmwatson/Googles IoT operating system, Brillo, http://www.techspot.com/news/60753-google-iot-operating-system-codenamed-brillo-may-arrive.html

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