machine learning crash course 2017 - genova - dibris - iit - mit
TRANSCRIPT
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Artificial Intelligence to make precise decisions
June 28, 2017Pietro Leo Executive Architect & CTOChief scientist, and research strategist IBM ItalyIBM Academy of Technology Leadership Teampieroleo.com
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Hype Cycle for Emerging Technologies, 2016 (Gartner)
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Well done folks!Now it’s time to start to work…. seriously
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DECISION
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You shared your position with me and can guess your mobility need. I can take you where you need to be
Just enjoy your new experience. Stay safe as in your friend’s home
I know what is needed for you, even before you order it
Please, come with me and stay by me.I know your content I can take care of all your digital life
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Video: http://www.digitaltrends.com/home/grush-toothbrush-wins-americas-greatest-makers/
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http://www.grushgamer.com/
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HYPERDATAWORLD
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Source: http://www.bloomberg.com/video/meet-the-world-s-most-connected-man-Vs~LzkbkR7yhjza~7nji1g.html
Meet theWorld's Most Connected Man
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12Image source: http://personalexcellence.co/blog/i deal-beauty/
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13Image source: http://personalexcellence.co/blog/i deal-beauty/
City
Lifestyle
ZIPcode
Costal vsInland Maritalstatus
Generation
Location
FamilySize
Gender
Income Level
Competitors
Age
Loyalty&CardActivity
Revenue Size
Life Stages
Eductation
Legalstatus
Sector
Industry
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Image source: http://personalexcellence.co/blog/i deal-beauty/
City
Lifestyle
ZIPcode
Costal vsInland Maritalstatus
Generation
Location
FamilySize
Gender
Income Level
Competitors
Age
Loyalty&CardActivity
Revenue Size
Life Stages
Eductation
Legalstatus
Sector
Industry
SubscriptionsDate on Site
Wish List
Size of Network
Check-ins
App usage duration
Number of Apps on Device
Deposits/Withdrawals
Device UsagePurchase History
FollowingFollowers
Likes
Number of Hashtags used
History of Hashtags
Search Strings entered
Sequence of visits
Time/Day log in
Time spent on site
Time spent on page
Frequency of Search
Videos Viewed
Photos liked
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Image source: http://personalexcellence.co/blog/i deal-beauty/
City
Lifestyle
ZIPcode
Costal vsInland Maritalstatus
Generation
Location
FamilySize
Gender
Income Level
Competitors
Age
Loyalty&CardActivity
Revenue Size
Life Stages
Eductation
Legalstatus
Sector
Industry
SubscriptionsDate on Site
Wish List
Size of Network
Check-ins
App usage duration
Number of Apps on Device
Deposits/Withdrawals
Device UsagePurchase History
FollowingFollowers
Likes
Number of Hashtags used
History of Hashtags
Search Strings entered
Sequence of visits
Time/Day log in
Time spent on site
Time spent on page
Frequency of Search
Videos Viewed
Photos liked
Sentiment
Tone
Euphemisms
Hedonism
Extroversion
Face Recognition
Openess
Colloquialism
Reasoning Strategies
Language Modeling
DialogIntent
Latent Semantic Analysis
Phonemes
Ontology Analysis
Linguistics Image Tags
Question Analysis
Self-transcendent
Affective Status
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Image source: http://personalexcellence.co/blog/i deal-beauty/
City
Lifestyle
ZIPcode
Costal vsInland Maritalstatus
Generation
Location
FamilySize
Gender
Income Level
Competitors
Age
Loyalty&CardActivity
Revenue Size
Life Stages
Eductation
Legalstatus
Sector
Industry
SubscriptionsDate on Site
Wish List
Size of Network
Check-ins
App usage duration
Number of Apps on Device
Deposits/Withdrawals
Device UsagePurchase History
FollowingFollowers
Likes
Number of Hashtags used
History of Hashtags
Search Strings entered
Sequence of visits
Time/Day log in
Time spent on site
Time spent on page
Frequency of Search
