Driving Transformation Through Disruptive TechnologiesAI Building Blocks Speech recognition Computer...
30
ay 1 Driving Transformation Through Disruptive Technologies The Intersection of AI and IoT Brent Leland Taste of Technology 2019
Transcript of Driving Transformation Through Disruptive TechnologiesAI Building Blocks Speech recognition Computer...
ay1
Driving Transformation Through Disruptive Technologies
The Intersection of AI and IoT
Brent Leland
Taste of Technology 2019
Top 10 AI Movies3
1. 2001 Space Odyssey
2. Star Wars
3. Alien
4. Blade Runner
5. The Terminator
6. Star Trek: The Motion Picture
7. Her
8. Wall-E
9. The Matrix
10. Moon
ZDNet “15 of the Best Movies about AI Ranked”, January 2018
Artificial Intelligence – Put SimplyTechnologies that seem to emulate human thinking and action
4
Like Human
• Uses natural language
• Perceives sensory input
• Learns from experience
• Executes nonroutine tasks
More Than Human
• Quickly analyzes high volumes of data
• Detects patterns more accurately
• Works 24/7
• Doesn’t get bored (yet)
Artificial Intelligence Is All Around Us5
AI - Why Now?6
Computing Power
Algorithm Break-
throughs
Digital Data Explosion
GPUs (Graphics Processing
Units) using 1000’s of smaller,
efficient cores specifically
designed to run AI-oriented
applications. Deep Learning algorithms
using multi-layered "neural
networks" to mimic human
learning behavior.
Vast quantities of real-time data
(internal, external, structured,
unstructured) now available.
(2.2 billion gigabytes a day.)
The Rise of the Algorithm7
Simple
Y = f(x)
Complex
ProgramData + Rules Results(Algorithm)
Traditional Programing
TrainingData + Results Algorithm(Rules)
Machine Learning
i.e. traditional virus detection (.DAT files)
i.e. automatic spam filtering
AI Development Lifecycle8
Pro
du
ctio
nD
eve
lop
me
nt
Training SetModel
Training/ Building
Test Model Predictions/
Actions
Streaming Data
Deployed Model
Predictions/ Actions
Historical Data
Test Set
Feature ExtractionTrain/Test Loop
Deep Learning &
Neural Networks
Eureka Moments10
Checkers Chess Jeopardy Go Go (further)
Year 1994 1997 2011 2016 2017
Program Chinook IBM Deep Blue IBM Watson AlphaGo AlphaGo Zero
Approach 100% human programmed
Manually tuned using thousands of masters games
Trained using machine learning w/ millions of documents
Deep learning seeded with professional Go games
Breakthrough First human champion defeat
Massively parallel supercomputer
Natural Language Processing (NLP)
Supervised Deep Learning
Reinforcement Learning
With no human input, played itself millions of times to teach itself the game!
Eureka Moments11
The Hitchhiker’s Guide to the Galaxy by Douglas Adams, 1979 Google Pixel Buds with Google Translate, 2017
Predict
&
Optimize
What happened?
Why did it happen?
What will happen?
What should we do?
How make it happen?
Sense
&
AnalyzeDescriptive Analytics (1990’s)
Query/Drilldown
Standard Reports
Diagnostic Analytics (2000-2004)
Statistical Analysis
Root Cause
Predictive Analytics (2005-2010)
Predictive Modeling
Forecasting/Extrapolation
Prescriptive Analytics (2011-now)
Big Data
Optimization
Cognitive Analytics (now)
Machine Learning/Deep Learning
Augmented Decision Making
Advanced Analytics & Big Data are the Foundation of AI
Advanced
Analytics
Traditional
BI
Make it happen!Artificial Intelligence (now>soon)
Autonomous Systems
Human Machine InterfacesAutomate
&
ActAI
More About Data13
Economic
Indicators
Internal
External
UnstructuredStructured
Weather
Forecasts
CRMHR Records
Inventory
Financial
Sales
Records
WebsitesBeacons
Call logs /
transcripts
Store Staff
Publicly Available
Data SetsBirth
Rates
Social
Media
WearablesConnected
Devices
Digital Personal
Assistants
Internal
Documents
Video
Blogs
Traditional BI
Connected
Home
POS
SharePoint
Sensor
Data
Online
Forums
ERP
Demographics
Traffic
Credit History
Real Estate
Records
Census Data
Housing Starts
Emails
Internet
Simple Example - Energy Cost Reduction14
Production Data
Wholesale energy transmissions/pricing
Local energycompany data
NOAA weather forecasts
Predictive / Prescriptive Modeling
Rules & Constraints
What-If Analysis & Overrides
Optimal Production Schedule
Used machine learning with historical production data and 3rd party electric and weather datasets to predict energy
prices and adjust production schedules accordingly.
External Data
20% Cost Reduction400% ROI
Connecting AI to the Physical World15
50 Billion devices by 2020
Cisco Estimate
System of interrelated computing devices, machines, objects, animals, or people with
unique identifiers and the ability to transfer data over a network automatically.
