Smarter Planet megatrends: Learning Systems Roadmap

Smarter Planet
megatrends
- Jørgen Floes, Chief Architect Nordic SO Delivery

© 2012 IBM Corporation

Smarter Planet megatrends

The IT world is changing - driven by shifts in market dynamics and
client needs

Big Data1
Growth Markets8
Through 2015, more than 85 percent
By 2015, IDC expects
of Fortune 500 organizations will fail
emerging markets to generate
to effectively exploit big data for
over 33% of all IT spending
competitive advantage
Security7
Analytics2
Through 2016, the financial impact of
cybercrime will grow 10 percent per Through 2015, more than 90% of

Software
year, due to the continuing discovery of business leaders contend information
new vulnerabilities is a strategic asset, yet fewer than
10% will quantify its economic value
Hardware
Customer
Sets
Technology Business
Cloud6 Social Business3
Services Services
63% of companies already are using By 2014, 20% of business users will
(Cloud) or expect to use it in 2012, up replace email as the primary interpersonal
from 49% last year communications with social networking

Mobile Enterprise5 Smarter Planet4
66% of CIOs ranked mobility as a
IBM Smarter industry solutions will
top investment priority in 2012
grow 5x faster than total solutions

Smarter Planet megatrends - © 2012 IBM Corporation 2


IBM’s transformation has gone through distinct phases in the past
decade; the “smarter” phase of the journey is underway
2002
Sharing & partnering

2006
Globally integrating

Consistent set of
processes worldwide 2010
Leverage best Making things smarter
practices
Right skills, right
Standardize and place, right cost
reduce waste 2012
Rationalize support
Governance and functions for greater
performance efficiency Being essential
discipline Instrumented,
Radically simplify interconnected, intelligent
processes New era of computing
Enable growth and Changing client
productivity
Evolving IBMer
Optimize the whole system


Global Technology Outlook



IBM Global Technology Outlook Objectives

GTO identifies significant technology trends
early. It looks for high impact disruptive
technologies leading to game changing
products and services over a 3-10 year
horizon.

Technology thresholds identified in a GTO
demonstrate their influence on clients,
enterprises, & industries and have high
potential to create new businesses.



GTO 2012 – The Genetic Map


Technology example: The Watson System



Future Systems – The Learning Paradigm

Society Nature Institutions Archives

(Natural Interfaces)
Training and Learning Engines
To Build Models and Define Insight Policy Engine
Active Learning Business, Legal
and Ethical Rules

Verification Engines Hypothesis Engines
(e.g. Simulations) To Understand and Plan Actions

Outcome Engine
Actuation and Validation



Watson – a Workload Optimized System

Hardware
90 x IBM Power 750 servers
2880 POWER7 3.55 GHz cores
500 GBps on-chip bandwidth
15 Terabytes of memory
500 GB of data (in memory)

Software
IBM DeepQA,
UIMA and UIMA AS
Apache Hadoop



Learning Systems Roadmap to Meet the Challenge
Autonomously & accurately identify essential features across multiple domains.
Learning systems must understand context to disambiguate.

Autonomous
Dynamic Learning Systems Learning Systems
Achieve understanding
Dynamic Data Corpus
of natural language,
Expand Hypothesis Generation to different
Watson images and other sensory
domains (leverage crowd-sourcing)
information. Hypothesis
Static Learning Add Scorers for Different Input Modalities:
and question generation
images, video, voice, environmental, biological;
Keyword Systems leverage new devices & hardware acceleration
across arbitrary domains;
meta-heuristic to
Search Expert teams identify Deeper Reasoning: Allow higher-levels of
automate algorithm
features across semantic abstraction. Leverage new hardware.
Delivers lists choices
industries, create first Domain Adaptation Tools
based on
commercial learning
keywords &
systems
human filters Biological Inspiration: Cognitive Process Understanding

1985 2010 2015 2020 2025

Greater Autonomy

Big Data and Predictive Governance
Speaker: Steven Adler



Internet of Things Scenarios Show a Pattern of Customer Pain
Points
Water Management Grid Food Safety

Logistics Home Healthcare Transportation

Collecting information to provide better service and work smarter
Establishing the smarter planet!



Uncertainty of data arises from many sources

Process Uncertainty Data Uncertainty Model Uncertainty
Processes contain Data input is uncertain All modeling is approximate
“randomness”

Intended Actual
Spelling Text Entry Spelling

? ?
? Fitting a curve to data
Uncertain travel times GPS Uncertainty

? ?
Testimony
?
{Paris Airport}
Ambiguity

{John Smith, Dallas}
Semiconductor yield {John Smith, Kansas} Forecasting a hurricane
Contaminated? (www.noaa.gov)
Rumors Conflicting Data



By 2015, 80% of all available data will be uncertain

By 2015 the number of networked devices will
be double the entire global population. All
9000
sensor data has uncertainty.
8000 100
Global Data Volume in Exabytes

90 The total number of social media
7000
accounts exceeds the entire global
Aggregate Uncertainty %

80 population. This data is highly uncertain
6000
in both its expression and content.
70

)
gs
rs
5000

hin
rn nso
60

fT
Se

o
4000 Data quality solutions exist for

et
50
enterprise data like customer,

te
(In
3000 40 product, and address data, but
this is only a fraction of the ia )
M ed d text
2000 30 total enterprise data. ial an
oc audio
S ,
20 eo P
1000 (vid VoI
10
0 Enterprise Data
Multiple sources: IDC,Cisco
2005 2010 2015



