ARTIFICIAL INTELLIGENCE€¦ · Chatbots Service providers Media delivery Financial services Fraud...
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HPE DISCOVER MORE ARTIFICIAL INTELLIGENCE
Transcript of ARTIFICIAL INTELLIGENCE€¦ · Chatbots Service providers Media delivery Financial services Fraud...
HPE DISCOVER MORE
ARTIFICIAL INTELLIGENCE
HEWLETT-PACKARD ENTERPRISE, MERCEDES AMG PETRONAS…WHAT ELSE?
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AI IS EVERYWHERE
ManufacturingPredictive and prescriptive maintenance
HealthPersonalized medicine, image analytics
Consumer techChatbots
Service providersMedia delivery
Financial servicesFraud detection, ID verification
GovernmentCyber-security, smart cities and utilities
EnergySeismic and reservoir modeling
RetailVideo surveillance, shopping patterns
BUT KEY QUESTIONS REMAIN …
Skillset
IT Integration
Data Sources
Company Culture
Use case
BARRIERS TO MOVING AT AI SPEED
Unprecedentedvolumes of data
Data silosand complexity Lack of AI talent
and skilled resources
Ever-changing, expanding partner ecosystem
Unpredictable costsand capacity needs
Scalable infrastructure optimized for AI and ML
WHAT DO MY CUSTOMERS WANT ?
Decisions are made Need to make everything run
IT Manager/Admin
Questions / Challenges
– ‘Get control’ of AI IT projects across the org
– Maintain infrastructure standards
– Accelerate Speed of Deployment
– Minimize downtime
– ‘Look smart’ in front of developers/data scientists
What are theylooking for?
– Leverage existing vendor installations
– Automated management
– Expertise in design, deployment & support
– Ability to scale, boundless architecture
– Help on ‘Cloud vs. on-prem’ question
MLArchitect/Developer
Questions / Challenges
– Accelerate Business Model Development
– Keep up with the Technology Frameworks
What are theylooking for?
– Shortest path to learning & deployment
– Options to move “cloud deployed models” to on-premises
– Automated Cloud based offerings on a pay-per-use basis
CIO/CDO
Questions / Challenges
– Edict for Business Transformation
– AI is the path to Digital transformation
– AI is a Board / CEO level discussion now – ‘Why AI’ moving to ‘Why not AI’
What are theylooking for?
– ROI & Business Value on AI
– How/where to start?
– Defining the use case
– First to market with proven results
– Expand AI use in multiple domains
Questions / Challenges
– Latest models and techniques
– How to select the right model and use it
– Data management
– Deliver the promise of AI
What are theylooking for?
– modeling and data management advice
– Quick access to training / inference architecture with proven benchmarks
– Infrastructure needed?
DataScientist
One company … many wishes
THE JOURNEY
New AI/ML Idea
1. Outcomes in Business Value2. Which use cases or workloads3. How to get there and start
CXO makes a decision based business priorities
DATA
Data Scientists Pile of AI Prototypes
Data Center / Production
Edge / Production
IT Manager/ Team
Tools
Workshop/CollaborationInspiration
AI Prototypes
AI/ML Developer
R & D LabPoC
THE COMPLETE JOURNEY
New AI/ML Idea
1. Outcomes in Business Value2. Which use cases or workloads3. How to get there and start
CXO makes a decision based business
priorities
DATA
Data Scientists
Pile of AI Prototypes
Workshop/Collaboration
Inspiration
AI Prototypes
AI/ML Developer
R & D LabPoC
Data Center / Production
Edge / Production
IT Manager/ Team
Tools
Orchestration
Scalability
Edge to Core Model and Data Management
User Experience
PEOPLE
CONFIDENTIAL
CXO makes a decision based business priorities
Data Scientists AI/ML Developer IT Manager/ Team
Workshop/Collaboration
PEOPLE + TECHNOLOGY
R & D LabPoC
Data Center / Production
Edge / Production
CXO makes a decision based business priorities
Data Scientists AI/ML Developer IT Manager/ Team