Connecting AI to the Physical World16
Process sensor data
SENSORS
ACTUATORS
Calculate desired actions
Create actuator commands
Sense the environment
Act on the environment
Measures
Machine Vision / Ambient Light
Acceleration / Tilt
Electric / Magnetic
Leaks / Levels
Force / Load / Torque / Pressure
Position / Presence / Proximity
Motion / Velocity / Displacement
Temperature / Humidity / Moisture
Acoustic / Sound / Vibration
Radar / Lidar
Chemical / Gas
Flow / Volume
Combining AI & IoT17
Engineer Make Operate / Use Service / Support
Connected Cow
Putting it all Together18
AI Building Blocks
Speech recognition
Computer vision
Machine learning
Deep learning
Natural language processing
Classification and prediction
Sentiment analysis
Anomaly detection
AI Solutions
Chatbots / Virtual Assistants
Cognitive Decision Making
Conversational AI Platforms
Recommendation Engines
Content Generators
Smart Products
Intelligent Marketing
Robotic Process Automation
Disruptive Technologies
Internet of Things (IoT)
Augmented/Virtual Reality
3D Printing
Blockchain
Advanced Robotics
Autonomous Vehicles
Drones
5G Wireless
“Use AI and IoT along with other disruptive technologies and techniques to go beyond just changing business
processes to changing entire business models.”
Leveraging AI Capabilities – Build vs. Buy19
Pre-Trained AI Cloud Services
Voice-to-text, image recognition, language translation, sentiment analysis, emotion detection, video tagging
i.e. Google, Microsoft, IBM, Amazon, Zebra, Nuance, Infermedica
Prepackaged Apps (w/ AI Built-In)
Digital marketing, data analytics, incident management, virtual engineers, sentiment analysis, network security
i.e. IPsoft, Service Now, Cisco, RPA vendors, Salesforce.com
AI Cloud Algorithms
Cloud AI toolkits and algorithms to use your own data to create, train, and deploy self-learning models.
i.e. Azure ML, Amazon ML, Google Cloud ML, Watson ML, OpenAI
In-House AI
Build your own machine-learning / data science team, hire talent, procure tools, etc.
Skills: how to build algorithms, collect and integrate data and supervise the training of the algorithm.
Easier Harder
AI-as-a-Service (AIaaS)
Service provider experts gather/clean data, deploy and train models, deliver insights and automation via API’s
i.e. Element.ai, Metis Machine, DataScience.com
“Robust AI solutions may require utilizing various service providers from large AI cloud vendors to one of 3,500 niche AI start-ups.”
Enterprise Opportunities20
“Do you want to compete against companies that are using these technologies, or force
them to compete with you?”
AutomationOperational Efficiencies
AugmentationScalability
DisruptionMarket Growth
Machine - Human
Machine + Human
Anything Goes
21
AugmentationScalability
Augmented
reality owners
manual.
Harley Davidson used Adgorithm’s AI-driven
marketing platform to analyze digital channels
like Facebook and Google and then
automatically optimize marketing campaigns.
22
$700M Automotive Manufacturer used
RPA to automate a very cumbersome paper
based Accounts Payable process:
• 18 AP personnel, 60,000 annual invoices
• 70% decrease in cycle time
• 43% reduction in processing labor
AutomationOperational Efficiencies
Amazon’s KIVA robots bring the product
to human pickers allowing greater
warehouse density and fulfillment speed.
23
DisruptionMarket Growth
Insurance companies using
drones integrated w/ AI to
automatically process aerial
imagery, assess hail damage,
and calculate damage extent.
Blue River Technology uses
computer vision to identify weeds,
machine learning to determine
treatment, and robotics to apply a
microdose of herbicide.
Amazon Go automated grocery
store uses computer vision, deep
learning and sensor technology
so customers can grab the
products they want and just walk
out the door.
High Expectations24
MIT Sloan Management Review and BCG, September 2017
“To what extent will the adoption of AI affect your
business today versus five years from now.”
The AI Journey25
Education &
awareness
Lack of sponsorship
No resources or
budget
Some use cases
identified
Data siloed,
inaccessible
Analytics largely
historical
Exploring Experimenting Operationalizing Institutionalizing
Ad-hoc use cases
Proof-of-concepts
Internally focused
Projects functionally
siloed
Start of a data
strategy
Analytics moves to
predictive
Leveraging partners
AI strategy/roadmap
Solutions that scale
Adding external focus
Cross-functional
coordination
Data becomes a core
competency
Culture of innovation
Strategic partners
“AI First” mindset
Data becomes a
strategic asset
AI as a core
competency
AI Center-of-
Excellence (COE)
Broad employee
engagement
Commercialization
47% 30% 18% 5%
Foundational Building Blocks26
• Education
• Data Competencies
• Advanced Analytics
• Digital Transformation
• Cloud
• Innovation
• Culture
Issues / Barriers to Adoption27
• Job security concerns
• Lack of available talent
• Unclear business case
• Availability of training data
• AI transparency
• Built-in bias
• Regulatory and social barriers
• Legal implications
• Privacy considerations
• Security concerns
Where Does IT Fit In?28
• To lead or to follow?
• Educate yourself
• Start educating key stakeholders
• Continue (or start) to build out the foundational areas
• Leverage partners, but plan for knowledge transfer
• Do something; do anything
29
www.advancingaiwisconsin.com
