Artificial intelligence (AI) is not new. It emerged as a computer science discipline in the 50’s and has been a persistent theme in science fiction. What is new is that enterprises now have the prerequisites needed to create pragmatic AI applications: plenty of data, deep learning frameworks, and blazing fast distributed compute clusters à la Apache Spark. Forrester Vice President and Principal Analyst, Mike Gualtieri will enumerate and demystify nine essential AI technology building blocks that enterprises can use to add a modicum of intelligence to existing and new applications.

1. Artificial Intelligence: How Enterprises
Can Crush It With Apache Spark
Mike Gualtieri, VP & Principal Analyst
February 9, 2017
Twitter: @mgualtieri

2. #Priority

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52%
53%
53%
54%
58%
64%
64%
65%
66%
73%
75%
0% 10% 20% 30% 40% 50% 60% 70% 80%
Better leverage big data and analytics in business decision-making
Create a comprehensive strategy for addressing digital technologies like mobile,
social & smart products
Create a comprehensive digital marketing strategy
Better comply with regulations and requirements
Improve differentiation in the market
Increase influence and brand reach in the market
Address rising customer expectations
Improve our ability to innovate
Reduce costs
Improve our products /services
Improve the experience of our customers
Customer experience and product innovation
are top priorities.
› Base: 3,005 global data and analytics decision-makers
› Source: Global Business Technographics Data And Analytics Online Survey

4. For you For all For segments For you
Demographic
Relationships
Hyper-Personal,
Digital
Relationships
Personal
Relationships
Mass
Relationships
CustomerExperience
1800 1900 1950 2000 2015

5. #Friends

6. Customers want and increasingly expect you
to know them as well as friends know them.

7. • Learn individual customer
characteristics and
behaviors
• Predict customer needs
and desires in real-time
• Adapt applications to serve
individual customers
Hyper-personal customer
experiences must:

8. ~150

9. NUMBER
DUNBAR’SThe cognitive limit to the number of
people with whom one can maintain
stable social relationships (friends).

10. “We can only ever
have 150 friends at
most.”
Robin Dunbar
- University of Oxford, Head of the
Social and Evolutionary
Neuroscience Research

11. • Our relationships form a
hierarchically inclusive series
of circles of increasing size but
decreasing intensity.
• 150 is the limit on
personalized, reciprocated
relationships.
• 1,500 = limit on memory for
faces.
5
15
50
150
Dunbar
500
1500 Who are the 5 people
you care about the
most?

12. #Customers

13. 25 million investors
How many customers does your organization
have?
6 million active customers
390 million visitors/month
1.8 vehicles per year
320 million citizens

14. #Quiz

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How well do you know this consumer?
› Male
› 35 years old
› Single
› Resides in New York
City
› Makes $100,000 per
year
What do you predict he would do
if the bank accidently transferred
$5,000 into his bank account?
A. Give the money back
B. Take the money and run
Spark Summit Quiz

16. George Costanza

17. #AI

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Enterprises that plan to invest in AI expect customer
experience and business model benefits

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Artificial intelligence (AI) interest is high; adoption is
nascent
Opportunity

20. AI is now on the syllabus at top-tier business schools
such as Harvard, Insead, MIT, Northwestern, Stanford

22. #PureAI

23. The purest benchmark for AI is technology
that strives to mimic human intelligence…

24. “ . . . within a
generation, the
problem of creating
‘artificial intelligence’
will substantially be
solved.” (1967)
Marvin Minsky (1927-2016)
Co-founder of MIT’s AI Laboratory in
1959

25. #PragmaticAI

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Enterprises can use AI building blocks today to
add a modicum of intelligence to apps
Pragmatic AI
Nope!
Yep!

27. #BuildingBlocks

28. Pragmatic 1 Pragmatic 2 Pragmatic 3Research
Use one or more of these AI building block technologies
to build a modicum of intelligence in your apps.
Pure
?
None yet
Good Enough Pretty Good Creepy Good

29. #ML

30. Machine learning is used by data scientists
to train probabilistic predictive models.

31. A recommendation engine is a finely tuned
prediction about what you might enjoy watching.

32. Leading financial services firm uses machine
learning to predict clients’ portfolio actions.

33. InteractiveTel AI listens in real-time to 200,000 minutes
of car buyer conversation per month at a large
dealership.

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Machine learning augments programmed logic
with learned logic to create AI apps
Streaming data
Application
interface
App logic
Appli-
cations
Context
Actions
Real-time
context
Programmed
logic
Learned logicMachine learning Learning
External
actions
External
context
From other data
sources of
applications
To other data
sources or
applications

35. #GoDeep

36. Deep learning requires “stupidly powerful”
compute processing for more accurate models.

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Deep learning open source libraries are
available now
›Caffé
›Deeplearningforj
›MxNet
›OpenAI
›Theano
›Tensorflow
›Torch

42. Property insurers can use DL to automatically
assess damage and repair costs.

43. #

44. #Models

46. 10 characteristics + 10 behaviors + 10 needs =
30 AI models per customer
1 million customers x 30 models =
30 million AI models
AI Models

47. #Data

48. All data originates in real-time…

49. 110010011011001
010010011011001
010011001101101
010010011011001
CustomerData
Transactions
Everything
IoT
…but, traditional analytics to gain insights and
build models is usually done much, much later.

50. Millions of AI models…
…updated continuously
with real-time data!

51. Great data pipelines are a pre-requisite to
pragmatic AI.

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Enterprises can use AI building blocks today to
add a modicum of intelligence to apps
Pragmatic AI
Nope!
Yep!
Prerequisite

53. #

54. Spark is designed for speed.

55. Spark is designed to scale.

56. Spark is designed for
distributed machine learning.

57. Spark does deep learning.

58. Spark has a vibrant ecosystem.

59. #Pragmatic

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Pragmatic use cases can work today.
Pragmatic AI
Nope!
Yep!
Prerequisite
Make it
converse
Make it
predict
Make it
see
Make it
discover
Make it
move

61. #DoYourJob

62. Do your job…

63. Do your job…with Apache Spark!

64. forrester.com
Thank you
Mike Gualtieri
mgualtieri@forrester.com
Twitter: @mgualtieri