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What does A.I. look like in
‘real world’ business?
CUTTING THROUGH
THE HYPE
WORKSHOP GOALS
● How to wrap your head around this A.I. thing
○ Put A.I. into a clear context, so you can more easily apply it
● Where we are today
○ What’s real
● A view into into paths A.I. could follow
○ So you can better predict where it may be headed
● Starting points with quick R.O.I.
○ A.I-powered ‘chatbot’
○ A.I-powered support
○ A.I-powered personalization
INTRODUCTIONS
STARTUPS & ENTERPRISE
chris.mohritz@10xeffect.com
● Lead a startup accelerator for web/mobile
● Also run corporate innovation events & consulting
● Using A.I. (machine learning) in business since 2009
A
B
O
U
T
Philosopher
MY PERSPECTIVE
Sherpa
vs.
Learn & lead by doing. Learn & lead from theory.
A
B
O
U
T
1. Are you looking for your first step or next step?
2. What is that 1 thing that would make today a
total success for you?
3. And would you consider yourself to be to be an A.I

Skeptic? Watcher? Explorer? Rising star? Visionary?
3 QUICK QUESTIONS...
HOUSEKEEPING
A FEW DETAILS
● WiFi connection is...
● Bathrooms are

● Refreshments are...
● Everyone order lunch?
All 5 presentations are intended as ongoing resources.
Tons of information.
Tons of links.
You have full access to all slides

bit.ly/SiliconHillsAI
ENJOY THE RIDE
I’m here to answer your questions.
And the slides are designed to provoke more
questions.
So don’t hesitate to dive in with a
thought, question or comment.
CHIME IN ANYTIME
We all come in here with different expectations,
different goals, and different preconceptions about A.I.
But if I do my job right, we’ll all leave with a clear view on
where A.I. translates into real world business value.
DIFFERENT STARTING POINTS
COMING UP...
Laying the foundation
● Cutting Through the Hype
2 A.I. Technologies that will have the greatest impact
● Computer Speech
● Computer Vision
2 A.I. Applications with the quickest R.O.I.
● Predictive Engagement
● Predictive Personalization
A
G
EN
D
A
We’re entering an era where we will no longer be
thinking about technology

We will be thinking with it.
So let’s unpack what that looks like...
WELCOME TO THE GOLDEN AGE OF
A.I.
● It’s here to stay
● It’s coming faster than you think
● It’s just software trying to act smart
● It’s changing everything...literally
● It loves to make you look good
● It’s easier to use than you think
ARTIFICIAL INTELLIGENCE
O
U
R
JO
U
R
N
EY
IT’S HERE TO STAY
Business loves it

● Boosts revenue
● Reduces costs
Technology caught up

● More data — “Life begins at a billion examples.”
● More computing — go cloud!
WHY NOW?
“...by 2020 almost all respondents believe A.I.
can generate a significant R.O.I. impact
through both an expected 39% boost to
revenues on average and an anticipated 37%
reduction in costs.”
~ Infosys
1,600 IT and business decision-makers were interviewed in November 2016. All came
from organizations of more than 1,000 employees, with $500M or more annual revenue
and from a range of sectors.
That’s 76% to the bottom line!
But what caused the change in attitude for business?
A.I. ACCELERATES BUSINESS
As it was famously said back in 2011

Software is Eating the World.
Because software automates, simplifies, and
accelerates business.
And now...A.I. is eating the software.
Because A.I. automates, simplifies, and
accelerates software.
And we have a lot of software these days!
● Hiring the right people
● Augmenting finance
● Measuring brand exposure
● V.I.P. identification
● Drone/satellite asset mgmt
● Retail shelf analysis
● IP infringement monitoring
● Visual search
● Chatbots
EXAMPLES OF A.I. IN USE TODAY
● Personalizing customer service
● Improving customer loyalty
● Boosting customer retention
● Detecting fraud
● Predictive maintenance
● Smoother supply changes
● Career planning
● Route optimization
● Reduce power consumption
R
ESO
U
R
C
ES
Business loves A.I.
● A.I. removes friction, allowing greater productivity
● Greater productivity translates into a faster
growing business
● Faster growing business translates into further
investments to expand A.I.
