Rita Ceresi Client Technical Architect, IBM Italia - Eventi on Demand
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Rita Ceresi Client Technical Architect, IBM Italia
Contents
Part One – What is AI? Part Five – Introducing IBM Watson
Part Two – AI and our lives Part Six – How handle AI pitfalls with
responsibility ?
Part Three – How AI Works?
Part Seven – Imagining the Future
Part Four – AI Pitfalls
2
Che cosa è l’AI??
3
AI definition Artificial Intelligence (AI) focuses on understanding core human abilities such as vision, speech, language, decision making, and other complex tasks, and designing machines and software to emulate these processes. https://searchenterpriseai.techtarget.com/definition/AI-Artificial-Intelligence
Dare una definizione di AI
5
6
AI, Machine Learning, Deep Learning
7
deep
learning
simple
machine
learning
see hear feel talk
learn write read
find discover
10
Riflettiamo su quanti dati
generiamo in un solo minuto
fra:
- Social (facebook, twittet,
instagram, youTube…)
- Download (App, music,
video, …)
- Email spedite
- Ricerche su internet
- Acquisiti sui siti
1125 gigabytes 80 million
wearable health 153 exabytes
devices will
of data per hour be available by of healthcare
2017.
is generated by a data generated by
connected car. devices in 2013.
Available
Data
Data
90% of cars will Increasing to 2,314
be connected by 2020. exabytes in 2020.
2.5 Enterprise
There
quintillion Amnesia
will be
bytes of data 28 times
generated daily
by connected more
machines. sensor-
enabled
devices 1.7 megabytes
than of data per
people second
Understood Data
generated by
by the every human
year 2020. being on the
Time planet by 2020.AI is everywhere
Industries that are experiencing
Netflix recommendations about enhancements after AI adoption
new series to watch? 70%
AI! 60%
50%
TelCo
The voice that gives you Banking & Insurance
indications when you are lost in a Oil & Gas
new city?
40%
Retail & Consumer Goods
Media & Entertainmernt
AI! 30%
Manufactoring & Hi-Tech
Travel & Transportation
Public Sector
20%
Your smartphone facial
recognition? 10%
AI! 0%
Fonte: Infosys 2018
13Part Two
1415
90% accident
10X
inspection risk
number of
times rate
inspectionsCulex
The Southern
quinquefasciatus
House Mosquito
Assembled the 1.2 billion letter genome
(faster and cheaper than ever before)
to understand its vulnerabilitiesRadiologists Overloaded with medical imaging data. Eye Fatigue. Missed Diagnoses. Radiologists are scarce.
Shape
Boundary
Technology
Attenuation
understands save
morphology.
91% accuracy
cancerous
time
determination.
money
Holy grail?
Premalignant lesions livesOil & Gas Billion Cell Reservoir calculation
USE CASES
22
ARE EVERYWHEREPart Three
23AI => interaction with environment
Accept sensorial Deal with people Modify things
inputs • Language • Process Automation
• Vision comprehension
• Robotics
• Sound • Handwriting
recognition • Production Control
• Voice • Profiling Offering
• Text summarization
• … • …..
• Dialogue
• …
Learn
24How does a cognitive system “learn”? AI WorkFlow
NEW DATA
Provision Time 80% of Data Science Time Resource Optimization Champion Challenger
INGEST CLASSIFY TRAINING INFERENCE
“Knowledge Model” “Training”
Define things that are important to recognize Teach the system to recognize these things
and handle into the correct context
25How are we approaching the
training?
Input «a cat»
26A first idea…
27It might work….
"cat"
28But not always things go as
expected…
29And things can get even worse…
Welcome to the Real World!
3132
Come cambia l’approccio nei sistemi Cognitivi
Programming
#static
#rule-based
#not-scaling
AI / Machine Learning
#dynamic
#data-driven
#can-generalizeIl significato delle reti nerurali
Addestramento di una rete Neurale: Training and Inference
“cat”
36Part Four
37Insidia 1: La precisione (AI needs plenty of data)
CatInsidia 2: AI is probabilistic Il significato della precisione del modello e della necessità di continuare il suo addestramento
Insidia 3: Il pregiudizio
AI learning can be biased
Source: www.ajlunited.orgo bir hemşire
He is a nurse. o bir doktor She is a nurse.
