Cognitive Systems

Cognitive Services

Cognitive Systems

M. Sc. Lukas Ott

Wintersemester 2016/17Hochschule Aschaffenburg

Nr. January, 2017CSC Proprietary and Confidential

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AgendaGartner Hypecycle

Watson & other Services

What is cognitive? - Basics

Influence of the Cognitive Era on our professional life (Discussion)


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Agenda

Gartner Hypecycle





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Gartner Hype Cycle - Explained

Innovations-TriggerPeak of InflatedExpectTrough of DisillusionmentSlope of EnlightmentPlateau of Productivitytimeexpectations

Nr. January, 2017CSC Proprietary and ConfidentialErnchterung4

Gartner Hype Cycle - Explained



Gartner Hype Cycle 2016

Nr. January, 2017CSC Proprietary and ConfidentialDas Internet der Dinge ist auf dem Peak!7

CSC Trends 2017

Nr. January, 2017CSC Proprietary and ConfidentialAgenda

Gartner Hypecycle





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What are cognitive services?

Nr. January, 2017CSC Proprietary and ConfidentialAlexa Google Clip10

What are cognitive systems? Cognitive systems understand (partly) human expressions.Text, verbal and visual through extraction of the actual intent of problem

They learn through known patterns.For the meaning they need examples and feedback. They interact with humans with their own words and expressions.

Nr. January, 2017CSC Proprietary and ConfidentialWhat are the possibilities a cognitive system like Watson can do?CognitiveNatural Language ProcessingTranslationSpeech to textConfidencePersonality insightsMachine learningTrend analysisContext analysisImage analysis

AnalyticsStructuring unstructured DataBuilding dashboardsCreating a corpus of knowledgeCombining multiple data sourcesKnowledge classificationData integration

Nr. January, 2017CSC Proprietary and ConfidentialWatson Jeopardy

Relationship ExtractionQuestions&AnswersLanguageDetectionPersonalityInsightsKeyword ExtractionImage LinkExtractionFeed DetectionVisualRecognitionConcept ExpansionConceptInsightsDialogSentiment AnalysisText to Speech

Tradeoff AnalyticsNatural LanguageClassifierAuthor ExtractionSpeech toTextRetrieve&RankWatsonNewsLanguageTranslationEntityExtractionTone AnalyzerConceptTaggingTaxonomyTextExtractionMessageResonanceImageTaggingFaceDetectionAnswer GenerationUsage InsightsFusion Q&AVideo AugmentationDecision OptimizationKnowledge GraphRisk StratificationPolicy IdentificationEmotion AnalysisDecision SupportCriteria ClassificationKnowledge CanvasEasy AdaptationKnowledge Studio ServiceStatistical DialogQ&A QualificationFactoid PipelineCaseEvaluationNatural Language ProcessingMachine LearningQuestion AnalysisFeature EngineeringOntology AnalysisJeopardyWatsonWatson ExplorerJeopardyWatsonWatson Knowledge StudioJeopardyWatsonWatsonEngagementAdvisorJeopardyWatsonWatson CompanyAnalyserJeopardyWatsonWatsonAnalytics

IBM Watson is a growing platform and set of solutions & toolingIndustries

Nr. January, 2017CSC Proprietary and ConfidentialIBM Watson Services


Nr. January, 2017CSC Proprietary and ConfidentialAmazon Alexa Homemade Skills for the Smart Home

Nr. January, 2017CSC Proprietary and ConfidentialAzure ML Studio

Cognitive Services (extract):Speech RecognitionKnowledge ExtractionLanguage Recognition

Cortana Intelligence Suite

Nr. January, 2017CSC Proprietary and ConfidentialIntegration into HoloLens17

Cortana skills

Nr. January, 2017CSC Proprietary and ConfidentialCan reuse Alexa Skills as well!18

Agenda

Gartner Hypecycle





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Steps for the semantic intelligence of machines

Nr. January, 2017CSC Proprietary and ConfidentialHow does it work?