IT’S HERE TO STAY
R
EC
A
P
IT’S COMING FASTER
THAN YOU THINK
● We are hardwired to expect things to happen in a
linear fashion
● Yet, digital technologies are evolving at computing
speeds — exponentially
Which is why things that evolve at an exponential rate
tend to ‘catch us off guard.’
OUR PERCEPTION IS DECEPTIVE
Our world is messy...really messy.
Which — historically — has confused computers.
But now they are quickly figuring out our physical world.
This is allowing computers to interact and deeply
integrate into our daily work and lives...opening up all
kinds of wonderful opportunities.
FIGURING OUT OUR MESS
Speech — computers can now recognize and speak
natural language.
Vision — computers can now recognize and create
visual information.
WHAT ALLOWS THEM TO DO
THAT?
We’ll dive into these 2 in more detail.
Linear thinking
Our minds don’t register exponential
change...so things that move quicker
than linear are ‘hard to believe.’
In addition, computers have figured out
our messy physical world, which opens
the door for it to quickly move in.
IT’S FASTER THAN YOU THINK
Exponential
change
R
EC
A
P
It will never
‘feel’ right.
100 million times faster...?
“I would predict that in 10 years there’s nothing but
quantum machine learning”
~Hartman Nevet
Head of Google’s Quantum AI Lab
via: technologyreview.com
AND IT’S ONLY GETTING FASTER
Hint: Now is the time to act.
AN INTERESTING TIPPING POINT...
2011: Machine tries to beat humans. 2017: Humans try to beat machine.6yrs later ⇹
The Echo is already
mainstream enough
for SNL.
‘Mockery is the
sincerest form of
flattery.’
AND ANOTHER...
youtube.com/watch?v=YvT_gqs5ETk
IT’S JUST SOFTWARE TRYING TO
ACT SMART
Automation
Software
Artificial Intelligence
Machine Learning
Neural Networks
Deep Learning
PUTTING BUZZ WORDS INTO
CONTEXT
Artificial intelligence is a subjective
result created by “smart” software
Machine learning is a form of software
development that creates “smart” software
Neural networks are a technique of
machine learning
Deep learning is a neural network
with more than 2-3 layers
Software is a method of
automation
CONTINUING TO AUTOMATE OUR
WORLD
In the 20th
century we automated work,
In the 21st
century we are automating intelligence.
The traditional way...
DEVELOPING SOFTWARE
The machine learning
way...
Model
00110011010111
01
010110011101
0
11001001101
Stored as a
mathematical model.
Trained logic through finding patterns in the data.Handwritten logic.
tripID hasEggs eggsBought milkBought
1 1 6 1
2 0 0 2
3 1 6 1
4 1 8 1
5 0 0 1
6 1 6 1
7 0 0 3Remember “Software Accelerates Business”...?
Machine Learning allows us to accelerate that software — further accelerating business.
All because machine learning can create more complex logic than handwritten code. Making it
“Smart.”
FOR EXAMPLE...
Handwritten logic
if (eval) { do_this() }
if (eval) { do_this() }
if (eval) { do_this() }
if (eval) { do_this() }
if (eval) { do_this() }
Trained logic
if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() }
if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() }
if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() }
if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() }
if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() }
if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() }
if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() }
if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() }
if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() }
if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() }
if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() }
if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() }
if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() }
if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() }
if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() }
if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() }
if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() }
How would you
program a computer
to identify dogs?
Machine learning allows us to
generate the granularity needed
(in rules) in a matter of hours.
A.I. IS A SUBJECTIVE “RESULT”
● Machine learning allows us to create software with
more complex logic
● This “smarter” software can produce results that
mimic human intelligence
But we don’t really understand what human
intelligence is...so what delineates tasks that require
intelligence from tasks that don’t?
Artificial flowers have the same
relationship to natural flowers
as
artificial intelligence has to
natural intelligence.
Useful, but not the same.
AND LET’S BE
CLEAR...
Movies are just entertainment.
AND OF COURSE...
Photo: imdb.com/title/tt1340138
CODE TRYING TO BE CLEVER
A.I. is the result of “smart” software developed through
machine learning.
And since we don’t fully understand our only point of
reference — natural (human) intelligence — all we can
do is subjectively mimic intelligence.
