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WIFI SSID:SparkAISummit | Password: UnifiedAnalytics
Rafael Zotto, HP
Franco Vieira, HP
A Virtual Assistant
Ecosystem for Workflow and
Workplace Optimization
#UnifiedAnalytics #SparkAISummit
//ABOUT US
3#UnifiedAnalytics #SparkAISummit
//RAFAEL ZOTTO
Holds a master degree in Computer Science focused on high-performance
computing. Specialized in parallel and distributed computing with a special interest
in cloud and serverless computing. Works for HP Inc. for more than a decade acting
as a software engineer for print firmware and wearable technologies. Currently works
in the data science research team as a software engineer and solutions architect
having most activities related to applied AI and conversational interfaces.
//FRANCO VIEIRA
Professional with vast experience in information technology working in
software development, cloud computing, and machine learning projects. In
the past 5 years, Franco has been developing new services focused on activity
recognition, content sharing, and device health. Currently, works in HP
Personal Systems Software producing machine learning solutions on the edge.
Franco holds a degree in computer science.
//LEARNING FROM EXPERIENCES
4#UnifiedAnalytics #SparkAISummit
//UNIFIED APPROACH TO ANALYTICS
5#UnifiedAnalytics #SparkAISummit
//RICH INSIGHTS
6#UnifiedAnalytics #SparkAISummit
//PROBLEM STATEMENT
7#UnifiedAnalytics #SparkAISummit
_LOTS of INFORMATION
_Just a FEW reports
_Not always CONFIGURABLE
_TIED to development cycles
//Offer a QUICK way to share INFORMATION
//CONTEXT
8#UnifiedAnalytics #SparkAISummit
//FLEET MANAGER
_MANAGES a fleet of devices
_Need to UNDERSTAND status
_FIX problems
//END-USER
_USES one or more devices
_Wants assets AVAILABLE
_Interested on PERFORMANCE
//OUR APPROACH
9#UnifiedAnalytics #SparkAISummit
//Be AVAILABLE
//Offer DYNAMIC ways to access the INFORMATION
//Using NATURAL LANGUAGE
//INVESTIGATION
10#UnifiedAnalytics #SparkAISummit
//Generate STRUCTURED QUERIES from Natural Language
_SEQ2SQL, SQLNet, Coarse2Fine, …
//INTENT recognition / Chatbot PLATFORMS
_DialogFlow, LUIS, AWS LEX, Watson, …
//CHATBOT PLATFORM ANATOMY
11#UnifiedAnalytics #SparkAISummit
INTENTS UTTERANCES SLOTS
FULFILLMENT
COMPOSED
BY
MIGHT
HAVE
//EXAMPLE
_“I need to travel from San Francisco to Philadelphia next weekend”
SLOT 1: Origin SLOT 2: Destination SLOT 3: Date
//CHATBOT AS PART OF A SOLUTION
12#UnifiedAnalytics #SparkAISummit
//Our INSIGHTS and PREDICTIONS refers to a DOMAIN
//Our DOMAINS can be mapped to INTENTS
_Battery
_Thermal
_CPU
_…
//INTENTS can be fulfilled with INSIGHTS and PREDICTIONS
_MULTI-CONTEXT dialog management
//HIGH-LEVEL OVERVIEW
13#UnifiedAnalytics #SparkAISummit
ANALYTICS SERVICES
GRAPHQL
SAVES TO
WEB PORTAL
SLACK
CALL CENTER
MOBILE APP
INTENT
RECOGNITION
DESKTOP APP
LAMBDA
FUNCTION
FULFILLMENT
USES
_DYNAMIC response created
CONTEXT is created for the SESSION RDS
QUERY
//EASY access to our GOLD DATA
//UNDERSTAND user needs.