Workshop/Collaboration
Edge to Core Model and Data Management
Scalability
PEOPLE + TECHNOLOGY + PARTNERS
R & D LabPoC
Data Center /
Production
Edge / Productio
n
CXO makes a decision based
business priorities
Data Scientists AI/ML Developer
IT Manager/ Team
Workshop/Collaboration Orchestration
Edge to Core Model and Data Management
Scalability
Pile of AI Prototypes
AI Prototypes
AI/ML Developer
New AI/ML Idea
1. Outcomes in Business Value2. Which use cases or workloads3. How to get there and start
CXO makes a decision based business
priorities
DATA
Data Scientists
Pile of AI Prototypes
Workshop/Collaboration
Inspiration
AI Prototypes
AI/ML Developer
R & D LabPoC
Data Center / Production
Edge / Production
IT Manager/ Team
Tools
Orchestration
Scalability
Edge to Core Model and Data Management
User Experience
PEOPLE + TECHNOLOGY + PARTNERS = SOLUTIONS FOR BUSINESS OUTCOMES
Best-in-class people, technology and partners = solutions for business outcomesTHE HPE STRATEGIC ADVANTAGE
Best technologyIntegrated AI solutions leveraging HPE’s comprehensive portfolio
− Servers, storage, software, networking and services that work “better together” for the full end-to-end workflow
Best partnersProven global AI ecosystem, ideal for strategic planning / performance optimization
− ISVs
− System Integrators
− Channel /Distributors
− Value added resellers
− Technology partners
− Service providers
Best people Years of delivery expertise; global projects across multiple technologies and AI workloads
− Data scientists
− AI Ambassadors / pre-sales
− Solution architects
− Advisors / Consultants
− AI Centers of Excellence / POC
− Data center technologists
− AI benchmarking / engineers
Mercedes is using “Computer Vision” to setup the car using component level analysis before creating the final car.
BEST-IN-CLASS PEOPLE HELPING MERCEDES
Mercedes Formula 1Racing
People in action
HPE teams created a new AI model
Customer brainstorming sessions and workshops with HPE experts
Joint collaboration decreased processes from 4 weeks to 1 day
Edge Cloud
Compute Storage Fabrics Software
ManagementParallel Libraries
End-to-end
Infrastructure
Optimization
Orchestration Containers Bare Metal Cloud
Swarm Learning
Ingestion Federation Data Pipeline ConsumeRetain Stream Transform
BEST-IN-CLASS TECHNOLOGY
Less Traffic. Less Fatalities. Better Economics
BEST IN CLASS TECHNOLOGY HELPING AUTONOMOUS DRIVING
Technology in action
HPE is powering Autonomous driving working with various car manufacturers and providing the infrastructure from the ingestion station up to the data center.
Collecting Data Moving data Ingestion Station
Data Center
Ground Truth
Simulation
Single Events
BEST IN CLASS PARTNER ECOSYSTEM HELPING BANKING/FSI CUSTOMER
AI solution proactively monitors insider trading, collusion, and improper investment management practices
Partner ecosystem in action
– Partnered with Intelligent Voice (IV)
– Combined HPE and IV solution proactively monitors and stops suspicious activity
– Currently monitoring ~400 traders across email and IM (voice following shortly)
– Global monitoring ~1200 traders worldwide in a dozen languages (future plan)
ACCELERATE YOUR AI ADOPTION WITH HPE’S BLUEPRINTS
Surveillance usingvideo analytics
Airport surveillance– Facial recognition– Queue monitoring– Unattended items
Quality control and prescriptive maintenance
Manufacturing quality control– Identify defects
Prescriptive industrialmaintenance
– based on equipment condition
Speech To Text Natural Language Processing
Communication Surveillance – Speech to Text– Biometric search– Live Call monitoring
Autonomous Driving Connected Cars
HAD– Implementation of level 3 and
level 4 of autonomous driving
PEOPLETECHNOLOGYPARTERNSHIPS
A STORY
24Fixing Predicting
Generic Customized
Obedience Autonomy
Isolated Connected
