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Inventurist fast track adoption of ai innovations shared.pptx

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Artificial intelligence is a foundational technology that will impact every industry and type of business. In that respect, AI is very similar to the Internet and right now it's where the Internet was in the mid 90s. The timing for understanding AI and applying it in your business is now!

However, AI is also a vastly broad topic and exceedingly complex set of technologies. In this talk, we will discuss how the AI technology itself can lower your barrier-to-entry into AI.

WHY? Because AI is automating and streamlining the process of discovering and validating many potential applications in a particular domain. With the help of automation and analytics tools, innovation and product managers with minimal technical will learn to quickly generate multiple 'designs' for new AI products or solutions and validate and rank their designs.

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Inventurist fast track adoption of ai innovations shared.pptx

  1. 1. Fast-Track Adoption of AI Innovations Cirrus Shakeri, Ph.D. Co-Founder & CEO-CTO Inventurist Venture with Confidence April 2018 Gil Heydari, MBA Co-Founder & COO-CAO Inventurist
  2. 2. Copyright Inventurist 2018 Outline of the Talk 2 ● Introduction ● What is AI? (elephant in the dark) ● Big benefits and big challenges (like anything else in life!) ● Approach AI methodically (discover benefits and minimize challenges) ○ ‘AI Product Engineering’ (an Inventurist invention) ○ It’s a marathon not a sprint! (the grind of product-market fit) ● Tools can help (like … umm … AI?) ○ AI Product Design Platform (an Inventurist invention) ● Where to start from: Demo (... on the fast-track to AI) ○ AI assets or unsolved problems (that’s the question!)
  3. 3. Copyright Inventurist 2018 Introduction 3 Venture with Confidence Mentor to AI Startups AI for Automation of Business Processes Chief AI Architect ‘Million AI Startups’ AI for Automation of Engineering Design Ph.D. AI for Automation of Engineering Design AI for Automation of Design & Manufacturing Vision: AI will make the world a better place! Mission: Automate Product Innovation Cirrus Shakeri, Ph.D. Founder & CEO-CTO Inventurist
  4. 4. Copyright Inventurist 2018 What is AI? 4 “Elephant in the dark”
  5. 5. Copyright Inventurist 2018 What is AI? 5 Data Storage Cost Computing Cost Cloud Computing Big Data Machine Learning Sensor Networks The Internet RoboticsDeep Learning *
  6. 6. Copyright Inventurist 2018 AI Big Benefits and Big Challenges 6 Benefits ● New solutions for old problems ● Exponential innovation and growth ● The AI hype! Challenges ● Complex technologies ● Shortage of expertise ● The AI hype!
  7. 7. Copyright Inventurist 2018 Benefits: AI Economic and Social Impact 7
  8. 8. Copyright Inventurist 2018 8 Benefits: Bigger than Mobile AI-First Activation of knowledge Increase the capacity to act
  9. 9. Copyright Inventurist 2018 AI will be bigger than Internet 9 ● Progress in AI technologies is real but expectations are hyped beyond realm of possibility ○ De-Risk and validate new AI products before investing time and resources ● Turning AI technologies into solutions that make a business impact is not trivial ○ Internal R&D and external consulting are high risk and high cost approaches - now there is a better alternative ● Structured and machine-driven guidance is the right approach for successful commercialization of AI ○ Inventurist platform automates discovery and validation of new AI products for generating growth & new revenue … if it’s done right!
  10. 10. Copyright Inventurist 2018 Challenge: Shortage of AI Expertise 10
  11. 11. Copyright Inventurist 2018 11 Shortage of Expertise? … Automate it!
  12. 12. Copyright Inventurist 2018 Approach AI Methodically 12 ○ AI Product Engineering ○ It’s a marathon not a sprint! → the grind of product-market fit
  13. 13. Copyright Inventurist 2018 What does methodical mean? A framework, a process, the steps, best practices, ... Know where to start from and when to stop how to validate and measure progress Methodical vs. what? vs. chaotic, random, gut-feeling, purely intuitive, ... Engineering vs. craftsmanship But being methodical is hard! Good news: AI can help! 13
  14. 14. Copyright Inventurist 2018 Data Assets Data Ingestion AI Models Machine Reasoning Machine Intelligence Web Content (web sites, blogs, …) Predict (demand, inventory, …) Learning from Usage Patterns Semantic Inferencing Social Networks (twitter, Facebook, …) Enterprise Apps (ERP, CRM, …) Internet of Things (sensor data, device data, …) Textual Content (documents, reports, …) Online Activities (search, shopping, …) Knowledge-bases (taxonomies, ontologies, …) Data Preparation • Data integration • Data enrichment • Data imputation • Data versioning • Data provenance • … Natural Language Processing • Entity extraction • Entity resolution • Relationship extraction • Taxonomy generation • Knowledge based population (slot filling) • … Context Engine Sensemaking Engine Semantic Search Machine Learning (classification, clustering, anomaly detection, …) Design (product, process, …) Analyze (performance, problem, …) Detect (incident, anomaly, opportunity, …) Find (people, content, …) Discover (insight, pattern, …) Compare (products, companies,, …) Processes (process logs, server logs, …) Automated Update Cycle Rule Engine Process Automation Engine Semantic Query Engine Inference Engine Network of: people, places, organizations, processes, rules, policies, events, documents, devices, … Recommendation Engine …… … Inventurist Methodical Approach: AI Product Engineering AIInnovations 14 *
