"empower developers with hpe machine learning and augmented intelligence", dr....
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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
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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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