"Empower Developers with HPE Machine Learning and Augmented Intelligence", Dr. Abdourahmane Faye, Big Data SME Lead DACH at HPE Watch more from Data Natives Berlin 2016 here: http://bit.ly/2fE1sEo Visit the conference website to learn more: www.datanatives.io Follow Data Natives: https://www.facebook.com/DataNatives https://twitter.com/DataNativesConf Stay Connected to Data Natives by Email: Subscribe to our newsletter to get the news first about Data Natives 2017: http://bit.ly/1WMJAqS About the Author: Abdou Faye is Subject Matter Expert in Big Data, Predictive Analytics / Machine Learning and Business Intelligence, with more than 19 years of experience in that area in various leading and executive roles, both from a Technical, Architecture and Sales perspectives. He recently joins HPE coming from SAP, where he was leading the Predictive Analysis & Big Data CoE (Center Of Excellence) business since 2010 for DACH, CEE and CIS region, in charge of Business Development and Sales Support. Prior to SAP, he worked 4 Years at Microsoft as Senior BI & SQL-Server Consultant in Switzerland, after 10 years spent at Philip Morris (CH), Orange Telco (CH) and SEMA Group (FR). Abdou graduated from Paris 11 University in 2000, where he completed a PhD on Data Mining/Predictive Analytics, after completing a Master in Computer Science.

1. Empower developers with HPE Machine
Learning and Augmented Intelligence
HPE Big Data – Cognitive Analytics
Platform for Text and Rich Media
Dr Abdourahmane FAYE – Big Data SME Lead for DACH Region

2. HavenOnDemand.com
@HavenOnDemand
A (very brief) history of AI

3. Great Expectations...
Asimov’s Three Laws of Robotics:
1. A robot may not injure a human being or,
through inaction, allow a human being to come
to harm.
2. A robot must obey the orders given it by human
beings except where such orders would conflict
with the First Law.
3. A robot must protect its own existence as long
as such protection does not conflict with the First
or Second Laws.
3

4. Next attempt: neural networks
Attempt to imitate human learning
– Much closer match to human intelligence, contrasted well against rigid logic-based approaches
– Captures our fuzziness, ability to fail gracefully (i.e. guess)
– Very effective but unfortunately still only applicable to specific applications like speech
recognition, image recognition.
4

5. Which brings us to today
Smart machines, but very specific domains
– Very often better than humans, but only in the
specific tasks for which they were built
– However, they lack general intelligence, eg.
- Learn abstract concepts
- Think cleverly about strategy
- Compose flexible plans
- Make a wide range of ingenious logical deductions
- …
– Immense social change needed for human
acceptance of AI and delegating control
5

6. Machine Learning at the Service of Business
Augmented Intelligence

7. Open Innovation is transforming everything
Closed technology
architecture design
“After-the fact” static analytics,
e.g. Monthly reporting
Analyze data at
“rest”
Real-time insight &
understanding via machine
learning
Put data science into your
processes – Next-gen apps
and services
Analyze and apply perishable
data
anywhere at any time
Premise-based
systems
Seamless blending of open
source, advanced technology,
deployment choices…
Contain Cost Create Outcomes
Traditional Data Analytics Open Innovation Data Analytics
Journey to the New Style of Business

8. How do you bridge the gap between data and outcomes?
8
How do you consume
any data generated
or understood by
humans?
How do you identify
key aspects and
patterns to determine
outcomes?
How do you
automate to take
action?
Data sources Diverse Modern
Apps
Q1 Q2 Q3

9. Augmented Intelligence
power apps for competitive advantage
9
Augmented Intelligence
powered by HPE
Artificial intelligence, machine learning and natural
language processing using advanced analytics functions.

