Beyond hype why ai v4

©2017 IBM Corporation 11 December 20171
Why Artificial Intelligence is the Real Deal
Beyond the Hype, version 2.0
Cristene Gonzalez-Wertz | Electronics Leader, IBV

Cognitive
Computing
Artificial intelligence and
signal processing with
machine learning,
reasoning, natural
language processing,
speech and vision,
human–computer
interaction, dialog and
narrative generation,
among other
technologies
Deep
Learning
A subset of machine
learning that uses
layered algorithms to
model and understand
complex structures and
relationships among
data and datasets. Often
the output of one
algorithm is used as the
input to the next
Machine
Learning
A field of AI focused on
getting machines to act
without being
programmed to do so.
Machines "learn" from
patterns they recognize
and adjust their behavior
accordingly.
AI
A field of computer
science dedicated to
the study of computer
software making
intelligent decisions,
reasoning, and problem
solving.
Artificial Intelligence as a concept is being thrown around with
multiple meanings, here’s some grounding

NLP
Sensory
Evidence Based
Expert Systems
Planning/Optimization
Robotics
The AI spectrum: spanning from detection, recommendation,
automation, prediction, prevention and scenario modeling
AI Audio
Vision
Speech
Deep
Learning
Predictive
Analytics
Machine Learning
Classification
& Clustering
Information
Extraction
Translation
Speech to
Text
Text to
Speech
Pattern Recognition
“Channel”
Modulation
Image Recognition Machine Vision
Diarization
ForecastingScheduling
Dialogue
Driven
Command-
driven
Intention
Creation
Conflict Management
Representative only:
By no means complete, the pace of
change is such that it would be hard
maintain accuracy
Complexity Detection Scenario Models
Emerging Capabilities
AI

While the speech and command driven side is getting all the
attention, it’s not the end game. Dealing with complexity is.
A few simple
API calls
Understanding an
unfathomable tax code
Decoding genes, drugs
and patient care options

How to think about AI Use Cases: Start with Users, Assets, Context.
Then examine volume and velocity
PEOPLE DATA
Owner / Driver / Tenants / Patient / Doctor
ASSET DATA
Building / Appliances / Vehicles
ENVIRONMENT DATA
Local / Regional/Global
Behaviour
Occupancy / movement / activity
Intent / Context
Residential / location / weather / region
Personal Information
Age / lifestyle / preferences
Claim History
Insurance / legal
SENSORS GATEWAYS APPLICATIONSIoT PLATFORM
Map Event Management
Buildings nearby / mains supply / routes/
accessibility
Event Pattern Analysis
Accidents / crime / health /social/sports
Movement Pattern Analysis
flow / accidents / routes / satellite / traffic
3rd Party Data
weather / financial / regulatory / lifestyle access
trend / illness
History
Incidents / maintenance / repair
Diagnostics
Alerts / monitoring
Usage Context
Weather / time of day / road / temp
Origin
Manufacturer / warranty / recall
Usage Patterns
Journeys / location / remote control

We talk about AI as if it were going to replace
humans. It’s not.
The jobs we’re giving to AI are jobs humans can’t do.
10, 50 or even 1,000 humans can’t collect, classify
and adjudicate data at the speed and scale in which
its coming at us.
CIO – Financial Services Data Provider

Multiple interpretations
Hundreds of answer sources
▪ Primary search
▪ Candidate answer
generation
Tens of thousands of evidence
sources and scores
▪ Answer scoring
▪ Evidence retrieval
▪ Deep evidence scoring
Inquiry analysis Decomposition Hypothesis generation SynthesisHypothesis and
evidence scoring
Final confidence
merging and ranking
Example Example
? !
Learned models
▪ Combine and weigh evidence
Let’s unpack this a little further and talk about going beyond
an initial algorithm and pattern recognition

It’s only going to intensify. (I am apologizing to you in advance)
https://www.gartner.com/smarterwithgartner/top-trends-in-the-gartner-hype-cycle-for-emerging-technologies-2017/

#Fail: Speech and text doesn’t always work as we planned with
technology. Continuity, negation, persistence – context!

