vital.ai creating intelligent apps
DESCRIPTION
Vital.AI's Big Data App Platform allows creating data-driven apps rapidly.TRANSCRIPT
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C r e a t i n g I n t e l l i g e n t A p p sw i t h S e m a n t i c s & B i g D a t a
O c t o b e r 2 , 2 0 1 3
Marc C. Hadfield, FounderEmail: [email protected]
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<introduction>Marc HadfieldFounder of Vital.AI
Vital.AIBig Data Application Platform:
Semantics & Big Data in one platform,
combining multiple Data Analysis
techniques.
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Intelligent Applications
Development Processes
Business Value
Today:
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Intelligent Applications:
...learn from experience.
Thus, are experience-driven: data-driven.
“self-optimizing”
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Data-Driven Applications
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Moderni.st
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Moderni.st
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Personal Agent App
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Why are data-driven applications different?
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User Interface
Business Logic
Database
Traditional Applications
Why are data-driven applications different?
“sta%c”
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Why are data-driven applications different?
“dynamic”
User Interface
Business Logic
Events
Data-Driven Applications
Data
Analytics
Derived Behavior
Logic
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Data-Driven Applications use many different technologies, with many different skill sets:greater power, higher cost.
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Why do we want a data-driven application?
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What are the components of a data-driven application?
Data Collection
Dynamically Adjust Behaviors
Data Analysis / Feedback
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Implementing a Data-Driven Application.
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Implementation Goals:
Off the shelf?
Minimize Impedance Mismatch:Mobile/Web User Interface vs.
Semantic vs.Big Data vs.
...
Efficient Development Processes
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Vital.AI Platform Stack
Clean separation of responsibilities and skill sets.
Rapid Development of Data-Driven Apps.
VitalSigns: Ontology-based Data Model.
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Vital Prime
REST Interface
Collects Real-Time Events
Database Interfaces:HBase, Allegrograph, ...
Workflow Interface
Script Engine
In-Memory Analytics
User State Management
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Vital Flows
Implements Workflows:
Natural Language Processing
Run Predictive Analytics
Graph Analytics
Logical Inference
Many open-source components in a common workflow framework.
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Hadoop
Implements Big Data Analysis:
Machine Learning
Build Predictive Models
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Vital Core Ontology
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Vital Core Ontology
Vital Domain Ontology
Application Domain Ontology
Extending the Ontology
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Generating Data Bindings with VitalSigns:
Ontology VitalSigns
Groovy Bindings
Semantic Bindings
Hadoop Bindings
Prolog Bindings
Graph Bindings
HBase Bindings
JavaScript Bindings
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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
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Editing the Ontology
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Developing with the Ontology in UI, Hadoop, NLP, Scripts, ...
Node:Person Node:PersonEdge:hasFriend
Set<Friend> person123.getFriends()
“Best Practices” in Ontology Development.
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Data Analysis
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Using Natural Language Processing
Topic Categorization Extract Entities
Dialogue System Entity Normalization
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Using Graph Analytics
PageRank, Centrality, Interest Graph, ...
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Using Machine Learning
Implemented via Hadoop
Algorithms from Mahout
Build Predictive Models
Models used in Workflows
Data defined in Ontology
Classification, Clustering...
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Data Visualization - Cytoscape
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Data Management - Dashboard, Wiki
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Examples
Shopping Recommendation App
Personal Agent App
Content Recommendation App
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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
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Personal Agent
Dialogue System
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Personal Agent
Interest Graph Recommendations
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Moderni.st
App Server
Vital Prime
IntegratorFlow
NLP Flow Logger Flow
Inference Flow
VITAL APIVitalSigns
Web Browser /Mobile Device
HDFS
Hbase Hadoop JobsMahout
Vital Flows
Flume
Allegrograph
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Creating an Intelligent App
Create User Interface.Use Vital Client, Send Signals
Create App Ontology, includingDomain Classes & Events/Signals
Define Workflows for Data Processing
Define Predictive Models, Build Models
Create scripts for App Functionality
Deploy Components
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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.
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Business Value
Intelligent App.
Efficient, Rapid Development.
Flexibility to learn, adapt, improve.
Greatly reduce risk.
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For more information, please contact:Marc C. Hadfield, FounderE: [email protected]: 917.463.4776
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THANK YOU!
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