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

HavenOnDemand.com

@HavenOnDemand

A (very brief) history of AI

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.

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Next attempt: neural networksAttempt 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.

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Which brings us to todaySmart 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

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Machine Learning at the Service of BusinessAugmented Intelligence

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 appsand services

Analyze and apply perishable dataanywhere 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

How do you bridge the gap between data and outcomes?

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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

Augmented Intelligence power apps for competitive advantage

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Augmented Intelligence powered by HPE

Artificial intelligence, machine learning and natural language processing using advanced analytics functions.

Human data

Connected people, apps and things generating massive data in many forms

Machine data

Business data

faster growth

than

traditional

business data

10x

HavenOnDemand.com

@HavenOnDemand

What’s so difficult about human information?

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

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”

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

HavenOnDemand.com

@HavenOnDemand

But we are all fine with structured data, right?

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

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 integrationwith existing ETL and BI solutions

SQL-99+ compliant Ultimate deployment

flexibility Extended advanced

analytics 24/7 Load & Query

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- 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

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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

HavenOnDemand.com

@HavenOnDemand

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

Over 70 APIsConnect, extract, index, search and analyze

Real life challenges

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eDiscovery

Fileshareanalysis

Call data

Broadcastmonitoring

Website search

HPE Haven OnDemand Combination APIsReusable 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.

HPE Haven OnDemand Combinations Marketplace for cognitive servicesAccelerate development with copy and paste Machine Learning solutions for real world problems

1. Browse 3. Copy

Your Apps

4. Paste2. Select

Reduce Implementation Effort and Accelerate DevelopmentSimplify integration and have more stable applications – 75% faster to build apps

Search video as easily as textTransform 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

Timecodesynchronization

Automatic keyframe generation

AutomateAutomatically create metadata, keyframes, transcriptions

UnderstandUnderstand video footage and audio streams in real time

ActApply advanced analytics such as clustering and categorization, and link with other file types

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”

Intuitive Knowledge Discovery for Self-Service Analytics

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Visualization to simplify analytics workflow Topics MapSunburst

Result ComparisonRich Contextual View

Business Intelligence for Human Information (BIFHI)

HPE Virtual Assistant – Cognitive Chat BotAn 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.)

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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

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

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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

HPE cognitive analytics mirror human thought

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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

HPE cognitive analytics is trained to understand user dialogue, and continues to learn from each user interaction

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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 VirtualAssistant

Case study – Cognitive Chat Bot

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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 openand 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.

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