R
EC
A
P
IT’S CHANGING
EVERYTHING...LITERALLY
A.I. removes friction.
It’s software that can interact and adapt — on the fly.
And by removing friction, A.I. gives us:
● Quicker adoption,
● Greater accuracy, and
● Faster speed
Which ultimately translates into more productivity.
AT THE VERY CORE...
AND IT’S ALL UP FOR GRABS
Everything mankind has ever invented — including all
software apps — will be reinvented using A.I.
A.I. will make everything frictionless
and more productive.
And it will do it completely behind-the-scenes...
ON A PATH TO UBIQUITY
“The most profound technologies are those that
disappear. They weave themselves into the fabric of
everyday life until they are indistinguishable from it.”
~Mark Weiser
Scientific American, 1991
CHANGING EVERYTHING
Can you think of anything that doesn’t have a
software element to it today?
Everything that is software today — or will be in the
future — will get the “A.I.-powered” treatment.
Remember, Software is Eating the World
?
And today, A.I. is eating the software.
R
EC
A
P
IT LOVES TO MAKE YOU
LOOK GOOD
Before ~2000 A.I. research was primarily driven by
academia and focused on creating General A.I.
Today, research is driven by business, which is
focused on Narrow A.I.
General A.I. Narrow A.I.
‘Academia’ focus ‘Business’ focus
THE A.I. REBOOT
EMPOWERING OUR WORLD
A.I. is the bridge between our world
and the computer world.
A bridge that understands how both sides work
— and translates between them.
And brings out the best in both.
“In 2018, half a billion users will save two hours a day as
a result of AI-powered tools.”
~ Gartner, 2017
THE GREAT AMPLIFIER
A.I. is a tool for augmentation, not replacement.
Augment your staff
A.I. can empower your staff to be (exponentially) more
productive:
● To work faster, and
● To work more accurately
Augment your customers
A.I. can make it easier for your customers to adopt, use, and
support your products.
(e.g. Alexa)
A.I. can reduce friction in nearly any business process.
But stay focused on small, precise tasks.
General A.I. Narrow A.I.
‘Replace’ mindset ‘Augment’ mindset
THINK BIG, BUILD SMALL
“Anything that a typical human can do
with 1 second of thought, we can probably
now or soon automate with A.I.”
~ Andrew Ng
Former lead of Google Brain project
FOCUS ON PINPOINT SOLUTIONS
THINK THIS... NOT THIS...
One model to rule
them all.
Product
Recommendations
Emotion
Recognition
Sentiment
Analysis
Text
Analytics
Job Search &
Discovery
Video
Analysis
Text to
Speech
Computer
Vision
Search
Autosuggest
Facial
Recognition
Language
Translation
Speech
to Text
Resume
Analysis
Content
Moderation
Micro A.I. Monolithic
A.I. should stand for

Augmented Intelligence.
Stay focused on small, narrow tasks that amplify
human productivity, not replace it.
MAKING YOU LOOK GOOD
R
EC
A
P
IT’S EASIER THAN YOU THINK
WHERE DO I START LOOKING?
Break down your search into bite-sized chunks.
Anything related to improving customer experience is usually a good
bet.
Marketing Support Product Admin
Innovatio
n
Following sessions will dive into the Marketing, Support and Product blocks.
Quickest R.O.I.
Suggested implementation path
GROW INTO IT
A.I. M
aturity
No training data required!
Purpose-Built Platform, Their Training Data
Commercial Platform, Their Training Data
Commercial Platform, Your Training Data
In-House Platform, Your Training Data
Most of the major cloud providers
have purpose-built A.I.-powered APIs.
Many have a free tier.
And they work exactly like
every other API you’re already using.
NOTHING NEW HERE
IN SHORT...
You don't need to know A.I. to use it.
Who uses software?
vs. Who knows how to write software?
That’s kinda the point.
A.I. is the universal bridge.