Videos Viewed
Photos liked
Sentiment
Tone
Euphemisms
Hedonism
Extroversion
Face Recognition
Openess
Colloquialism
Reasoning Strategies
Language Modeling
DialogIntent
Latent Semantic Analysis
Phonemes
Ontology Analysis
Linguistics Image Tags
Question Analysis
Self-transcendent
Affective Status
X-rays (CT scans) sound (ultrasound), magnetism (MRI), Radioactive (SPECT, PET)light (endoscopy, OCT)
Bio-Images
Clinical/Biochemical DataMicrobiome
EnvironmentDNAProteome
Steps
Nutrition
Genetics
Runs
Food
Source: Bipartisan Policy Center, “F” as in Fat: How Obesity Threatens America’s Future (TFAH/RWJF, Aug. 2013)
Internet of Body
BMI
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Rapid growth of exogenous data is transforming healthcare
6 Terabytes
60%Exogenous Factors
1100 TerabytesVolume, Variety, Velocity, Veracity:Educational records, Employment Status, Social Security Accounts, Mental Health Records, Caseworker Files, Fitbits, Home Monitoring Systems, and more…
0.4 TerabytesElectronic Medical / Health Records, Physician Management Systems, Claims Systems and more…
30%Genomics Factors
10%Clinical Factors
IBM Watson Health // SOURCE: ©2015 J.M. McGinnis et al., “The Case for More Active Policy Attention to Health Promotion,” Health Affairs 21, no. 2 (2002):78–93
Data Generated per Life
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Leveraging Exogenous Data for Chronic Care
60%Exogenous Factors
30%Genomics Factors
10%Clinical Factors
SOURCE: ©2015 J.M. McGinnis et al., “The Case for More Active Policy Attention to Health Promotion,” Health Affairs 21, no. 2 (2002):78–93
Glucose Monitoring
Calorie Intake
Stress LevelsPhysical Activity
Other vital signs SocialInteraction
Affinity (retail)
Sleep Pattern
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> 2.5 Trillion PDF Files in the World
Majority with public and private enterprises and institutions.
Enterprise HYPERDATA
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Multi-Modal Rich data: Text, Tables, Images, Audio, Video, Formats, Hierarchy….
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A small step with a big result:Raw Data to Business Artifacts: Understanding PDFs
DocumentStructure
Model
Multi-Modal Rich data: Text, Tables, Images, Audio, Video, Formats, Hierarchy….
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PRECISION
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Leveraging the Explosion of Data in Medicine An Impossible Task Without Analytics and New advanced Artificial Intelligence Computing Models
1000
Fact
s pe
r Dec
isio
n
10
100
1990 2000 2010 2020
Human Cognitive Capacity
Electronic Health Records (Clinical Data)
Internet of Things (Exogenous Data)The Human Genome (Genomic Data)
Capturing the Value of Data: Big Changes Ahead
Medical error—the third leading cause of death in the US
Source: BMJ 2016; 353 doi: http://dx.doi.org/10.1136/bmj.i2139 (Published 03 May 2016) Cite this as: BMJ 2016;353:i2139
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Body Mass Index (BMI)
Mass (weight - Kg) / height (cm) x height (cm)
You are “Normal” if your BMI is between 18.5 and 24.99
Adolphe Quetelet, 1832
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Practice Pearls:• BMI - Body mass index is a strong and independent risk factor for being diagnosed with type 2 diabetes mellitus• Type 2 diabetes risk may be incrementally higher in those with a higher body mass index• Understanding the risk factors helps to shorten the time to diagnosis and treatment
How precise could be a “simple” signal
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© 2017 International Business Machines Corporation
The way to find information
The way to make precise decisions
Big
Dat
a ++
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© 2017 International Business Machines Corporation
Technology ingredients to make precise decisions: driving new Capability for Business
Artificial IntelligenceRange of techniques including natural language understanding,knowledge, reasoning and planning, for advanced tasks
Cognitive ComputingLeverage a combination decision-makingand reasoning strategies over deep domain models and evidence-based explanations, using AI/ Machine Learning tools.