//DEMO
14#UnifiedAnalytics #SparkAISummit
//CREATING A PLATFORM
15#UnifiedAnalytics #SparkAISummit
ANALYTICS SERVICES
GRAPHQL
SAVES TO
WEB PORTAL
SLACK
CALL CENTER
MOBILE APP
INTENT
RECOGNITION
DESKTOP APP
LAMBDA
FUNCTION
FULFILLMENT
USES
RDS
QUERY
_Support for
MULTIPLE INTENTS
_Gathering data from
MULTIPLE SOURCES
//LEARN FROM MISSED UTTERANCES
16#UnifiedAnalytics #SparkAISummit
//UNDERSTAND what we still DON’T KNOW
MISSED UTTERANCES INPUT TEXT
ENTITIES KEY PHRASES
FILTERING SLOTS KNOWLEDGE NEEDED
INSIGHT DISCOVERY
INTENT RECOGNITION
//EXAMPLE
_“What was the health grade of my device fleet yesterday”
KNOWLEDGE : 0.99+ KNOWLEDGE: 0.99+ DATE: 0.98
//ONGOING WORK
_DEVICES are THINGS connected to our stack.
_We have INSIGHTS and PREDICTIONS ready to be used.
_Why not DELIVER them to the interested part?
17#UnifiedAnalytics #SparkAISummit
//IMMEDIATE delivery
_As soon as detected, NOTIFICATION is delivered to the USER.
//SCHEDULED delivery
_Kept to be delivered as a FUTURE or RECURRENT NOTIFICATION.
//DELIVERING INSIGHTS
18#UnifiedAnalytics #SparkAISummit
ANALYTICS SERVICES
EVENTS
NOTIFICATIONS ACTIONS
PRODUCE
TRIGGER
DELIVERED AS
_EXTENSIBLE list of PLUGINS
_ACT to address an issue
_WATCH the system
WRITES TO
EVENT SINK
WRITES TO
PROCESSING
INITIATE
SIMPLE QUEUE
MQTT
//DEMO
19#UnifiedAnalytics #SparkAISummit
00
//NEXT STEPS
//It’s all about USER-EXPERIENCE
_HELP fleet-managers.
_AMAZE end-users.
_ACT in advance.
_UNDERSTAND users profile.
20#UnifiedAnalytics #SparkAISummit
DON’T FORGET TO RATE
AND REVIEW THE SESSIONS
SEARCH SPARK + AI SUMMIT

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A Virtual Assistant Ecosystem for Workflow and Workplace Optimization

  • 1. WIFI SSID:SparkAISummit | Password: UnifiedAnalytics
  • 2. Rafael Zotto, HP Franco Vieira, HP A Virtual Assistant Ecosystem for Workflow and Workplace Optimization #UnifiedAnalytics #SparkAISummit
  • 3. //ABOUT US 3#UnifiedAnalytics #SparkAISummit //RAFAEL ZOTTO Holds a master degree in Computer Science focused on high-performance computing. Specialized in parallel and distributed computing with a special interest in cloud and serverless computing. Works for HP Inc. for more than a decade acting as a software engineer for print firmware and wearable technologies. Currently works in the data science research team as a software engineer and solutions architect having most activities related to applied AI and conversational interfaces. //FRANCO VIEIRA Professional with vast experience in information technology working in software development, cloud computing, and machine learning projects. In the past 5 years, Franco has been developing new services focused on activity recognition, content sharing, and device health. Currently, works in HP Personal Systems Software producing machine learning solutions on the edge. Franco holds a degree in computer science.