And that challenge is not simply limited to language

We live in a global world,
yet we don’t always train our algorithms as if they do.
Among the greatest challenges we have
as data stewards is to be inclusive and diverse
to support all of the people we serve
with the technologies we deliver.
CIO – Reinsurance

Mobility
Collaboration
Analytics
IoT
AI and Cognitive
Augmented/Virtual Reality
Cloud
AI/Cognitive is not an island.
A full tech stack drives new capabilities
. .

Individually, new and emerging technologies can generate attractive
returns on investment
Return on Investment (ROI)
We now see many client examples of applying IoT and predictive analytics with cloud apps
to achieve real-time monitoring and visibility across a wide spectrum of industries and use
cases. And this innovation is paying off for adopters. In every area, the reported level of return
on investment (ROI) was substantial to significant (see Figure 4).
COO
Source: IBM Institute for Business Value analysis.
Figure 4
Level of ROI realized based on implementation of critical technologies
Internet
of Things
Collaboration
and social
Predictive
analytics
Cloud Cognitive
computing
Mobile Industry
speciﬁc
technologies
(Robotics)
34%
27%
Substantial Signiﬁcant
32%
22%
32%
19%
31%
20%
32%
18%
30%
17%
24%
20%
Source: IBM Institute for Business Value, “Who’s Leading the Cognitive Pack in Digital Operations?” Q7. What level of ROI have you realized based on your
implementation of these technologies?

AI amplifies benefits from analytics and automation
with better answers to critical questions
Analytics
Structured data
Automation
Robotics
With cognitive
Unstructured data
§ Improves productivity in defined
ranges
§ Interacts in formal means
(commands, screens)
§ Reduces human learning by
lowered interactions
With cognitive (Human-to-
machine, M2M interactions)
Natural language
Analytics
Structured data
With
cognitive
Unstructured
data
§ Addresses predefined
issues/problems
§ Provides accurate and
definitive answers
§ Handles known semantics and
taxonomy
Automation
Robotics
With
cognitive
(Human-to-
machine, M2M
interactions)
Natural language
§ Continuously understands,
assesses and redefines
productive ranges
§ Enables interactions with human
language and sensory inputs
§ Is always learning and sharing to
prevent “knowledge failure”
§ Enables detection of new or
unseen issues through patterns
§ Provides answers/alternatives
with margin of error
§ Is able to learn semantics and
taxonomy and expand upon
them

Chatbots, chatbots, everywhere. They are expected to have
80% adoption* by 2020 – estimated market value $23B**
* 80% is primarily consumer-facing
** $23B is probably a low-side estimate
…just enough UI, whether
conversational and/or widgets
…to be delighted by a
service/brand with immediate
access to a rich profile
…without the complexities of
installing a native app

Two perspectives on chatbots
We have to stop saying the
business wanting to go off on
their own is bad idea.
Clearly someone thought it
wasn’t.
What we have to ask is why?
CIO – European Automotive Manufacturer
It has to be about governance, fit for
purpose, architecture and especially
security.
There are significant risks we need to
educate the business on.
We need to be fast, fluid and effective
CIO – Large Scale Print Manufacturing Services

Audience participation: I have 15 use cases. We can only cover 5,
so you tell me what you want to hear
Improving
Organization
Knowledge Retention
Watson
Genomics and Quest
Diagnostics
NASA and
the Mars Rover:
Innovation, Testing,
Collaboration
Cognitive
Diagnosis – for
Machines
Smarter
Security
Cognitive +
Marketing=
Insight, Easily
Contactless
Commerce,
Integrated Shopping
Personalizing
Education
Precision
Agriculture
Partnering
to Deliver Great
Products
Buildings, Equipment
and Maintenance
Better
Supply Chains
Smarter Mirrors
for Retail
& Hotels
Cognitive
Team Work
New Business
Models for
Asset-Intensive
Industries

Woodside Energy
30 years worth of documents; as tall as the Statue of Liberty
Improving
Organization
Knowledge
• Addressing worker attrition and massive automation
• Maintaining business continuity under stressful conditions
• CEO drove project and commitments to be an industry leader