Nr. January, 2017CSC Proprietary and ConfidentialUIMA= Unstructured Information Management Architecture21

Named Entity Recognition - NER

Format AnalysesTokenizerNamed Entity RecognitionText

Nr. January, 2017CSC Proprietary and ConfidentialEinToken(Art.: das;Pl.: Tokens) ist eineZeichenkette, der von einerformalen Grammatikein Typ zugewiesen wird22

NLP Part-of-speech Tagging and Treebank

Nr. January, 2017CSC Proprietary and ConfidentialNamed Entity Recognition

POS tag list: NN noun, singular 'desk' NNS noun plural 'desks' NNP proper noun, singular 'Harrison' NNPS proper noun, plural 'Americans' VB verb, base form take VBZ verb, 3rd person sing. present takes23

Named Entity Recognition - NER

Format AnalysesTokenizerNamed Entity RecognitionRelationship detection and ClassificationText

Nr. January, 2017CSC Proprietary and ConfidentialEinToken(Art.: das;Pl.: Tokens) ist eineZeichenkette, der von einerformalen Grammatikein Typ zugewiesen wird24

NLP Semantic nets


Ontology Domaine Knowledge Graph

Reference material from TS-0012: oneM2M Base Ontology


Linked data


Neural networks

Nr. January, 2017CSC Proprietary and ConfidentialSupervised (Regression / Classification)

Types of Machine Learning

SVM (Classification)Unsupervised (Clustering)

K- Means (Clustering)


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Software Algorithms for decision makingRule-based decisionsIf condition then action 1oraction 2Examples:thresholdSimple machine programmingStatistical reasoningSimple regressionExamples:Outlier detectionInterpolationPredictiveMaintenanceMachine LearningClassification tasksExamples:Identification of relevant features from a huge datasetQuality assurance with different metricsArtificial IntelligenceDynamic AdaptionExamples:Self-driving carsHuman-like conversationsIntelligent assistanceevery programmerData ScientistComplex System Engineer


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From Big Data to smart Applications Big Data Web content (Blogs) Social Networks Online Activities (Search and Buy) Enterprise applications (ERP, CRM) Internet of Things (sensor data) Processes Text based content (reports) Knowledge representation Smart ApplicationsPredictionsPlanningAnalysesDiscoverDetectionComparison Data acquisitionData preparation

Natural Language ProcessingEntity- ExtractionRelation - ExtractionTaxonomy - GenerationSemantic Graph

Machine based reasoningIntentsRecommendationsContextSemantic searchRulesMachine learning


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Nr. January, 2017CSC Proprietary and ConfidentialPeople Understand what kind of people are interacting with your application

Interact Understand the context and the intent

Naturally - Understand and respond like people normally would doInteract naturally with people


Findevidence tosupport responses

Cognitive Computing and Analytics

Trained to Understand, Discover & LearnIngestrelevant data across a broad domain to create a repositoryUnderstandan ambiguousEnglish languageinquiryGeneratepotentially relevantresponsesRankresponses with confidance factorsand adaptfrom machinelearning

Hello Mickey,

Welcome toABC Insurance

Train



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Pepper the first robot that read emotions Already in use for shops and trade fairs


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Agenda

Gartner Hypecycle





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Nr. January, 2017CSC Proprietary and ConfidentialOutlook and abstract

Cognitive Services

Watson/ Cortana/ Alexa Services

Future of Artificial Intelligence

Nr. January, 2017CSC Proprietary and ConfidentialVenetzung mit Cloud und MobilityFunktion As a servivceSemantisch Daten mit Bedeutung fr maschinen verstndlich machen ( Zukunft A.I. / Sprachassisten)39

Thank you!

Questions?

Feedback!

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QuellenGartner Hype Cyclehttp://www-05.ibm.com/de/watson/index.htmlIBM Watson Academyhttps://www.ibm.com/watson/developercloud/project-intu.htmlIBM Watson Developer Conference, November 2016, San FranciscoHow to Make Intelligent Robots That Understand the World | Danko Nikoli | TEDhttp://www.slideshare.net/DankoNikolic1/how-data-science-works-and-how-can-customers-helphttps://www.microsoft.com/cognitive-services/en-us/apishttp://www.economist.com/technology-quarterly/2017-01-07


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Cognitive Systems

Education

Transcript of Cognitive Systems