  • 5. //UNIFIED APPROACH TO ANALYTICS 5#UnifiedAnalytics #SparkAISummit
  • 7. //PROBLEM STATEMENT 7#UnifiedAnalytics #SparkAISummit _LOTS of INFORMATION _Just a FEW reports _Not always CONFIGURABLE _TIED to development cycles //Offer a QUICK way to share INFORMATION
  • 8. //CONTEXT 8#UnifiedAnalytics #SparkAISummit //FLEET MANAGER _MANAGES a fleet of devices _Need to UNDERSTAND status _FIX problems //END-USER _USES one or more devices _Wants assets AVAILABLE _Interested on PERFORMANCE
  • 9. //OUR APPROACH 9#UnifiedAnalytics #SparkAISummit //Be AVAILABLE //Offer DYNAMIC ways to access the INFORMATION //Using NATURAL LANGUAGE
  • 10. //INVESTIGATION 10#UnifiedAnalytics #SparkAISummit //Generate STRUCTURED QUERIES from Natural Language _SEQ2SQL, SQLNet, Coarse2Fine, … //INTENT recognition / Chatbot PLATFORMS _DialogFlow, LUIS, AWS LEX, Watson, …
  • 11. //CHATBOT PLATFORM ANATOMY 11#UnifiedAnalytics #SparkAISummit INTENTS UTTERANCES SLOTS FULFILLMENT COMPOSED BY MIGHT HAVE //EXAMPLE _“I need to travel from San Francisco to Philadelphia next weekend” SLOT 1: Origin SLOT 2: Destination SLOT 3: Date
  • 12. //CHATBOT AS PART OF A SOLUTION 12#UnifiedAnalytics #SparkAISummit //Our INSIGHTS and PREDICTIONS refers to a DOMAIN //Our DOMAINS can be mapped to INTENTS _Battery _Thermal _CPU _… //INTENTS can be fulfilled with INSIGHTS and PREDICTIONS _MULTI-CONTEXT dialog management
  • 13. //HIGH-LEVEL OVERVIEW 13#UnifiedAnalytics #SparkAISummit ANALYTICS SERVICES GRAPHQL SAVES TO WEB PORTAL SLACK CALL CENTER MOBILE APP INTENT RECOGNITION DESKTOP APP LAMBDA FUNCTION FULFILLMENT USES _DYNAMIC response created CONTEXT is created for the SESSION RDS QUERY
  • 14. //EASY access to our GOLD DATA //UNDERSTAND user needs. //DEMO 14#UnifiedAnalytics #SparkAISummit
  • 15. //CREATING A PLATFORM 15#UnifiedAnalytics #SparkAISummit ANALYTICS SERVICES GRAPHQL SAVES TO WEB PORTAL SLACK CALL CENTER MOBILE APP INTENT RECOGNITION DESKTOP APP LAMBDA FUNCTION FULFILLMENT USES RDS QUERY _Support for MULTIPLE INTENTS _Gathering data from MULTIPLE SOURCES
  • 16. //LEARN FROM MISSED UTTERANCES 16#UnifiedAnalytics #SparkAISummit //UNDERSTAND what we still DON’T KNOW MISSED UTTERANCES INPUT TEXT ENTITIES KEY PHRASES FILTERING SLOTS KNOWLEDGE NEEDED INSIGHT DISCOVERY INTENT RECOGNITION //EXAMPLE _“What was the health grade of my device fleet yesterday” KNOWLEDGE : 0.99+ KNOWLEDGE: 0.99+ DATE: 0.98
  • 17. //ONGOING WORK _DEVICES are THINGS connected to our stack. _We have INSIGHTS and PREDICTIONS ready to be used. _Why not DELIVER them to the interested part? 17#UnifiedAnalytics #SparkAISummit //IMMEDIATE delivery _As soon as detected, NOTIFICATION is delivered to the USER. //SCHEDULED delivery _Kept to be delivered as a FUTURE or RECURRENT NOTIFICATION.
  • 18. //DELIVERING INSIGHTS 18#UnifiedAnalytics #SparkAISummit ANALYTICS SERVICES EVENTS NOTIFICATIONS ACTIONS PRODUCE TRIGGER DELIVERED AS _EXTENSIBLE list of PLUGINS _ACT to address an issue _WATCH the system WRITES TO EVENT SINK WRITES TO PROCESSING INITIATE SIMPLE QUEUE MQTT
  • 20. //NEXT STEPS //It’s all about USER-EXPERIENCE _HELP fleet-managers. _AMAZE end-users. _ACT in advance. _UNDERSTAND users profile. 20#UnifiedAnalytics #SparkAISummit
  • 21. DON’T FORGET TO RATE AND REVIEW THE SESSIONS SEARCH SPARK + AI SUMMIT