● Microsoft Azure
● DiffBot
● BigML
● Google Cloud
● AWS
● IBM Watson
● Baidu
● Salesforce
● Alibaba
● Oracle Cloud
● HP Haven
● Adobe Sensei
R
ESO
U
R
C
ESLOTS OF COMMERCIAL OPTIONS
AND OPEN SOURCE OPTIONS
● Google TensorFlow
● Microsoft CNTK
● Apache PredictionIO
● Deeplearning4j
● Caffe / Caffe2 (Facebook)
● H2O
● Apache Spark MLlib
● Apache Mahout
● OpenNN
● Oryx 2
● OpenCyc
● Amazon DSSTNE
( If you decide to go in-house. )
R
ESO
U
R
C
ES
WHY DID I CHOOSE
TENSORFLOW?
● “If it’s good enough for Google
”
● Strong commercial commitment
● High-quality ‘pre-trained’ models
● Large diverse ecosystem
● Active independent development
● Most compelling path to in-house solutions
(interchangeable with cloud?)
TENSORFLOW DEEP DIVE
● github.com/astorfi/TensorFlow-World
● github.com/jtoy/awesome-tensorflow
● github.com/TensorFlowKR/awesome_tensorflow_implementations
● github.com/gstaff/awesome-tensorflow
● github.com/kozistr/Awesome-GANs
And here’s some complementary DNN stuff...
● github.com/guillaume-chevalier/Awesome-Deep-Learning-Resourc
es
R
ESO
U
R
C
ES
● archive.ics.uci.edu/ml
● deeplearning.net/datasets
● mldata.org
● grouplens.org/datasets
● cs.toronto.edu/~kriz/cifar.html
● cs.cornell.edu/people/pabo/movie-review-data
● yann.lecun.com/exdb/mnist (handwriting)
● kdnuggets.com/datasets/index.html (long list)
● image-net.org (competition)
PLUS OPEN SOURCE DATASETS
● gallery.cortanaintelligence.com
● bigml.com/gallery/models
● predictionio.incubator.apache.org/gallery/template-gallery
● github.com/tensorflow/models
● algorithmia.com/algorithms *
AND PRE-BUILT M.L. MODELS
PLUS...ARTIFICIAL A.I.
mturk.com
AND EASY GATEWAYS
Computer
Speech
Computer
Vision
Predictive
Engagement
Predictive
Personalization
Technologies with
the greatest impact
on our future.
Applications with
the quickest R.O.I.
Just add skills

Most implementations do not require a new team,
All you need are some new skills.
BUT HOLD OFF ON NEW TEAMS
● Right technical expertise to cut through the hype
of new offerings, and
● Right business acumen to know where to best
apply those technologies.
WHAT SKILLS DO YOU REALLY
NEED?
( Sound familiar? )
A.I. fuels growth.
You could end up
hiring more people,
not laying them off.
“A.I.-POWERED” TENDS TO HIRE
geekwire.com/2017/amazon-soars-340k-employees-adding-110k-people-single-year
We’ve gone through
this transition
before.
A.I. just makes
existing stuff
“smarter.”
IT’S EASIER THAN YOU THINK
R
EC
A
P
Don't get me wrong, there's an insane amount of complexity behind the scenes.
But fortunately, you need to know that stuff to take advantage of A.I.
NEXT STEPS
HOW-TO GUIDES
● Building Voice-Enabled Products With Amazon Alexa
● Cognitive Customer Engagement Using IBM Watson
● Harnessing Visual Data Using Google Cloud
● Building a Recommendation Engine Using Microsoft Azure
● Predicting Marketing Campaign Response Using Amazon Machine Learning
● Unleashing A.I.-Powered Conversation With IBM Watson
● Get into the Mind of Your Customer Using Google’s Sentiment Analysis Tools
● Discover Your Customers’ Deepest Feelings Using Microsoft Facial Recognition
● Give Your Products the Power of Speech Using Amazon Polly
● Computers Are Opening Their Eyes — and They’re Already Better at Seeing Than We Are
● How to Predict When You’re Going to Lose a Subscriber
● The Future of Business is a Digital Spokesperson — Let’s Build a Preview Using Microsoft’s Bot
Framework
● Predicting Personality Traits from Content Using IBM Watson
R
ESO
U
R
C
ES
● A.I. is here to stay
● It’s coming faster than you think
● It’s just software trying to act smart
● It’s changing everything...literally
● It loves to make you look good
● It’s easier to use than you think
JOURNEY’S END
R
EC
A
P
We’re entering an era where we will no longer be
thinking about technology

We will be thinking with it.