Machine LearningStatistical analysis forpattern recognition to make data-driven predictions
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© 2017 International Business Machines Corporation
Research at the heart of core AI
2
Comprehension: From video and text to rich human perception
Learning and Reasoning:From scalable machine learning to making a case
Interaction:Understanding language, tone, emotion and context
“A green bird sitting on top of a bowl”
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https://www.ibm.com/annualreport/2016/images/dow nloads/IBM-Annual-R eport-2016.pdf
Augmenting DECISIONS
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Assistant
Tools
Collaborator
Coach
Mediator
Emerging types of Cognitive Systems
Augment Decision Making is opening to new forms of collaboration between humans and machines
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Radiologist Oncologist
Sales Assistant Tax Advisor
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Chef Designer
Musicist Movie Director
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Opportunity for decision-making
support2025
Augmenting decisions opens new opportunities on top of traditional IT
Traditional globalIT spend
Source: IBM analysis presented to the Investor Briefings
~$2T
~$1.2T
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Top outcomes from cognitive initiatives vary by industry
Finance49% Increased market agility46% Improved customer service43% Increased customer
engagement43% Improved productivity &
efficiency42% Improved security &
compliance, reduced risk
Retail56% Personalized customer / user
experience56% Increased customer engagement56% Improved decision making &
planning 56% Reduced costs55% Improved customer service
Health66% Accelerated innovation of
new products / services66% Improved productivity & efficiency64% Improved security & compliance,
reduced risk62% Reduced costs59% Improved customer service
Manufacturing 64% Improved decision making
& planning 58% Improved productivity &
efficiency54% Improved security &
compliance, reduced risk52% Improved customer service49% Enhanced the learning
experience
Government/Education54% Personalized customer / user
experience50% Improved customer service37% Improved decision making &
planning 36% Improved productivity & efficiency33% Increased customer engagement
Professional Services40% Reduced costs36% Personalized customer/user
experience36% Improved customer service36% Expanded ecosystem34% Accelerated innovation of new
products / services
% achieving outcome with cognitive
Source: An IBM study of over 600 early cognitive adopters - 2016 Full report: http://www.ibm.com/cognitive/advantage-reports/
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IBM Watson is the most advanced Artificial Intelligence & Machine Learning platform to support Decision Making in Business
Toward a Precise Decision Making to reduce the wasteful spend as well as the risk in every industry
Watson:Cognitive System
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IBM Cognitive Computing
45Nazioni
100+Applicationsgià nel mercato
6.000Ricercatori e Specialisti in IBM
8Lingue
200Universitàorganizzano corsi su Watson
500+PartnersChe integrano Watson
API & HybridCognitive Frameworks
20Industrie
80.000Sviluppatoricostruiscono applicazionicon Watson
Watson Health5.000 Dipendenti, 6B$ di investimento
Watson InternetOf Things1000 Dipendenti, 3B$ di investimento
Watson FinantialServices
3 Unità di BusinessVerticali
200MCittadini
60MPazienti
30BImmagini
1.2MAbstractMedici
60+Soluzioni
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Who: Current top players (prevalent) competitive directions and approaches
Personalized Service /Content Aggregation
Industry-oriented / Professions SpecificOutcomes via cognitive Solutions
Core Business Cognitive /Enhance Experiences
IBM (Health,Finance, …)
API SERVICES /PLATFORM
AWS
Microsoft
Goggle
Amazon (Alexa)Facebook
IBM BlueMix
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Keyword Extraction, Entity Extraction, Sentiment Analysis, Concept Tagging,
Conversation Intents Entities Dialogues
Personality Big5 Personality Traits Needs Values
Language Tone Emotion Social propensities Language styles
Translate Conversational News Custom TranslationPatents
Language DeepUnderstanding
Relation Extraction, Taxonomy Classification, Author Extraction….. Custom Analysis
Speech-to-text
Custom pronunciations Voice TransformationExpressive Voice
Voice synthesis
Keyword Spotting Telephony Broadband
Vision Face Recognition Image Similarity Image ClassificationCustom eyes
Source: https://www.ibm.com/watson/developercloud/services-catalog.htmlWATSON
Kind of skills
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39https://www.technologyreview.com/s/603895/customer-service-chatbots-are-about-to-become-frighteningly-realistic/
The movements of Soul Machines’s digital faces are produced by simulating the anatomy and mechanics of muscles and other tissues of the human face.
Soul Machines
The avatars can read the facial expressions of a person talking to them, using a device’s front-facing camera
Soul Machinesmade NADIA, a chatbot for the Australiangovernment to help people getinformation aboutdisabilityservices.
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Conversation
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I am going to New York next May
Man
Walking, go around
vest
Where and When will you be using this jacket?
I'll find a jacket that fits those conditions. Are you looking for a men's or women's jacket?
Okay, I got it. What will you use this jacket for?
What styles are you looking for?
Conversation
https://www.thenorthface.com/xps
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I am going to New York next May
Where and When will
you be using this jacket?
I'll find a jacket that fits those
conditions. Are you looking for a
men's or women's jacket?
https://www.thenorthface.com/xps
Man
Okay, I got it. What will you
use this jacket for?
Walking, go around
What styles are you
looking for?
vest
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It will be more and more a bots vs bots marketing battle!
Our personal BOTS will buy for us, #Brands should convince them NOT us!
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© 2017 International Business Machines Corporation
Watson OncologyA collaboration between IBM and Memorial Sloan Kettering (MSK). Watson for Oncology utilizes MSK curated literature and rationales, as well as over 290 medical journals, over 200 textbooks, and 12 million pages of text to support decisions.
