The Era of Cognitive Computing

Transcription

1 The Era of Cognitive Computing

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6 Why Now? We ve been hearing about this forever: Fuzzy Systems Artificial Intelligence Natural Language Processing These things: Gaming - $64 billion Search indexed knowledge SaaS app marketplace Devices compute everywhere Also

7 Google Acquires Deep Mind

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9 IBM Watson

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14 Why Is Smart Required for IoT and Cloud?

15 Cloud The umbrella term for anything available over a network Relevant attributes which typify and classify architectures include Public or private Virtualized or non-virtualized Service oriented or person oriented Hardware oriented or platform oriented or software oriented Organizationally oriented or personally oriented Secure or unsecure Paid or free Paid by quality attribute or paid by operational attribute Guaranteed or unguaranteed

16 Internet of Things Identifying all physical and virtual objects on a network Relevant attributes which will typify and classify architectures may include Type of IoT identity (hardware, network, software, service, invoker, agent, intelligent agent, independent intelligent agent, provocateur) Size or scope of object (molecular -> planetary) Data type/volume consumption/production Power consumption/production Location and Mobility Object interaction power in virtual, physical or both Intention and Autonomy

17 Proposed Hierarchy of IoT Identities Provocateur - Intelligent agent with intention (human level) Independent Intelligent Agent - Intelligent agent acting without permission Intelligent Agent Agent with a degree of reasoning capacity Agent Invoker which changes addresses in some way Invoker Service which calls other services Service Software object which returns a complex response Software Network object which returns a simple response Network An object which is addressable over a network Hardware An object which is identifiable over a network

18 How is Smart Implemented Now Advanced Search Genetic, Graph Theory Inferencing (Deductive, Inductive) Fuzzy Reasoning Optimization Learning Interpreting and Language Negotiation

19 Searching for Information Information has to be constructed from data and context There is more data and information in the world than we can process Intelligent search is key to our ability to make use of information Common applications: business intelligence, lifestyle optimization, interest optimization This is what Watson is really aimed at - semantic interaction of people and systems

20 The Rules We Live By Most companies have large numbers of commonly modified rules Inferencing allows us to deduce new information within context (forward-chaining) induce information from existing data (backward-chaining) Common Applications: Insurance rates and converage, retail pricing and discounts, purchase decisions, lifestyle choices If the train is late let me sleep in

21 Fuzzy Reasoning and Controllers Humans and business work on fuzzy definitions which is simply that most things are both true and not true It is cold in Sweden may be true to a Texan but not an Eskimo! A cup is also a bowl can be more or less true That hotel is extremely expensive for me but Bill Gates? Allows our devices to be more precise and selective in decision making and reasoning Pre-heat the car when it is very cold We buy very high quality business supplies Common Applications: Energy utilization, mechanical controllers, human definitional input

22 Optimization Business processes, graph navigation, optimal path traversal, and business integration all involve process optimizations Multi-processes integration beyond the simplicity of a single service (physical or virtual) control much of our lives Utilization of embedded process engines and optimization allows for maximum flexibility of physical and virtual agents Common Applications: multi-partner business transactions, automated delivery systems, personal travel itineraries, multidevice automation

23 Learning More and more data and choice is available to system software As automation and autonomy become ubiquitous training in desired outcomes is necessary for personal and business The vast amount of data and information requires grouping, characterizing and classifying Neural networks and decision trees Common applications: Food, travel and personal preferences, natural language processing, optimal energy input/output, security threat detection Welcome Azure ML

24 Thing to Thing Communication Language, dialect, grammar, vocabulary and pronunciation are all relevant in IoT communications and configuration Knowledge and language ontology and dictionary will be essential to self-configuration (and therefore adoption) This may be the single most difficult task in the IoT Even humans struggle with this constantly Molecular data element combinations are not solidified (what is an address, a name, a birthday) Common applications: Thing configuration and communication, business analytics, service orchestration, personal identity management (pay for use)

25 Negotiation As systems begin to represent us there is more and more conflict What is the best price we can get for pencils for employees Using negotiation techniques to avoid conflict with game theory Common applications: Device resource allocation and utilization, purchasing

26 Considering Value and Risk Value to Who? Individuals Governments and NGOs Vendors and Service Integrators For Profit non-vendor What type of Value Lifestyle Social Value Financial Value Customer Operational Value Societal Human Value Risk to Who? Individual Corporation Governments What type of Risk? Physical Financial Societal

27 How Smart Becomes Value There is a world of new objects to sell to the world There is an unlimited number of ways to incorporate new inventions into multiple channels, services and products Learning about your customers and partners Dynamically allocating resources and processes Optimized pathing Planning and forecasting Configuration management and ease of use Human interaction and reasoning

28 Architecture Value Profitability Constituent Value Reuse Grow Market Size Grow Market Quality

29 What is creates value? What is Good? suitable or efficient for a purpose beneficial or advantageous

30 What does Smart Mean Tomorrow We must begin to consider systems as more than software services Autonomy the degree to which systems can act without permission Power (to influence) the amount of influence or size of outcomes a system can achieve Resources (to command and use) the size and makeup of objects a system may use Motivation as systems gain more power and autonomy we will need to understand Combat when systems with autonomy, power and resources disagree about outcomes

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32 The use, disclosure, reproduction, modification, transfer, or transmittal of this work without the written permission of IASA is strictly prohibited. IASA 2014 Accomplishments More than 2,500 individuals trained globally in 2014 More than 2000 individuals certified Y2D Core courses updated to version 4.0 Capabilities Guidebook project launched ( CITA-S certification launched Solution and Enterprise course and certification launched Major companies standardizing to Iasa skills & certifications: Avanade, AstraZeneca, Volvo, Citrix, Dell, Costco, Microsoft, TMobile

33 Iasa business model The business model canvas KEY PARTNER KEY ACTIVITIES OFFER RELATIONSHIPS Customers Membership Personal Network Communities Thought leaders Education Events KEY RESOURCES Career Growth Problem Solving Giving Back Knowledge Resource CHANNELS Architects Large Companies Communities Events Subscriptions COST CENTRES People Events REVENUE STREAMS Membership Sponsorship Education Source: Canvas by businessmodelgeneration.com

34 Iasa Strategy Map Programs Measures Financial Grow Revenue Member Value Improve Quality Community Membership Education Chapter Levels Member Sat Job Opportunities Grow Membership Increase Program Participation Customer Content Development Program Development Community Development Membership Drive Chapter GEM # Members Member Programs Process Community 3.0 Technology People Training Program Development Techniques # new programs People, Knowledge GEM Training Guide Contribution to

35 Skill Taxonomy The use, disclosure, reproduction, modification, transfer, or transmittal of this work without the written permission of IASA is strictly prohibited. IASA 2009

36 Engagement Enterprise Enterprise Architects Finance Sales LOB IT Business Architects Interns Information Architects Interns Business Capability Software Architect Infrastructure Architects Interns Software Architect Interns Software Architect Interns Data Center

37 Career Path

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