Not to imply that A.I. can think

But that A.I. will expand our thinking.
CLOSING THOUGHT...
QUESTIONS OR COMMENTS?
Gigaom A.I. Team: ai@gigaom.com
Workshop Facilitator: chris.mohritz@10xeffect.com
C
O
N
TA
C
T
THANK YOU

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Artificial Intelligence: Cutting Through the Hype

  • 1. What does A.I. look like in ‘real world’ business? CUTTING THROUGH THE HYPE
  • 2. WORKSHOP GOALS ● How to wrap your head around this A.I. thing ○ Put A.I. into a clear context, so you can more easily apply it ● Where we are today ○ What’s real ● A view into into paths A.I. could follow ○ So you can better predict where it may be headed ● Starting points with quick R.O.I. ○ A.I-powered ‘chatbot’ ○ A.I-powered support ○ A.I-powered personalization
  • 4. STARTUPS & ENTERPRISE chris.mohritz@10xeffect.com ● Lead a startup accelerator for web/mobile ● Also run corporate innovation events & consulting ● Using A.I. (machine learning) in business since 2009 A B O U T
  • 5. Philosopher MY PERSPECTIVE Sherpa vs. Learn & lead by doing. Learn & lead from theory. A B O U T
  • 6. 1. Are you looking for your first step or next step? 2. What is that 1 thing that would make today a total success for you? 3. And would you consider yourself to be to be an A.I
 Skeptic? Watcher? Explorer? Rising star? Visionary? 3 QUICK QUESTIONS...
  • 8. A FEW DETAILS ● WiFi connection is... ● Bathrooms are
 ● Refreshments are... ● Everyone order lunch?
  • 9. All 5 presentations are intended as ongoing resources. Tons of information. Tons of links. You have full access to all slides
 bit.ly/SiliconHillsAI ENJOY THE RIDE
  • 10. I’m here to answer your questions. And the slides are designed to provoke more questions. So don’t hesitate to dive in with a thought, question or comment. CHIME IN ANYTIME
  • 11. We all come in here with different expectations, different goals, and different preconceptions about A.I. But if I do my job right, we’ll all leave with a clear view on where A.I. translates into real world business value. DIFFERENT STARTING POINTS
  • 12. COMING UP... Laying the foundation ● Cutting Through the Hype 2 A.I. Technologies that will have the greatest impact ● Computer Speech ● Computer Vision 2 A.I. Applications with the quickest R.O.I. ● Predictive Engagement ● Predictive Personalization A G EN D A
  • 13. We’re entering an era where we will no longer be thinking about technology
 We will be thinking with it. So let’s unpack what that looks like... WELCOME TO THE GOLDEN AGE OF A.I.
  • 14. ● It’s here to stay ● It’s coming faster than you think ● It’s just software trying to act smart ● It’s changing everything...literally ● It loves to make you look good ● It’s easier to use than you think ARTIFICIAL INTELLIGENCE O U R JO U R N EY
  • 16. Business loves it
 ● Boosts revenue ● Reduces costs Technology caught up
 ● More data — “Life begins at a billion examples.” ● More computing — go cloud! WHY NOW? “...by 2020 almost all respondents believe A.I. can generate a significant R.O.I. impact through both an expected 39% boost to revenues on average and an anticipated 37% reduction in costs.” ~ Infosys 1,600 IT and business decision-makers were interviewed in November 2016. All came from organizations of more than 1,000 employees, with $500M or more annual revenue and from a range of sectors. That’s 76% to the bottom line!
  • 17. But what caused the change in attitude for business?
  • 18. A.I. ACCELERATES BUSINESS As it was famously said back in 2011
 Software is Eating the World. Because software automates, simplifies, and accelerates business. And now...A.I. is eating the software. Because A.I. automates, simplifies, and accelerates software. And we have a lot of software these days!
