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Kyield OS 12-2016


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This presentation reflects the current version of the publicly shared portion of the Kyield OS as of December, 2016, which includes DANA. An extensive audio is included for live presentations lasting about an hour. Tailored presentations have been provided for many of the world's leading organizations and are available by request. Some restrictions may apply. Please contact me for more information (Mark Montgomery ).

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Kyield OS 12-2016

  1. 1. Kyield OS A Distributed AI System for Optimizing Human and Machine Intelligence Mark Montgomery Founder & CEO
  2. 2. Background of founder & Kyield (All within USA) 1980s WA State ...Student Worker Entrepreneur ‘Team WA’ Consultant Executive 1990s Arizona Consultant Publisher Lean Incubator SW programmer Hands-on live KS lab ‘Yield management of knowledge’ theorem Russell Borland 2000s AZ/SV/NM AZ VC SV VC NM scientist Inventor Patent application Negotiations Negotiations Negotiations 2010s NM AI sys patent award Pivot to customers C-Suite EDU on AI Testing models Kyield viability Pilot phase Next gen R&D Student... 2© Copyright Kyield 2016
  3. 3. Definitions for this talk (All Mark Montgomery quotes) AI (Artificial intelligence) Any combination of technologies and methodologies that result in learning and problem solving ability independent of naturally occurring intelligence Distributed AI Systems An engineered system consisting of algorithmic functionality executed by software modules over distributed networks AI Augmentation Enhancing the quality of human work products and economic productivity with the assistance of AI Beneficial AI AI that has been programmed to prevent intentional harm and to mitigate unintended consequences within a strictly controlled governance system 3© Copyright Kyield 2016
  4. 4. The rule (s) of law (s) 1. Governments • Compliance is required, but insufficient. AI systems governance can provide an attractive ROI for organizations of all types 2. Competition • Most are investing in AI systems today due to competitive threat. Opportunities are largely secondary and overlooked 3. Physics • Enterprise-wide functionality is physically required to achieve many critical functions including crisis prevention of potentially fatal events 4. Economics • While costs are falling, AI systems do require a significant investment Unified costs are high, but risks and opportunities are much higher 5. Corporate Policy • A determent influence on architects as well as a requirement of system design; policy and governance are particularly important in AI systems 4© Copyright Kyield 2016
  5. 5. Examples of AI systems Military Predator Drones Fighter Jets Ships Submarines Insect Drones Logistics UPS Orion DHL Parcel Robot RR Command Center Transportation Cars | Trucks Buses | Trains Air Taxies 5© Copyright Kyield 2016 Internet of Entities Google Facebook GE Amazon Automakers Biotech Implants Smart Drugs Real-time Diagnostics Agriculture Dairy Case IH ACV Greenhouses Lodging Room Service Concierge Entire Property Financial Robo Advisors Distributed Platforms
  6. 6. Key issues in AI systems 1. Tend to be highly complex and very expensive • Usually requires leadership by CEO with team consensus • 90+% of costs in AI and ML are for talent • Growing number of internal multi-billion USD AI programs 2. The talent war is real • Number proven to advance AI is in the dozens globally 3. System design and business models are critical • Increasing numbers are expanding into new sectors • Old IT models are not necessarily best match in AI era 4. Algorithmics are dynamic and rapidly evolving • ML is often best employed as a continuous process (system) • Algorithms require constant tweaking and improvement 5. Commoditization is a double edged sword • Most need both lower costs and greater differentiality 6© Copyright Kyield 2016
  7. 7. AI-enhanced workplace 7© Copyright Kyield 2016
  8. 8. Governance Inspired by nature. Managed by humans. Assisted by AI. Discover Secure Prevent Collaborate Create Produce Learn Adapt Group Knowledge Worker Organization Regulator Customer Partner 8© Copyright Kyield 2016