10. Human data
Connected people, apps and things generating massive data in many forms
Machine data
Business data
faster growth
than
traditional
business data
10x

11. HavenOnDemand.com
@HavenOnDemand
What’s so difficult about
human information?

12. Human Information is made up of ideas, is diverse and has context
Why is processing human data different?
– Ideas don’t exactly match like data does; they have distance.
– Human Information is not static – it’s dynamic and lives everywhere.
– Legacy techniques have all fallen short.
Social Media Video Audio Email Texts Mobile
Transactional Data IT/OTDocuments Search Engine Images

13. Strong information and weak information
Key Words are small amounts of very strong information without contextLarger amounts of weaker information is what humans refer to as “context”
“Mercury”
Is it a planet?Is it an element?Is it a car?With high certainty; it’s an element!
“A heavy element and the only metal that is liquid at standard conditions for
temperature and pressure with the symbol Hg and atomic number 80,
commonly known as quicksilver”

14. Using Cognitive Analysis to form a human-like understanding of content
HPE Natural Language Processing (NLP) engine
Fundamentally created to understand natural
human language using probabilistic modeling
and NLP algorithms
• Allows incoming data to dictate the model,
not pre-defined rules, dictionaries, or semantic webs
Self-Learning / Machine Learning
• Updates as more data is added or removed
• Adapts to changing definitions or meaning
Fundamentally language-independent
• Treats words as symbols
Optimized with language packs
• Eduction, sentiment analysis, speech analytics
Information Theory and
Bayesian Inference

15. HavenOnDemand.com
@HavenOnDemand
But we are all fine with
structured data, right?

16. Unfortunately, most existing structured data solutions are full
of compromise
Traditional Enterprise Databases
–The original SQL databases did not envision today’s
data volumes
–Vendors scrambling to handle bigger data volumes
by tacking on Hadoop technologies and retrofitting
legacy technologies
–Either use reduced data sets or eye-watering costs
Hadoop-Based Solutions
–Major Hadoop vendors strive to meet the standard
with SQL on Hadoop
–NoSQL is incomplete SQL
–Analytics Performance is very limited
–Not a substitute for a full implementation of SQL
Manage
Huge Data
Volumes
Deliver
Fast
Analytics
Compromise

17. HPE Augmented Intelligence Real-Time Analytics
Native High
Availability
Standard SQL
Interface
Column
Orientation
Auto
Database
Design
Advanced
Compression
MPP Massive
Parallel
Processing
Leverages BI, ETL,
Hadoop/MapReduce and
OLTP investments
No disk I/O bottleneck
simultaneously load &
query
Native DB-aware
clustering on low-cost
x86 Linux nodes
Built-in redundancy that
also speeds up queries
Automatic setup,
optimization, and DB
management
Up to 90% space
reduction using 10+
algorithms
 50x – 1000x faster
than traditional
RDBMS
 Scales from TB to PB
with industry-
standard hardware
 Simple integration
with existing ETL and
BI solutions
 SQL-99+ compliant
 Ultimate deployment
flexibility
 Extended advanced
analytics
 24/7 Load & Query
17

18. - Machine Learning algorithms, such as k-means and
regression, built into the core HPE engine
- Advanced predictive modeling runs within the
database eliminating all data duplication
typically required of alternative vendor offerings
- Traditional approaches can’t handle many data
points forcing data scientists to “down-sample”
leading to less accurate predictions
- A single system for SQL analytics and Machine
Learning
18
Node 1 Node 2…. Node n
Machine learning functions run in
parallel across hundreds of nodes in a
cluster
Machine Learning integrated into the core of the HPE
Augmented Intelligence Platform

19. HavenOnDemand.com
@HavenOnDemand
HPE Haven OnDemand is a self-
service cloud platform that
provides augmented intelligence
through cognitive analytics,
machine learning APIs and
services.

20. Over 70 APIs
Connect, extract, index, search and analyze

21. Real life challenges
21
eDiscovery
Fileshare
analysis
Call data
Broadcast
monitoring
Website
search

22. HPE Haven OnDemand Combination APIs
Reusable Machine Learning building blocks for cognitive apps and services
Machine Learning API Mashups
Democratizing Machine Learning to accelerate development of cognitive apps and services for all devices and
platforms. Reimagine your business.