Watson Genomics and Quest Diagnostics
“70% of cancer patients are treated in the community”
Personalized Care
Anywhere
• Addresses the precision care issue driven by genetic mutation
• Ingests 10,000 articles and 100 new clinical trials each month
• Uses sequenced genetic data to uncover potential therapies

Mars 2020: What happens when you only have one shot to
get it right?
Product
Innovation,
Collaboration,
Testing
• 125,000 items for testing, mission analysis and inspections
• From 100+ spreadsheets to a traceable integrated environment
• 620 global members can interact without time zone challenges
• IoT for integration and data scale management
Picture courtesy of JPL

Cognitive Diagnosis: Detecting ailing machines
First time fix ↑
Spare parts costs ↓ and
smooths spare part
distribution uses targeted
algorithms
Customer sat ↑
Diagnose
Remotely,
Act Locally
• Initial model provides correct diagnosis 78% and improving
• Provides correct answer even when the tech is wrong
• Techs enjoy working with the application and have accepted it

Cognitive + Security delivers a hyper-responsive and superfast
learning system for your SOC
Increase analyst
productivity for
faster incident
investigation
• Analysts were 50% faster in analyzing information, prioritizing and
respond to threats in minutes versus hours or days.
• Averages 10,000 events per second per client and 50,000 flows per
minute per client, with larger clients seeing substantially higher volumes
Business context use cases
“an insurer we work with was concerned hackers were
performing quote requests against their online quoting
apps to change their pricing model. Using QRadar, we
can easily build a use case to detect this type of activity.”
Vincent Laurens, Sogetti Luxembourg

Changing Marketing with
Watson Customer Engagement
Insights,
segments,
interactions,
oh my!
• Insights automatically derived from your data – with the ease of adding
external data. Highly visual formats and trends
• Goal and performance management
• Customer Journey designer and cognitive advertising approaches
• Data and insight interrogation with recommendations and evidence

The Northface unveiled a cognitive shopping application you
can play with yourself so they could learn about user input
Get what you
really wanted
• A more intuitive shopping experience
• Usage, weather, personal preference details
• Scoring showing exactly why the items were selected for you

Contactless Commerce:
Your car can ask if you want fries with that
Unique
collaboration
VISA + IBM
• Visa payment technologies with Watson IoT platform
• Visa Token Services for security – unique digital identifier
• Can use any connected object – watch, ring, belt, refrigerator

Seeing through walls: IoT and Augmented Reality show
new value for builders and engineers, increased worker safety
Nascent
technologies allow
workers to see
around corners
• Visual and complex mechanical data become consumable and easy to
update and cascade
• Translates understanding to action: What/Where is it? What are the
requirements? How do I operate or repair it? What tools do I need?

Growth: In every sense of the word
A winery uses external data to cultivate success
Novel data use
and IoT + AI
increase yield
• Precision agriculture uses satellite imaging, IoT, crop, weather
environment and feeding data to create customized plans
• Reduces water by 25%, provides better treatment timing

IBM’s cognitive supply chain is digital from the ground up,
redesigned to make data consumable, combinable and scalable
Use all of your
information to
increase your
insight and
responsiveness
• Traffic lane congestion detection
• Detection of single source risks and remediations
• Brings together external data – like weather and related
disruptions, news and internal data to drive prevention or faster
resolution

Samsung goes deep and wide with ecosystem partners to create a
new AI + IoT ruggedized tablet for industrial applications
“We strategically worked to build a wider
partner ecosystem for extended
functionality …with leading industry
players, such as IBM, ECOM Instruments,
Gamber-Johnson, Ram®Mounts, iKey,
Otterbox and Koamtac.”
Suk-Jea Hahn, Executive Vice President of
Samsung Electronics’ Global Mobile B2B Team
Use Your
Ecosystems:
Build, Buy, Partner
• Includes Asset Management and Work Management
• Easier to use and more efficient for field workers, inspections
and next generation mobility

USA Cycling: What if your team had real-time performance
feedback and dashboards, at your fingertips, as you’re working?
Feedback that
prevents mistakes
• Split Second Performance
• Sensors, googles and dashboards drive team based
improvements for athletes and coaches

