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Vital.AI Creating Intelligent Apps
 

Vital.AI Creating Intelligent Apps

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Vital.AI's Big Data App Platform allows creating data-driven apps rapidly.

Vital.AI's Big Data App Platform allows creating data-driven apps rapidly.

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    Vital.AI Creating Intelligent Apps Vital.AI Creating Intelligent Apps Presentation Transcript

    • Creating Intelligent Apps with Semantics & Big Data O c t o b e r 2 , 2 0 1 3 Marc C. Hadfield, Founder Email: marc@vital.ai Thursday, October 3, 13
    • <introduction> Marc Hadfield Founder of Vital.AI Vital.AI Big Data Application Platform: Semantics & Big Data in one platform, combining multiple Data Analysis techniques. Thursday, October 3, 13
    • Intelligent Applications Development Processes Business Value Today: Thursday, October 3, 13
    • Intelligent Applications: ...learn from experience. Thus, are experience-driven: data-driven. “self-optimizing” Thursday, October 3, 13
    • Data-Driven Applications Thursday, October 3, 13
    • Moderni.st Thursday, October 3, 13
    • Moderni.st Thursday, October 3, 13
    • Personal Agent App Thursday, October 3, 13
    • Why are data-driven applications different? Thursday, October 3, 13
    • User Interface Business Logic Database Traditional Applications Why are data-driven applications different? “sta%c” Thursday, October 3, 13
    • Why are data-driven applications different? “dynamic” User Interface Business Logic Events Data-Driven Applications Data Analytics Derived Behavior Logic Thursday, October 3, 13
    • Data-Driven Applications use many different technologies, with many different skill sets: greater power, higher cost. Thursday, October 3, 13
    • Why do we want a data-driven application? Thursday, October 3, 13
    • What are the components of a data-driven application? Data Collection Dynamically Adjust Behaviors Data Analysis / Feedback Thursday, October 3, 13
    • Implementing a Data-Driven Application. Thursday, October 3, 13
    • Implementation Goals: Off the shelf? Minimize Impedance Mismatch: Mobile/Web User Interface vs. Semantic vs. Big Data vs. ... Efficient Development Processes Thursday, October 3, 13
    • Vital.AI Platform Stack Clean separation of responsibilities and skill sets. Rapid Development of Data-Driven Apps. VitalSigns: Ontology-based Data Model. Thursday, October 3, 13
    • Vital Prime REST Interface Collects Real-Time Events Database Interfaces: HBase, Allegrograph, ... Workflow Interface Script Engine In-Memory Analytics User State Management Thursday, October 3, 13
    • Vital Flows Implements Workflows: Natural Language Processing Run Predictive Analytics Graph Analytics Logical Inference Many open-source components in a common workflow framework. Thursday, October 3, 13
    • Hadoop Implements Big Data Analysis: Machine Learning Build Predictive Models Thursday, October 3, 13
    • Vital Core Ontology Thursday, October 3, 13
    • Vital Core Ontology Vital Domain Ontology Application Domain Ontology Extending the Ontology Thursday, October 3, 13
    • Generating Data Bindings with VitalSigns: Ontology VitalSigns Groovy Bindings Semantic Bindings Hadoop Bindings Prolog Bindings Graph Bindings HBase Bindings JavaScript Bindings Thursday, October 3, 13
    • person123.name = "John" person123.worksFor.company456 <person123> <hasName> "John" <worksFor123> <hasSource> <person123> <worksFor123> <hasDestination> <company456> <worksFor123> <hasType> <worksFor> person123, Node:type=Person, Node:hasName="John" worksFor123, Edge:type=worksFor, Edge:hasSource=person123, Edge:hasDestination=company456 Groovy RDF HBase Data Representations Thursday, October 3, 13
    • Editing the Ontology Thursday, October 3, 13
    • Developing with the Ontology in UI, Hadoop, NLP, Scripts, ... Node:Person Node:PersonEdge:hasFriend Set<Friend> person123.getFriends() “Best Practices” in Ontology Development. Thursday, October 3, 13
    • Data Analysis Thursday, October 3, 13
    • Using Natural Language Processing Topic Categorization Extract Entities Dialogue System Entity Normalization Thursday, October 3, 13
    • Using Graph Analytics PageRank, Centrality, Interest Graph, ... Thursday, October 3, 13
    • Using Machine Learning Implemented via Hadoop Algorithms from Mahout Build Predictive Models Models used in Workflows Data defined in Ontology Classification, Clustering... Thursday, October 3, 13
    • Data Visualization - Cytoscape Thursday, October 3, 13
    • Data Management - Dashboard, Wiki Thursday, October 3, 13
    • Examples Shopping Recommendation App Personal Agent App Content Recommendation App Thursday, October 3, 13
    • Content Recommendation REST Interface Vital Client Vital Prime Vital Flow Queue Integrator NLP HadoopML Model S3 Elastic Map/Reduce Mahout 300M Users 100K Publishers NLP Machine Learning Content + User Signals Recommendations Thursday, October 3, 13
    • Personal Agent Dialogue System Thursday, October 3, 13
    • Personal Agent Interest Graph Recommendations Thursday, October 3, 13
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    • Moderni.st App Server Vital Prime Integrator Flow NLP Flow Logger Flow Inference Flow VITAL API VitalSigns Web Browser / Mobile Device HDFS Hbase Hadoop Jobs Mahout Vital Flows Flume Allegrograph Thursday, October 3, 13
    • Creating an Intelligent App Create User Interface. Use Vital Client, Send Signals Create App Ontology, including Domain Classes & Events/Signals Define Workflows for Data Processing Define Predictive Models, Build Models Create scripts for App Functionality Deploy Components Thursday, October 3, 13
    • Development Processes Use the right tool for the right job, & the right people for the right job. Integrated Framework. Coordinate on Ontology. Eliminate Data Mis-Matches. Clean code separation of “paradigms.” Solve “Variety” Big Data challenge. Thursday, October 3, 13
    • Business Value Intelligent App. Efficient, Rapid Development. Flexibility to learn, adapt, improve. Greatly reduce risk. Thursday, October 3, 13
    • For more information, please contact: Marc C. Hadfield, Founder E: marc@vital.ai P: 917.463.4776 51 THANKYOU! Thursday, October 3, 13
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