23. HPE Haven OnDemand Combinations Marketplace for cognitive services
Accelerate development with copy and paste Machine Learning solutions for real world problems
1. Browse 3. Copy
Your Apps
4. Paste2. Select

24. Reduce Implementation Effort and Accelerate Development
Simplify integration and have more stable applications – 75% faster to build apps

25. Search video as easily as text
Transform rich media into intelligent assets
Inquire
“Search your data”
Investigate
“Analyze your
data”
Interact
“Personalize your
data”
Improve
“Enhance your
data”
Live video or playback
from archived footage
On-screen text
recognition
Face identification
Automatically generated
transcript using speech
recognition
Speaker identification
Timecode
synchronization
Automatic keyframe
generation
Automate
Automatically create metadata,
keyframes, transcriptions
Understand
Understand video footage and audio
streams in real time
Act
Apply advanced analytics such as
clustering and categorization, and link
with other file types

26. Image technology: 2D objects
Registered image Test image
Generic Logo recognition
Registered
Logos
Test image
Inquire
“Search your data”
Investigate
“Analyze your
data”
Interact
“Personalize your
data”
Improve
“Enhance your
data”

27. Intuitive Knowledge Discovery for Self-Service Analytics
27
Visualization to simplify analytics workflow Topics Map
Sunburst
Result Comparison
Rich Contextual View
Business Intelligence for Human Information (BIFHI)

28. HPE Virtual Assistant – Cognitive Chat Bot
An illustrative case study
A few ways to approach this:
1. Build a big long list of 5,000-10,000 Q&A pairs
Not really cognitive AI though is it?
2. Build a cognitive solution that automatically
extracts answers from data
Conceptually understands the ideas and meaning.
Seamlessly combines multiple analysis techniques
(Probabilistic Conceptual Analysis, Machine Learning,
Neural Networks, etc.)
28
This kind of full automation requires a platform with a few pre-requisites:
1. Universal connectivity, out of the box
2. Automatic processing and fact extraction
3. Cognitive Analytics platform supporting all data formats and including a broad range of
algorithms

29. Yahoo! Finance
News (text and broadcast)
Annual Reports
User profiles
Market data
Company profiles
Company Websites Facts
Raw Data Sources Knowledge Creation and Analysis
HPE’s flexibility, adaptability and speed makes this a seamless process
HPE Cognitive Analytics: ingest data from any source and
create knowledge
HPE
IDOL
8

30. 30
HPE Augmented Intelligence automatically identifies and
extracts facts from documents
ASOS Annual Report 2015
ASOS Summary
Chief Executive Officer = Nick Beighton
Total revenue growth = 18%
Profit before tax = £47.5m
Cash position = £119.2m
UK Retail sales = £473,885,000
Group total revenues = £1,1550,788,000
…
• Language independant
• Automatic table recognition and field extraction
HPE IDOL

31. HPE cognitive analytics mirror human thought
31
Stock price
query
Swaps
IR Hedging
Human Working Memory
“Attentional spotlight”
≈ stack task hander
Semantic, declarative
and procedural
memory
≈ Conceptual
classification
• High user ‘intentionality’
means any task can be
added to ‘stack’
• LIFO method means
natural conversation
subject hierarchies and
conversational
digressions can be
accommodated
• Human like topics mean
system is transparent
and dialogue process
auditable
IR
Hedging
FX
Hedging
Loan
Multilateral
Loan
Bilateral
Loan
Trade
Finance
Guarantee
Documentary
Cash
Management
/ ALM
Investing
Client
Question

32. HPE cognitive analytics is trained to understand user dialogue,
and continues to learn from each user interaction
32
IR
Hedging
FX
Hedging
Loan
Multilateral
Loan
Bilateral
Loan
Trade
Finance
Documentary
Guarantee
Cash
Management
/ ALM
Investing
“I’m interested in
borrowing money
to invest in a new
production line”
“I’m not sure I
completely
understood you.
Did you want a
loan; or were you
asking for a credit
line, or securities
account and
brokerage
service?"
Intent Score
Loan 0.72
Credit Line 0.58
Investing 0.49
User
HPE Virtual
Assistant

33. Case study – Cognitive Chat Bot
33

34. Summary
• Artificial Intelligence is not here yet, and likely will not be for some decades at least
• Instead, the focus in on Augmented Intelligence – using machines to make people smarter and
more effective
• The key to success and achieving business value is agility and innovation. Build fast, fail fast.
• Everything is derived from the data – never underestimate the importance of being able to
access, ingest and process the raw data
• A broad range of analytic tools and algorithms are key to this agility and innovation. An open
and transparent architecture is critical for futureproofing and allowing for further innovation.
• Only HPE’s pioneering AI platform is uniquely able to facilitate all of the above – through
connectivity, breadth of analysis, and ease of application development and innovation.
34