Ensuring Technical Readiness For Copilot in Microsoft 365
Technology innovation through AI
1. Technology innovation through AI
Leveraging legacy data in AI. Modernizing legacy systems with AI.
Glen Koskela
Fujitsu Fellow Asysco Technology Conference 2017
Chief Technology Officer, Nordic Alkmaar, the Netherlands
Head of New Business Development October 11th, 2017
2. Copyright 2017 FUJITSU
AI can help any kind of business
AI is all about learning from data to automate, optimize and predict events
AI technology should be part of application modernization and innovation processes and
in order to constitute real value, should take into account data on existing IT scenery.
CHANGE IN
DEMOGRAPHICS
CUSTOMER
EXPERIENCE
HEALTH, WELLNESS,
WELL BEING, SAFETY
GLOBALIZATION,
URBANIZATION
INTELLIGENT
SERVICES
DIGITAL CHANNELS
AND BEHAVIOUR
In many cases however, the information we can get from open
data, physical world, unstructured content, and social listening
is far richer than what we can collect from the legacy systems.
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Market drivers for IT modernization
Specialization across physical value chain
Transaction processing
Management information systems
Components & products
Specialization across information value chain
Information & processes, Online information systems
Global functional organization and BPOs
Decision support and BI systems
Specialization across human value chain
Collaborative learning and problem solving
Knowledge work agents, Analytical systems
Community collaboration tools
To output an accurate answer, the system needs accurate inputs
MRP; MRPII; SCM; PLM; ERP;…
Email; Internet; Extranet; eCommerce; UC;
EDI; Web1.0; process automation; SOA,…
Cloud; blogs; social networks; tweets; communities;
crowdsourcing; Web2.0; SaaS; gamification,…
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Paying down technical debt
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Changes how development staff works – but preserves business logic
Application, data and process
modernization to unleash the potential
in existing applications and data
Data and business logic as objects and
methods that can be consumed by new
applications and engines
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Next: exploration for smarter service models
Industrialized use of algorithms to drive improved business decisions or process automation
Purpose of the firm will no longer be to minimize the transaction costs of doing business:
algorithms, leveraged assets, automated knowledge, staff on demand, social engagement, community & crowd,…
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Artificial Intelligence/ML/DL; APIs;
IoT; AR/VR; Robotics; DLT;…
Specialization across dynamic digital value chain
Data driven Artificial Intelligence, Machine/Deep Learning, Cognitive computing
Digital transformation, Service enablement
Cyber-physical systems, Advanced automation and control
Un-linear business models, Platform economy
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Modernization with AI is transformational
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Improved decision making
Increased visibility & transparency
Better customer insights
Better protection from security threats
Immense predictive power
Machine Learning, Deep Learning, Neural Networks
What ICT can do by itself
What ICT and AI can do
What we should do with
human-in-the-loop
Big data analysis
Automation/Autonomization
Knowledge accumulation
Customer contacts enhancement
Manufacturing transformation/SCM
Work style reform
Social issue solution
Logistics optimization
Disaster prevention
Decision-making support
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Efficiency improvements in operations
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Monitoring use of auxiliary power units usage
at airports to reduce environmental impact
Planes at a stand are supposed to turn off their auxiliary turbine
APU engine signature
sound is sampled and
analyzed in the cloud
CC BY 2.0 photo credit: https://www.flickr.com/photos/beigephotos/11453358366/
Reduce noise equivalent to c35,000 aircraft take-offs per year,
reduce air pollutants by 12,455 kg per year and NoX by 4%,
fuel savings c£480k per year, increased ground power revenue,…
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CC BY 2.0 photo credit: https://www.flickr.com/photos/56380734@N05/7449294024/
Uses machine learning to automatically identify patterns which indicate that there is a defect
Transformation of inspection processes
Visual inspection by level 2 operator to detect defects in the
structures and different layers of fibers is reduced by 83%,
translating into a saving of 34,000 man hours per year.
Ultrasound images (quality assurance)
Drone-captured images (buildings)
Protein crystallography images (drug production)
Line scan and laser camera images (railways)
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Prevention of phone scams
Prevent phone scams using keyword detection and emotional instability analysis
CC BY 2.0 photo credit: MattysFlicks https://www.flickr.com/photos/68397968@N07/10665288243/ CC BY 2.0 photo credit: Rooftop Mind https://www.flickr.com/photos/rooftopmind/4726894486/
Process data into information
into knowledge into new
services or decision support
“You owe IRS $1986.73 due to miscalculation
of taxes from 2011 to 2014…”
“Well, how could that have happened,…”
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Petrol station consumer behavior
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Vehicle counting
Vehicle type classification
Vehicle brand classification
License plate recognition
Queue time calculation
Service time at pump
People counting
Heat map
CC BY 2.0 photo credit: Serigne diagne https://https://www.flickr.com/photos/diagne/3212170482/
Real time video analysis of vehicles and consumers
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Helping cities to transform with digital
Internet of Things analytics and
decision support for urban public
transportation in smart cities.
Current state of operations on the ground
Visualization of service and passenger flows
Prediction of delays and chain of effects
Line and composition recommendations
Behavior analysis
Prediction of overcrowding
Multi-modal transport routes
Visualization of real-time situation
Real-time multi-modal traffic management
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Multi-modal transport, journey planner & ticketing
Determine service needs in light of current traffic conditions.
Inform passengers about current mobility options.
Extend with digital ticketing and payment system.
Geospatial big data analytics: traffic, venues, weather, incidents,…
New and more integrated modes of
transportation, entirely novel concepts of
ownership for vehicles, and a trend towards
cooperative automated driving fuse with
rising demands of high livability in smart
cities that offer safe, affordable, and
sustainable transportation.
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Prescribe most appropriate treatment
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Analysis of patient records as
data-based knowledge graph
Early detection of potential future patients and
their risks, addressing e.g. mental health
issues, using data analytics to identify patterns
Health risk algorithms to assess the mental
health risks of thousands of patients’ using
medical history data and non clinical data
(including over a million medical papers)
Helping doctors make more accurate clinical decisions by using AI
Already 95% as accurate as a team
of 8 clinicians – but in seconds
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Financial knowledge processing
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Analysis beyond performance comparison and business transactions
Financial reports
Stock prices
Customers’ private data
Newspapers
Social networking services
Wikipedia
Cross-sectional analysis of various
aspects of corporate activities
from financial statements, stock
prices, products and reputations
Uncovering non-obvious relationships between
people and institutions to offer a holistic view
Heterogeneous data federation
Machine learning
Deep learning analysis
Dynamic graph network analysis
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Smart factory transformation
Automate collection, analysis, prediction, and
comparison of factory-wide KPI information
across all regions, plants, production lines,
equipment, and orders, lots, shifts,…
Visualization, revelation, analytics
Unprecedented visibility of the manufacturing facilities in real time