She is a doctor. He is a doctor.
en - tk, tk - enPart Five
431997 – IBM Deep Blue vs. Garry Kasparov
2011 : IBM Watson at Jeopardy!
IBM Watson today
• Tools for companies and
professionals that want to
build their own AI
• Applications to build
preconfigured AI-based
solutions
• Functions that integrate AI
and machine learning
UNDERSTAND REASON LEARN INTERACTExtend capabilities hidden in your data
Structured Visual Sentiment Entities Concepts
Recognition
Unstructured Language Element Document And AI-based
Translation Classification Understanding More… Applications
Collect Enrich ApplyRoles in an AI project
DATA SCIENTIST
BUSINESS OWNER
Knowledge Watson Machine Open Knowledge Watson Watson
Catalog Studio Learning Scale Studio Discovery Assistant
Audio/Video Processing Natural Language Processing
Visual Text to Speech to Natural Language Natural Language Language Tone Personal
Recognition speech text Classifier Understanding Translator Analyzer InsightsPart Six
49just because you are using an algorithm doesn’t mean it’s going to be fair and just
Supplier’ Declaration
of Conformity (SDoC)
(48,7$·
AI systems should …
use training data and models that
are free of bias, to avoid unfair
treatment of certain groups.Supplier’s Declaration
of Conformity (SDoC)
63,(*$%,/(
AI systems should …
provide decisions or suggestions
that can be understood by their
users and developers.Supplier’s Declaration
of Conformity (SDoC)
52%8672
AI systems should …
be safe and secure, not vulnerable
to tampering or compromising the
data they are trained on.Supplier’s Declaration
of Conformity (SDoC)
'RFXPHQWDWR
AI systems should …
include details of their development,
deployment, and maintenance so they
can be audited throughout their lifecycle.Part Six
55Where is AI today?
#StrongAI
#AugmentedIntelligenceHow skills should adapt to the change?
«More than 120 million workers in the world’s 12 largest economies may need to be
retrained/reskilled in the next 3 years as a result of intelligent/AI-enabled
automation»
https://newsroom.ibm.com/2019-09-06-IBM-Study-The-Skills-Gap-is-Not-a-Myth-But-Can-Be-Addressed-with-Real-Solutions
«Millennials, especially those with both business and IT skills, are increasingly in high
demand, for leadership, analytics, coding, and managing projects to scale, yet
universities are not turning out enough candidates to meet the needs»
https://www.pewresearch.org/internet/2017/05/03/the-future-of-jobs-and-jobs-training/
Skilled humans fuel the global economy: however, skills availability and quality are in
jeopardy nowadays
https://www.ibm.com/downloads/cas/EPYMNBJAWhat skills are the most critical?
New skills vs changing of organization culture • AI has introduced the need for a new business model, new ways of working, and a flexible culture that foster the development of critical new skills • In this context traditional «core» skills remain vital; however, executives tell us soft «behavioral» skills have surpassed them in importance • Early formative experiences help people adapt to change skills and adopt new styles of working later in life. This adaption can also be learned and reinforced through ways of working that embrace change as the norm.
Managing the skill gap Make it personal
• Understanding the current skills of each and every
person
• Personalize learning and career path
• Go beyond the segmentation model of «job roles»
Turn up the transparency
• Aim for deep visibility into the skills position across
the enterprise
• Leverage AI-base analytics to obtain insights over
the «skill map»
Look inside and out
• Embrace open architectures and hybrid models
• Engage agile teams with heterogeneous skillsets
• Promote the creation of partners’ecosystemsReferences A beginner's guide to artificial intelligence https://www.ibm.com/developerworks/library/cc-beginner-guide-machine-learning-ai-cognitive/index.html The business of artificial intelligence https://hbr.org/cover-story/2017/07/the-business-of-artificial-intelligence IBM Watson home https://www.ibm.com/watson Algorithmic Justice League https://www.ajlunited.org/ Monitor WML Model with Watson OpenScale https://www.ibm.com/cloud/blog/tutorial-monitor-your-deployed-wml-model-with-watson-openscale The enterprise guide to closing the skills gap https://www.ibm.com/thought-leadership/institute-business-value/report/closing-skills-gap
Thank you!
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