  • 19. ● Hiring the right people ● Augmenting finance ● Measuring brand exposure ● V.I.P. identification ● Drone/satellite asset mgmt ● Retail shelf analysis ● IP infringement monitoring ● Visual search ● Chatbots EXAMPLES OF A.I. IN USE TODAY ● Personalizing customer service ● Improving customer loyalty ● Boosting customer retention ● Detecting fraud ● Predictive maintenance ● Smoother supply changes ● Career planning ● Route optimization ● Reduce power consumption R ESO U R C ES
  • 20. Business loves A.I. ● A.I. removes friction, allowing greater productivity ● Greater productivity translates into a faster growing business ● Faster growing business translates into further investments to expand A.I. IT’S HERE TO STAY R EC A P
  • 22. ● We are hardwired to expect things to happen in a linear fashion ● Yet, digital technologies are evolving at computing speeds — exponentially Which is why things that evolve at an exponential rate tend to ‘catch us off guard.’ OUR PERCEPTION IS DECEPTIVE
  • 23. Our world is messy...really messy. Which — historically — has confused computers. But now they are quickly figuring out our physical world. This is allowing computers to interact and deeply integrate into our daily work and lives...opening up all kinds of wonderful opportunities. FIGURING OUT OUR MESS
  • 24. Speech — computers can now recognize and speak natural language. Vision — computers can now recognize and create visual information. WHAT ALLOWS THEM TO DO THAT? We’ll dive into these 2 in more detail.
  • 25. Linear thinking Our minds don’t register exponential change...so things that move quicker than linear are ‘hard to believe.’ In addition, computers have figured out our messy physical world, which opens the door for it to quickly move in. IT’S FASTER THAN YOU THINK Exponential change R EC A P It will never ‘feel’ right.
  • 26. 100 million times faster...? “I would predict that in 10 years there’s nothing but quantum machine learning” ~Hartman Nevet Head of Google’s Quantum AI Lab via: technologyreview.com AND IT’S ONLY GETTING FASTER Hint: Now is the time to act.
  • 27. AN INTERESTING TIPPING POINT... 2011: Machine tries to beat humans. 2017: Humans try to beat machine.6yrs later ⇹
  • 28. The Echo is already mainstream enough for SNL. ‘Mockery is the sincerest form of flattery.’ AND ANOTHER... youtube.com/watch?v=YvT_gqs5ETk
  • 29. IT’S JUST SOFTWARE TRYING TO ACT SMART
  • 30. Automation Software Artificial Intelligence Machine Learning Neural Networks Deep Learning PUTTING BUZZ WORDS INTO CONTEXT Artificial intelligence is a subjective result created by “smart” software Machine learning is a form of software development that creates “smart” software Neural networks are a technique of machine learning Deep learning is a neural network with more than 2-3 layers Software is a method of automation
  • 31. CONTINUING TO AUTOMATE OUR WORLD In the 20th century we automated work, In the 21st century we are automating intelligence.
  • 32. The traditional way... DEVELOPING SOFTWARE The machine learning way... Model 00110011010111 01 010110011101 0 11001001101 Stored as a mathematical model. Trained logic through finding patterns in the data.Handwritten logic. tripID hasEggs eggsBought milkBought 1 1 6 1 2 0 0 2 3 1 6 1 4 1 8 1 5 0 0 1 6 1 6 1 7 0 0 3Remember “Software Accelerates Business”...? Machine Learning allows us to accelerate that software — further accelerating business. All because machine learning can create more complex logic than handwritten code. Making it “Smart.”
  • 33. FOR EXAMPLE... Handwritten logic if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } Trained logic if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } if (eval) { do_this() } How would you program a computer to identify dogs? Machine learning allows us to generate the granularity needed (in rules) in a matter of hours.
  • 34. A.I. IS A SUBJECTIVE “RESULT” ● Machine learning allows us to create software with more complex logic ● This “smarter” software can produce results that mimic human intelligence But we don’t really understand what human intelligence is...so what delineates tasks that require intelligence from tasks that don’t?
  • 35. Artificial flowers have the same relationship to natural flowers as artificial intelligence has to natural intelligence. Useful, but not the same. AND LET’S BE CLEAR...
  • 36. Movies are just entertainment. AND OF COURSE... Photo: imdb.com/title/tt1340138
  • 37. CODE TRYING TO BE CLEVER A.I. is the result of “smart” software developed through machine learning. And since we don’t fully understand our only point of reference — natural (human) intelligence — all we can do is subjectively mimic intelligence. R EC A P
  • 39. A.I. removes friction. It’s software that can interact and adapt — on the fly. And by removing friction, A.I. gives us: ● Quicker adoption, ● Greater accuracy, and ● Faster speed Which ultimately translates into more productivity. AT THE VERY CORE...