• Analyzes the patient's medical record• Identifies potential evidence-backed treatment options• Finds and provides supporting evidence from a wide variety of sources
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The Medical Sieve § Build a fast anomaly detection engine
–Quickly filters irrelevant images–Highlights disease-depicting regions–Flags coincidental diagnosis
§ Intended as a radiology assistant –Clinicians still do the diagnosis–Machine reduces workload –Machine performs triage/decision support
Given history of the patient and images of a study
Is there an anomalous image here?If so, where is the anomaly ?Describe the anomaly
The Medical Sieve
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© 2017 International Business Machines Corporation
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Weather is the secret to understanding how consumers feel… and cook
A brand able to gain a spot in the daily routines and rituals of consumers creates a not only a relation but a deep intimacy with them
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https://watsonads.com
Watson Ads
16
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CREATIVECOMPUTING
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MARCHESAA dress that think
JASONGRECH Fashion zeitgeist
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Creations from the Cognitive Collection – Designed by JASONGRECH and IBM Watson
Source: https://www.ibm.com/blogs/think/2016/08/cognitive-fashion/
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Source: https://www.ibm.com/blogs/think/2016/08/cognitive-movie-trailer/
1) A visual analysis2) An audio analysis3) An analysis of each scene’s composition
IBM Research Takes Watson to Hollywood with the First “Cognitive Movie Trailer”
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Watson / Presentation Title / Date56
WatsonPlatform
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57 IBM Cognitive Cloud | Electrolux Digital Summit 2017
Cloud InfrastructureA highly scalable, security enabled infrastructure
DataTools to prepare data for cognitive
AICognitive building blocks for developers
Applications, solutions and servicesTargeted solutions for enterprise businesses
IBM delivers an architecture engineered for disruption
Cognitive Systems leverage machine learning to predict meaning in features of human language (spoken, written, visual) and related forms of human reasoning
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58 IBM Cognitive Cloud | Electrolux Digital Summit 2017
Cloud InfrastructureA highly scalable, security enabled infrastructure
DataTools to prepare data for cognitive
AICognitive building blocks for developers
Applications, solutions and servicesTargeted solutions for enterprise businesses
Ingestion
ConversationA
PI
Storage Analytics Deployment Governance
WatsonHealth
Solutions
WatsonCyber
SecurityWeather
IBM Services & Ind.
Solutions
WatsonVirtual Agent
Watson Explore
and Discover
IBM Risk and
Compliance
Asset Mgmt.
(Maximo)
Visual RecognitionA
PI
Discovery
AP
I
Speech
AP
I
Compare and ComplyA
PI
Document ConversionA
PI
DLaaS
AP
I
Nat Language UnderstandingA
PI Nat Language
ClassifierAP
I
ToneAnalyzerA
PI Personal
InsightAP
I
KnowledgeQueryA
PI
IBM delivers an architecture engineered for disruption
Cloud Integration
Networking SecurityCore
Enterprise Infrastructure
CognitiveSystems
Virtual Servers File StorageObject
Storage
Cognitive Micro-services DevOps Tooling
ISV Solutions Client Solutions
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59 IBM Cognitive Cloud | Electrolux Digital Summit 2017
Data analyticsServe modelTrain model
Cognitive technologies transform data into augmented intelligence that drives differentiated experiences and outcomes
Cognitive micro-services driven tooling
CurateTraining data
ConversationAPI
ToneAnalyzerAP
I
Document ConversionAP
I
DiscoveryAPI
PersonalInsightAP
I
Nat Language UnderstandingAP
I
Compare & ComplyAP
I
Visual RecognitionAPI
Nat Language ClassifierAP
I
DLaaSAPI
SpeechAPI
KnowledgeQueryAP
I
AI
https://developer.ibm.com/academic/ https://www.ibm.com/developerworks/
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60 IBM Cognitive Cloud | Electrolux Digital Summit 2017
IBM Academic Initiativehttps://developer.ibm.com/academic/
References
Bluemixhttps://www.ibm.com/cloud-computing/bluemix/
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61
CLOSING
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Chief ArtificialIntelligence Officer
Chief Data Scientist
Chief InformationOfficer
Chief DataOfficer
DATA INFORMATION KNOWLEDGE WISDOM
“A number” “A STREET number”
“A map of a City”
“A GPS root recommendationto go from A to B”
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https://www.theguardian.com/technology/2016/sep/08/artificial-intelligence-beauty-contest-doesnt-like-black-people
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https://www.partnershiponai.org/
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Thank youfor your attention.
Pietro Leo Executive Architect & CTO
Chief scientist, and research strategist IBM ItalyIBM Academy of Technology Leadership Team pieroleo.com