  15. 15. Copyright Inventurist 2018 Inventurist Methodical Approach: End-to-End Product Design 15 BusinessModel Product Customers Team Financials Product-MarketFit *
  16. 16. Copyright Inventurist 2018 16 Inventurist Platform implements AI Product Engineering
  17. 17. Copyright Inventurist 2018 The Case for AI Product Engineering 17 “software will automate software, automation will automate automation” "... we can develop systematic and repeatable processes to initiate and pursue new AI opportunities." “It’s software that empowers the fundamental process of decision making, capital allocation and risk management, which needs to evolve to support investing at scale, at high velocity yet at repeatedly high rates of return.”
  18. 18. Copyright Inventurist 2018 Impacts of AI Product Engineering 18 Uncovers hidden opportunities that could not be explored manually Discovers new AI solutions with fraction of cost and time Minimizes risk of complex AI technologies by recommending best-of-breed vendors Leads to Exponential Innovation AI that builds other AIs Computer Aided Engineering (CAE)
  19. 19. Copyright Inventurist 2018 Tools Can Help! (to be methodical) Inventurist AI Product Design Platform 19 Internal & External Data AI Product Blueprint
  20. 20. Copyright Inventurist 2018 Inventurist AI Product Design Platform automates AI Innovation 20 It automatically spots and recommends emerging new AI technologies that can potentially apply to Inventurist customers based on their industry and current or targeted markets segments. It automatically spots and recommends emerging new AI technologies that can potentially apply to Inventurist customers based on their industry and current or targeted markets segments. It automatically spots and recommends emerging new AI technologies that can potentially apply to Inventurist customers based on their industry and current or targeted markets segments. It automatically spots and recommends emerging new AI technologies that can potentially apply to Inventurist customers based on their industry and current or targeted markets segments. It automatically spots and recommends emerging new AI technologies that can potentially apply to Inventurist customers based on their industry and current or targeted markets segments. It automatically spots and recommends emerging new AI technologies that can potentially apply to Inventurist customers based on their industry and current or targeted markets segments. It automatically spots and recommends emerging new AI technologies that can potentially apply to Inventurist customers based on their industry and current or targeted markets segments.
  21. 21. Copyright Inventurist 2018 Who can benefit from AI Product Engineering? ● Transportation ● Infrastructure ● Construction ● Manufacturing ● Supply Chain ● Automotive ● Aerospace ● Healthcare ● Airline ● ... 21 Product Executives Innovation Executives Strategy Executives Technology Executives ... Mid-market companies in established industries
  22. 22. Copyright Inventurist 2018 Where to start from? from AI assets or unsolved problems? 22 Case Study: Intelligent Traffic Light
  23. 23. Copyright Inventurist 2018 Live Demo 23
  24. 24. Copyright Inventurist 2018 Conclusions: Fast-Track AI Innovations based on AI Product Engineering Discover growth potential for your business based on AI Analyze and predict the ROI of AI Drive AI innovation based on specific KPIs Validate AI product roadmaps Track and respond to competition Select the best AI technologies and vendors Figure out how to execute on company-level mandate to adopt AI 24
  25. 25. Copyright Inventurist 2018 Inventurist Core Team Cirrus Shakeri, Ph.D., CEO-CTO ● 20 years in Artificial Intelligence ● Enterprise Process Automation ● Manufacturing, Aerospace, Automotive ● Startup advisor ● SAP, Dassault Systemes 25 Ondrej Jaura, Ph.D., Chief Architect ● Artificial Intelligence ● Semantic Technologies and Knowledge Graph ● Customer support Automation (SAP) ● Banking and Financial industry ● Python, Java Gil Heydari, MBA, COO- CAO ● Electrical Engineering & Control System ● Sales and Marketing for High Tech companies ● 22+ Years of experience in Public & Startups company ● Angel investors ● Ericson Zoltán Galáž, Ph.D., Data Scientist ● Ph.D. Candidate, Brno University ● Big Data and Machine Learning ● Signal Processing ● Matlab, C, Python Maria Grancicova, Innovation Analyst ● Startup analysis, Team Lead ● Technology trend analysis ● Market research ● Law and legal ● Government and contracts Engineering Team: Prof Mohammad Noori, Ph.D. ● Chairman of Advisory Board, Inventurist Joint Venture in Intelligent Infrastructure Systems ● Professor of Mechanical Engineering at Cal Poly, San Luis Obispo, CA http://www.patronous.com
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