Panasonic Smart Mirrors: News, weather and concierge
functionality at your fingertips
Reminders, offers,
and personalized
experience
• Panasonic debuted the smarter mirror at CES 2017
• Built using Bluemix by their own developer team with IBM help
• Full suite of functionality and easy customization with client data

Kone: We’re not selling equipment, we’re selling outcomes
Monitoring and
Services that
increase uptime
• Moving 1 Billion people a day
• Sensored equipment helps identify and predict issues, minimize
downtime, and personalize the experience for users
• The newest repair person has the knowledge of veterans

Ashoek Goel of Georgia Tech tricked students for a whole
semester into thinking his chatbot was a real TA
One student unwittingly
nominated Jill Watson
as outstanding TA in the
university’s teacher survey.
Optimizing
work/work
balance
• Free up teaching assistants to answer more involved questions
• Controlled environment mitigates risks
• Digitized conversation and answers improves guidance for all
users

In closing, you expect the role of the CIO to shift dramatically over the
2 to 3 years. AI will be both a tool and an enabler toward that change
69% 68%
63% 64%
60% 60%
63% 63%
61%
66%
37% 37% 34% 34% 28% 29% 31% 33% 28% 28%
Crossfunctional,
self directed
teams
Continuous
planning and
delivery models
Design thinking Automation
technologies
Culture and tools
to promote
collective
intelligence
Cloud and
Anything as a
Service (XaaS)
solutions
Dedicated and
specific education
around agility
practices
Constant
technology
upgrades and
updates (no
dedicated cycles)
DevOps and other
formal agile
methodologies
A data driven
single view of the
customer
2020 2018Are you ready to nearly double the presence of transformative skills in your organization?
IBM 2017 Global C-Suite Study CIO.4.1: Extent IT org uses practices and methods (Today) vs 4.2 (Tomorrow) n=1952

The best of the season to you.
May you find in yourself the wonder of a child, the wisdom of an elder
and the joy of a Labrador Retriever charging off into a snow bank
Best wishes for an amazing 2018.

Please reach out
on social media:
Linked In
Twitter
Questions?

Cognitive and AI are driving new capabilities . .
Artificial Intelligence
Cognitive Computing
Machine Learning
data and patterns and reacting to algorithms – much like
our brain stem. Lowest level of cognitive capabilities
different forms of machine learning that work together in
more complex set of algorithms
upper frontal lobe of brain – human’s differentiate- reasoning –
Beyond image or signal but bringing the human factors into and
context into high levels of reasoning

Marketing Media Spend: Cognitive Bid Optimization–
improving media efficiencies by 35-42%
Buy the right paid
media at the right
time
• Weather Channel, social and first-party data
• Optimizing over $50mm in spend
• Improved customer experience through better targeted

Watson Ads – sample…just could not resist showing you this
Ads constructed
for each advertiser
and each user
• Ability to compose ads based on multiple dimensions
• Allows specific constraints to be introduced (use product x or y)
• Goes beyond the ad to create an interaction

Improved Commerce through image recognition – I want
something that “looks like this”
Faceted
navigation is not
an experience
• Ability to tie past and potential purchases together
• Self tagging with attribute recognition (M/F, v-neck, jewel collar)
• Works to build better outfits that match a client’s desired look

Meet Olli – a 3D printed easy access, self driving, smart little bus
that is highly customizable. It can go where other buses can’t
Seating for 12 + a
smart driver
• Interact with the bus in natural language (many, in fact)
• Ability to service non-traditional lines, call on demand
• Independence and convenience for aging or disabled adults

Foxconn: Factory robots that you speak to – and can
translate for you
Speak your
language –
it gets your
meaning
• No modifications – the learning model does the work
• Demonstrates precision and versatility
• Headed for self-configuration of lines to increase flexbility

Beyond hype why ai v4

Empfohlen

Empfohlen

Weitere ähnliche Inhalte

Was ist angesagt?

Was ist angesagt? (7)

Ähnlich wie Beyond hype why ai v4

Ähnlich wie Beyond hype why ai v4 (20)

Mehr von Cristene Gonzalez-Wertz

Mehr von Cristene Gonzalez-Wertz (6)

Kürzlich hochgeladen

Kürzlich hochgeladen (20)

Beyond hype why ai v4