  • 40. AND IT’S ALL UP FOR GRABS Everything mankind has ever invented — including all software apps — will be reinvented using A.I. A.I. will make everything frictionless and more productive. And it will do it completely behind-the-scenes...
  • 41. ON A PATH TO UBIQUITY “The most profound technologies are those that disappear. They weave themselves into the fabric of everyday life until they are indistinguishable from it.” ~Mark Weiser Scientific American, 1991
  • 42. CHANGING EVERYTHING Can you think of anything that doesn’t have a software element to it today? Everything that is software today — or will be in the future — will get the “A.I.-powered” treatment. Remember, Software is Eating the World
? And today, A.I. is eating the software. R EC A P
  • 43. IT LOVES TO MAKE YOU LOOK GOOD
  • 44. Before ~2000 A.I. research was primarily driven by academia and focused on creating General A.I. Today, research is driven by business, which is focused on Narrow A.I. General A.I. Narrow A.I. ‘Academia’ focus ‘Business’ focus THE A.I. REBOOT
  • 45. EMPOWERING OUR WORLD A.I. is the bridge between our world and the computer world. A bridge that understands how both sides work — and translates between them. And brings out the best in both.
  • 46. “In 2018, half a billion users will save two hours a day as a result of AI-powered tools.” ~ Gartner, 2017
  • 47. THE GREAT AMPLIFIER A.I. is a tool for augmentation, not replacement. Augment your staff A.I. can empower your staff to be (exponentially) more productive: ● To work faster, and ● To work more accurately Augment your customers A.I. can make it easier for your customers to adopt, use, and support your products. (e.g. Alexa)
  • 48. A.I. can reduce friction in nearly any business process. But stay focused on small, precise tasks. General A.I. Narrow A.I. ‘Replace’ mindset ‘Augment’ mindset THINK BIG, BUILD SMALL
  • 49. “Anything that a typical human can do with 1 second of thought, we can probably now or soon automate with A.I.” ~ Andrew Ng Former lead of Google Brain project FOCUS ON PINPOINT SOLUTIONS
  • 50. THINK THIS... NOT THIS... One model to rule them all. Product Recommendations Emotion Recognition Sentiment Analysis Text Analytics Job Search & Discovery Video Analysis Text to Speech Computer Vision Search Autosuggest Facial Recognition Language Translation Speech to Text Resume Analysis Content Moderation Micro A.I. Monolithic
  • 51. A.I. should stand for
 Augmented Intelligence. Stay focused on small, narrow tasks that amplify human productivity, not replace it. MAKING YOU LOOK GOOD R EC A P
  • 53. WHERE DO I START LOOKING? Break down your search into bite-sized chunks. Anything related to improving customer experience is usually a good bet. Marketing Support Product Admin Innovatio n Following sessions will dive into the Marketing, Support and Product blocks. Quickest R.O.I. Suggested implementation path
  • 54. GROW INTO IT A.I. M aturity No training data required! Purpose-Built Platform, Their Training Data Commercial Platform, Their Training Data Commercial Platform, Your Training Data In-House Platform, Your Training Data
  • 55. Most of the major cloud providers have purpose-built A.I.-powered APIs. Many have a free tier. And they work exactly like every other API you’re already using. NOTHING NEW HERE
  • 56. IN SHORT... You don't need to know A.I. to use it. Who uses software? vs. Who knows how to write software? That’s kinda the point. A.I. is the universal bridge.
  • 57. ● Microsoft Azure ● DiffBot ● BigML ● Google Cloud ● AWS ● IBM Watson ● Baidu ● Salesforce ● Alibaba ● Oracle Cloud ● HP Haven ● Adobe Sensei R ESO U R C ESLOTS OF COMMERCIAL OPTIONS
  • 58. AND OPEN SOURCE OPTIONS ● Google TensorFlow ● Microsoft CNTK ● Apache PredictionIO ● Deeplearning4j ● Caffe / Caffe2 (Facebook) ● H2O ● Apache Spark MLlib ● Apache Mahout ● OpenNN ● Oryx 2 ● OpenCyc ● Amazon DSSTNE ( If you decide to go in-house. ) R ESO U R C ES
  • 59. WHY DID I CHOOSE TENSORFLOW? ● “If it’s good enough for Google
” ● Strong commercial commitment ● High-quality ‘pre-trained’ models ● Large diverse ecosystem ● Active independent development ● Most compelling path to in-house solutions (interchangeable with cloud?)
