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.

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

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Outline of the Talk
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● 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!)

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Introduction
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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

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What is AI?
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“Elephant in the dark”

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What is AI?
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Data Storage Cost
Computing Cost
Cloud Computing Big Data
Machine Learning Sensor Networks
The Internet
RoboticsDeep Learning
*

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AI Big Benefits and Big Challenges
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Benefits
● New solutions for old problems
● Exponential innovation and growth
● The AI hype!
Challenges
● Complex technologies
● Shortage of expertise
● The AI hype!

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Benefits: AI Economic and Social Impact
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Benefits: Bigger than Mobile
AI-First
Activation of knowledge
Increase the capacity to act

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AI will be bigger than Internet
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● 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!

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Challenge: Shortage of AI Expertise
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Shortage of Expertise? … Automate it!

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Approach AI Methodically
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○ AI Product Engineering
○ It’s a marathon not a sprint!
→ the grind of product-market fit

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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!
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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
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*

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Inventurist Methodical Approach: End-to-End Product Design
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BusinessModel
Product
Customers
Team
Financials
Product-MarketFit
*

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Inventurist Platform implements AI Product Engineering

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The Case for AI Product Engineering
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“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.”

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Impacts of AI Product Engineering
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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)

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Tools Can Help!
(to be methodical)
Inventurist AI Product Design Platform
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Internal &
External
Data
AI Product
Blueprint

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Inventurist AI Product Design Platform automates AI Innovation
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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.

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Who can benefit from AI Product Engineering?
● Transportation
● Infrastructure
● Construction
● Manufacturing
● Supply Chain
● Automotive
● Aerospace
● Healthcare
● Airline
● ...
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Product Executives
Innovation Executives
Strategy Executives
Technology Executives
...
Mid-market companies in established industries

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Where to start from?
from AI assets or unsolved problems?
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Case Study: Intelligent Traffic Light

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Live Demo
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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
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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
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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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