  9. 9. Redacted Redacted Redacted Redacted 9 ‘Yield Management of Knowledge’ Applied to achieve a CALO (Continuously Adaptive Learning Organization) © Copyright Kyield 2016 Patented:USPTO#8005778 CALO
  10. 10. Individual module example • Tailored to each entity • Self-managed NLP profiles • Network-wide engine (CKO) • Network-wide prevention • Proprietary security • Prescriptive deep learning • Personalized voice bot • Productivity metrics • Module data tuner • Knowledge currency 10© Copyright Kyield 2016 Some Functions Reflected are Patented: USPTO #8005778
  11. 11. DANA Digital Assistant with Neuroanatomical Analytics 11© Copyright Kyield 2016 Some Functions Reflected are Patented: USPTO #8005778 Algorithmic Functionality • Prescriptive intelligence • Probabilistic reasoning • Information valuation • Relationship management • Productivity optimization • Team optimization • Voice bot integration • Network security • Scale optimization Examples of Uses  Improve productivity  Personalized health mgmt.  Optimize performance  Reduce catastrophic risk  Prevent accidents  Expedite innovation  Reduce liability & costs  Home / Office / Mobile  Auto / Corporate / IoT
  12. 12. Proprietary security & privacy • Designed-in from inception • Relationship algorithmics • Behavioral screening • Personal metrics • Knowledge currency • Tight admin controls • Full transparency in all modules • Less intrusive than many current applications 12© Copyright Kyield 2016
  13. 13. A few use case scenarios Prevention and/or mitigation • Industrial accidents, malintent and fraud • Fukushima Daiichi nuclear disaster ($105bn) • Deepwater Horizon oil spill ($62bn) • VW emissions scandal (set aside $18.2bn) • Many smaller common events in all organizational types • Mitigate systemic crises • 9/11 – Phoenix memo, Iraq war ($10tn+) • Global financial crisis ($22tn – GAO) • Pandemics • Risk management platform • Reduce operational risk and liability • Lower IT, insurance, and borrowing costs 13© Copyright Kyield 2016
  14. 14. More use case examples Productivity & Collaboration • Financial and health management • Industry specific platforms due (primarily) to regulatory • Accelerate R&D • Pharma patent cliff is a prime example • Avoid disruption by competing with the best innovators (winning?) • Expansion into new markets • AWS is now the best business at Amazon • GE is transforming into an industrial IoT company • Automakers are moving to autonomous cars and fleet ownership • Insurers are becoming operational guardian angels 14© Copyright Kyield 2016
  15. 15. Issues for adoption in AI systems 1. EDU: CEO, CFO and board of directors (some CIOs) • Much progress has been made, however…. 1. A minefield of legacy and alliance conflicts (all kinds) 2. Business models are often in direct conflict with customers 3. Supply chains and ecosystems are changing due to AI 2. Applications & Financing • Estimates vary; 50% in testing some AI/ML sounds accurate 1. Many are misapplying AI/ML and/or products 2. Small ML projects are easier to fund, but majority of cases don’t resolve bigger issues facing enterprise (few exceptions) 3. Modeling & Ecosystems • Industry needs modeling and relationships that match AI 1. Ecosystems may need to be new or completely reconfigured 15© Copyright Kyield 2016
  16. 16. Summary 1. Distributed AI systems are now (finally) viable • Costs have fallen dramatically; still a significant investment • Super majority of costs are in human talent 2. Most valuable use cases requires a unified system • One-off ML projects are easier to fund, but can’t resolve or prevent majority of big issues facing organizations or highest ROI 3. Governance is complex and critical • There is an awful lot to know about AI systems… 4. AI is rapidly reshaping some of the largest industries • Ignoring it won’t make it go away 5. IT models not necessarily best suited for AI systems • Need new options in finance models, alliance structures, and licenses 16© Copyright Kyield 2016
  17. 17. Contact Contact Mark Montgomery Founder & CEO 17© Copyright Kyield 2016