  • 60. TENSORFLOW DEEP DIVE ● github.com/astorfi/TensorFlow-World ● github.com/jtoy/awesome-tensorflow ● github.com/TensorFlowKR/awesome_tensorflow_implementations ● github.com/gstaff/awesome-tensorflow ● github.com/kozistr/Awesome-GANs And here’s some complementary DNN stuff... ● github.com/guillaume-chevalier/Awesome-Deep-Learning-Resourc es R ESO U R C ES
  • 61. ● archive.ics.uci.edu/ml ● deeplearning.net/datasets ● mldata.org ● grouplens.org/datasets ● cs.toronto.edu/~kriz/cifar.html ● cs.cornell.edu/people/pabo/movie-review-data ● yann.lecun.com/exdb/mnist (handwriting) ● kdnuggets.com/datasets/index.html (long list) ● image-net.org (competition) PLUS OPEN SOURCE DATASETS
  • 62. ● gallery.cortanaintelligence.com ● bigml.com/gallery/models ● predictionio.incubator.apache.org/gallery/template-gallery ● github.com/tensorflow/models ● algorithmia.com/algorithms * AND PRE-BUILT M.L. MODELS
  • 64. AND EASY GATEWAYS Computer Speech Computer Vision Predictive Engagement Predictive Personalization Technologies with the greatest impact on our future. Applications with the quickest R.O.I.
  • 65. Just add skills
 Most implementations do not require a new team, All you need are some new skills. BUT HOLD OFF ON NEW TEAMS
  • 66. ● Right technical expertise to cut through the hype of new offerings, and ● Right business acumen to know where to best apply those technologies. WHAT SKILLS DO YOU REALLY NEED? ( Sound familiar? )
  • 67. A.I. fuels growth. You could end up hiring more people, not laying them off. “A.I.-POWERED” TENDS TO HIRE geekwire.com/2017/amazon-soars-340k-employees-adding-110k-people-single-year
  • 68. We’ve gone through this transition before. A.I. just makes existing stuff “smarter.” IT’S EASIER THAN YOU THINK R EC A P Don't get me wrong, there's an insane amount of complexity behind the scenes. But fortunately, you need to know that stuff to take advantage of A.I.
  • 70. HOW-TO GUIDES ● Building Voice-Enabled Products With Amazon Alexa ● Cognitive Customer Engagement Using IBM Watson ● Harnessing Visual Data Using Google Cloud ● Building a Recommendation Engine Using Microsoft Azure ● Predicting Marketing Campaign Response Using Amazon Machine Learning ● Unleashing A.I.-Powered Conversation With IBM Watson ● Get into the Mind of Your Customer Using Google’s Sentiment Analysis Tools ● Discover Your Customers’ Deepest Feelings Using Microsoft Facial Recognition ● Give Your Products the Power of Speech Using Amazon Polly ● Computers Are Opening Their Eyes — and They’re Already Better at Seeing Than We Are ● How to Predict When You’re Going to Lose a Subscriber ● The Future of Business is a Digital Spokesperson — Let’s Build a Preview Using Microsoft’s Bot Framework ● Predicting Personality Traits from Content Using IBM Watson R ESO U R C ES
  • 71. ● A.I. is here to stay ● It’s coming faster than you think ● It’s just software trying to act smart ● It’s changing everything...literally ● It loves to make you look good ● It’s easier to use than you think JOURNEY’S END R EC A P
  • 72. We’re entering an era where we will no longer be thinking about technology
 We will be thinking with it. Not to imply that A.I. can think
 But that A.I. will expand our thinking. CLOSING THOUGHT...
  • 73. QUESTIONS OR COMMENTS? Gigaom A.I. Team: ai@gigaom.com Workshop Facilitator: chris.mohritz@10xeffect.com C O N TA C T