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Machine Learning, Artificial Intelligence and IBM [email protected]
Cognitive Solution ArchitectCountry Technical Leader
Machine Learning morning TTY 21.2.2017
Agenda• What is IBM Watson• Benefits for Business• How to Get Started
© 2017 IBM [email protected]
IBM Watson in Different Industries Today
https://youtu.be/PujCkDAXji8© 2017 IBM [email protected]
Digitalisation
CloudSocial
Internet of Things
Mobile
CognitiveSecurity
Analytics
Cyber-Physical SystemsSmart Service Systems
Industry 4.0Servitisation
© 2017 IBM [email protected]
Why Cognitive Computing?
4V of Data(Volume, Variety, Velocity, Veracity)
Cap
abili
ty to
Cha
nge
Performance Gap
Opportunity…new ways of working, operating, thinking
Achievement…but riding by the constraints of limited capabilities, organization achievements would be at slower pace
Cognitivecomputing
© 2017 IBM [email protected]
What is a Biological Cognitive System?
© 2017 IBM [email protected]
Common capability: to use language for communicating and coordinating reasoning and interactions and the accumulation of knowledge for collectively better outcomes.
What is the Goal of Digital Cognitive Systems?
Artificial Intelligence = Machine Intelligence Augmented Intelligence =
Human Intelligence + Machine Intelligence
© 2017 IBM [email protected]
Star Trek: Mr Data Iron Man: Tony Stark & Jarvis
This is the Goal
An individual smart machine vs Man and machine co-operationCapability to use language with machines for coordinating and reasoning for better outcomes. Increases human intelligence by use and not diminish it.
We Need a New Way of Computing …
Tabulation
1900 - 1950 - 2011 -
Programmatic Era Cognitive Era
Traditional IT• Structured data (local)• Deterministic Applications• Machine Language• Systems of records
• Structured & unstructured (global)• Probabilistic Applications• Discovery Oriented• Natural Language• Systems of engagement
Industry Solutions
BusinessAnalytics
Big Data
Watson
Learn by example
Learn by programming
CloudComputing
© 2017 IBM [email protected]
IBM Watson Is a Cognitive System That…
99%60%10%
Understandsnatural language and human speech
Adapts and Learns from user selections and responses
Reasons for better outcomes
3
2
1
© 2017 IBM [email protected]
When to Use Cognitive Computing?
© 2017 IBM [email protected]
• When problems are complex, information and situation are shifting, and outcome depends on context
• Diverse, changing data sources, including unstructured (text, images) • No clearly right answers: Data is complex and ambiguous, conflicting evidence • Ranked (confidence scored), multiple answers are preferred (alternatives) • Context dependent: time, user, location, point in task • Human-computer partnership and dialog are required
When NOT to Use Cognitive Computing?
• When predictable, repeatable results are required (e.g. sales reports) • When all data is structured, numeric and predictable
When a probabilistic approach is not desirable • When existing transactional systems are adequate • When interaction, especially in natural language, is not necessary
© 2017 IBM [email protected]
Watson Discovery APIWatson Retrieve and Rank API
© 2017 IBM [email protected]
Relationship Extraction
Conversation
LanguageDetection
PersonalityInsights
Keyword Extraction
Image LinkExtraction
Feed Detection
VisualRecognition
Concept Expansion
ConceptInsights
Discovery Sentiment Analysis
Text to Speech
Tradeoff Analytics
Natural LanguageClassifier
Author Extraction
Speech toText
Retrieve&
Rank
WatsonNews
LanguageTranslatio
n
EntityExtraction
Tone Analyzer
ConceptTagging
Taxonomy
TextExtraction
MessageResonance
ImageTagging
FaceDetection
Answer Generation
Usage Insights
Fusion Q&A
Video Augmentation
Decision Optimization
Knowledge Graph
Risk Stratification
Policy Identification
Emotion Analysis
Decision Support
Criteria Classification
Knowledge Canvas
Easy Adaptation
Knowledge Studio Service
Statistical Dialog
Q&A Qualification
Factoid Pipeline
CaseEvaluation
IBM BlueMix Watson APIs Watson has 29 APIs, more to come...
Natural Language Processing
Machine Learning
Question Analysis
Feature Engineering
Ontology Analysis
© 2017 IBM [email protected] LEGO bricks to build cognitive solutions
Benefits for Business
© 2017 IBM [email protected]
The Goals Why Cognitive Technology is Used
© 2017 IBM [email protected]
https://public.dhe.ibm.com/common/ssi/ecm/co/en/cow03020usen/COW03020USEN.PDF
Achieved Benefits
© 2017 IBM [email protected]
Examples
© 2017 IBM [email protected]
Examples
© 2017 IBM [email protected]
How to Get Started
© 2017 IBM [email protected]
Is This the Reality Today…
© 2017 IBM [email protected]
How to Get Started – Business Value Focused Increments
• The secret to getting ahead is getting started, and getting started is easier than you might think
• Cognitive technology adoption comes in all shapes and sizes, and most often starts relatively small
• What the most successful projects have in common, no matter how ambitious, is they begin with a clear view of what cognitive technology can and cannot do
• Consider how to leverage cognitive technology. Adoption only makes sense if it aligns with strategic priorities
• Your adoption strategy should support profitable outcomes like saving money, gaining customers or increasing revenue.
© 2017 IBM [email protected]
Why Should I be Interested?
• Unarguably ML, AI & cognitive technologies will have a key role in future society
• The technology is available today to start learning and gaining expertise
• Early adopters can leverage the window of opportunity
© 2017 IBM [email protected]
Resources
© 2017 IBM [email protected]