Every Smarter Planet Solution has Big Data and Needs Big Analytics

Smarter Planet

Faster Decisions Deeper Insights
Real-time Awareness Predictive Models
Reactive Analytics Deep Analytics

Data in Motion Data at Rest
Big Data


New “Big Data” Brings New Opportunities, Requires New Analytics
Exa Homeland Security
600,000 records/sec, 50B/day
Up to
10,000 1-2 ms/decision
Times 320TB for Deep Analytics
Peta larger
Data Scale

Telco Promotions
Tera 100,000 records/sec, 6B/day
Data at Rest
Data Scale

10 ms/decision
270TB for Deep Analytics

Giga
DeepQA
100s GB for Deep Analytics
Traditional Data 3 sec/decision
Mega Warehouse and
Business Intelligence
Up to 10,000
Data in Motion times faster Smart Traffic
250K GPS probes/sec
Kilo
630K segments/sec
yr mo wk day hr min sec … ms µs
2 ms/decision, 4K vehicles
Occasional Frequent Real-time
Decision Frequency

Smarter Computing: Expert Integrated Systems
Speaker: Jean-Michel Rodriguez



Big Data Systems Require a Data-centric Architecture for Performance

Old Compute-centric Model New Data-centric Model
Manycore FPGA

out
put
ut Massive Parallelism
i np Persistent Memory

Flash Phase Change
Data lives on disk and tape Data lives in persistent memory
Move data to CPU as needed Many CPU’s surround and use
Deep Storage Hierarchy Shallow/Flat Storage Hierarchy

Largest change in system architecture since the System 360
Huge impact on hardware, systems software, and application design


Storage Class Memory - The Tipping Point for Data-centric Systems
(Phase Change)

FLASH

SCM in 2015
$0.05 per GB
$0.10 / GB $50K per PB

$0.01 / GB
Relative Relative
Source: Chung Lam, IBM
Cost Latency
DRAM 100 1
SCM 1 10
FLASH 15 1000
HDD 0.1 100000
HDD cost advantage continues, 1/10 SCM cost, but
SCM dominates in performance, 10,000x faster than HDD



2015 Vision: The Peta2 Data-centric System Petascale = Petaflop OR Petabyte
Petaflop x Petabyte = Peta2

Goal Relative System
– Data-centric, latency optimized, massive capacity 281x 336x
Density per Rack
system for long-running analytics and simulation
applications
35.7x
Requirements
– 1 Petaflop performance, massively parallel
12x
– 1 Petabyte BPRAM
– Extremely low latency, high bandwidth
interconnect (Xapt) 2.3x
Assumptions 1x 1.4x
– Majority of data stays resident in memory for long
periods, minority of data updated continually
– Persistent Memory becomes primary storage Peta2

+
2015 Peta2 Data-centric System Reactive+Deep Analytics Peta2 Analytics
POWER 8/A2, BPRAM ITEs on Harrier Platform Appliance

This system can become the System 360 equivalent for the Era of Analytics


Announcing the First Two Members of the IBM PureSystems Family

Infrastructure System: Platform System:
Expert at sensing and Expert at optimally
anticipating resource deploying and running
needs to optimize your applications for rapid
infrastructure time-to-value



IBM PureFlex System is Integrated by design
Expert
Integrated
Systems

Networking

Storage Virtualization

Compute Management

Tools Applications

Flexible and open choice in a fully integrated system


Mobility: Enabling mobile workstyles
and embrasing cloud
Speaker: Erik Pedersen


Social Business
Speaker: Stuart McRae



Adoption of Social Tools is Increasing Rapidly
Growth in Adult Social Network Site Use, 2005-2009 Companies plan to increase spending on social despite recession

Public Enterprise

Fortune Global 100 Companies
US Mobile Subscribers
Accessing Social Sites Companies with ... Twitter Accounts Facebook Fan Pages YouTube Accounts
(Thousands) 65%
54% 50% 72% 71% 69%
65% 67% 59%
Jan-09 Jan-10 Change 54% 52% 52%
50%
33% 40%
40% 35% 33%
Facebook 11,874 25,137 112% 33%

MySpace 12,338 11,439 -7%
Twitter Facebook YouTube Corporate
Total US Europe Asia LatAm Total US Europe Asia LatAm Total US Europe Asia LatAm
Twitter 1,051 4,700 347% Accounts Fan Pages Channels Blogs

Source:comScore MobiLens Source:Burston-Marsteller



Convergence of Social and Analytic Technologies Transform the
Way Businesses Operate

Socially Synergistic Enterprise Solutions
New top-line opportunities, better relationships with customers and partners,
enhanced talent pool, increased resiliency and efficiency

Individuals
Teams

Analytics Social Organizations

Society

Business
Data aggregation Process Customer Sentiment
Smart filtering Transformation Unmet Needs
Meaning extraction Talent Discovery
Consumable analytics Reasoning and Decision Support
Process orchestration Crowdsensing, Crowdsourcing
Stream processing Teaming, Incentives, Motivation

Data
Physical Enterprise Social
Sensors & Streams Data from and about People



Socially Synergistic Enterprise Solutions Can Provide Differentiating
Value

Customer Care and Insight Workforce Optimization Physical Meets Digital

Financial Operations Smarter Commerce Advanced Case Management



Thank you!


Smarter Planet megatrends: Learning Systems Roadmap

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