industrial ai - web.stanford.edu
TRANSCRIPT
/SLAC
Industrial AIee392b Seminar Overview
Dimitry Gorinevsky
Consulting Professor in Electrical Engineering
www.stanford.edu/~gorin
March 31, 2021
/SLACStanford
Class Topic: Industrial AI Big Picture
• What do companies mean when they hire AI engineers?• Why are companies compelled to do AI?• What is the outcome they expect?• What are the real issues there?
March 2021 © D. Gorinevsky: www.stanford.edu/~gorin 2
/SLACStanford
DIGITAL TRANSFORMATION
March 2021 © D. Gorinevsky: www.stanford.edu/~gorin 3
/SLACStanford
Digital Transformation
• Digital Transformation• Software is eating the world• Digital technology transforms all areas of economy
– Internet of People (IoP)– Internet of Things (IoT)– Business Processes
March 2021 © D. Gorinevsky: www.stanford.edu/~gorin 4
/SLACStanford
Analytics Applications
• Much of software business is in data management platforms
• Added value comes from business process changes driven by applications
March 2021 © D. Gorinevsky: www.stanford.edu/~gorin 5
www.forbes.com/sites/cognitiveworld/2019/08/29/software-ate-the-world-now-ai-is-eating-software/?sh=7ffaefab5810
/SLACStanford
Analytics in Industry
• Business Intelligence (BI)– Spreadsheets
• Data Science– Exploratory analysis services
• AI – Automated applications
March 2021 © D. Gorinevsky: www.stanford.edu/~gorin 6In
tegr
atio
n Scaled to Big Data
Descriptive analytics
Predictive analytics
Prescriptive analytics
/SLACStanford
Industrial AI in Digital Transformation
March 2021 © D. Gorinevsky: www.stanford.edu/~gorin 7
Data from Things
Analytical Applications
Industrial AI
Data from People
/SLACStanford
Digital Transformation and Industrial Revolution
• Industry 4.0 – 4th Industrial Revolution – Manufacturing: Data from Machines and Processes
March 2021 © D. Gorinevsky: www.stanford.edu/~gorin 8
/SLACStanford
Digital Transformation with Data From Things
• Smart Cities, Smart Buildings, Smart Homes• Industrial IoT (includes Industry 4.0, Smart Cities, and more)
– Smart Grid – Supply Chains – Transportation (Cars, Planes, Trains)
• More… – Insurance
• Data Centers and IT Systems (AI Ops)
March 2021 © D. Gorinevsky: www.stanford.edu/~gorin 9
/SLACStanford
INDUSTRIAL AI APPLICATIONS
March 2021 © D. Gorinevsky: www.stanford.edu/~gorin 10
/SLACStanford
What is Special about Industrial AI?
• Mission Critical Analytics – Explainable AI – Digital Twins models – Verification and validation processes, engineering rigor
• E.g., Tesla, Waymo
• Automated Data-driven Apps– Scalable, reduced deployment effort– Broaden access to the benefits of advanced analytics
March 2021 © D. Gorinevsky: www.stanford.edu/~gorin 11
/SLACStanford
Mission Critical Analytics
March 2021 © D. Gorinevsky: www.stanford.edu/~gorin 12
WebAdvertising
0.3%
High-freqTrading
51%
Industrial AIDecision Support
95%
Machine Learning/AIData Science
Control SystemsRocket Science
99.9999%
CivilAviation
PowerSystems
99.97% generality, fast development | reliability, accuracy
CS ENG
IT OTIoP IoT
AI Ops
/SLACStanford
Computing Platform: IT/OT Convergence
March 2021 © D. Gorinevsky: www.stanford.edu/~gorin 13
↑↓
• IT: Enterprise computing. Cloud. Information Technology
Operational Technology
Edge
Device
Cloud IT
• OT: Industrial systems. Secure, closed networks.
Edge computing. Fog.
OT
/SLACStanford
INDUSTRIAL AI AT STANFORD
March 2021 © D. Gorinevsky: www.stanford.edu/~gorin 14
/SLACStanford
Analytics Domains
March 2021 © D. Gorinevsky: www.stanford.edu/~gorin 15
IT
Embedded
↑
↑
↑
Engineering MethodsModeling & Simulation
Rigorous Analysis
Operations Research
Industrial AIMission Critical, Explainable
Decision and Control
Signal Processing
Data-Driven MethodsStatistics and
Machine Learning
Disciplines Methodology
IIoT Persistent Data
OT (Operational Technology)
/SLACStanford
Industrial AI Initiative
Rigorous Algorithms IndustrialMission Critical ApplicationsData Driven Modeling AI At Scale Deployment
March 2021 © D. Gorinevsky: www.stanford.edu/~gorin 16
Industrial AIData from ‘Things’
Mission Critical Applications
At Scale Deployment
StanfordIndustrial
AIInitiative
StanfordRigorous Analysis and Provable Algorithms
Data-Driven Modeling and Optimization
https://iai.stanford.edu
/SLACStanford
IMPORTANT USE CASES
March 2021 © D. Gorinevsky: www.stanford.edu/~gorin 17
/SLACStanford
Digital Transformation of Operations and Support
• Engineering and manufacturing – 10-15% of the lifecycle cost
• Operations and supply chains– 65-80% of the lifecycle cost
March 2021 © D. Gorinevsky: www.stanford.edu/~gorin 18
DoD CBM+
/SLACStanford
AIOps
• AI for IT Operations • Computing center as an industrial plant• Control plane provides ‘OT’• Tech Industry
– Much more dynamic than traditional industries
March 2021 © D. Gorinevsky: www.stanford.edu/~gorin 19
/SLACStanford
SYLLABUS
March 2021 © D. Gorinevsky: www.stanford.edu/~gorin 20
/SLACStanford
Planned Lectures
March 31, Introductory LectureApril 7, Industrial Enterprise, HitachiApril 14, AIOps, AlibabaApril 21, VC, GreylockApril 28, Consulting, Accenture (panel)May 5, VC, The Robotics HubMay 12, AIOps, GoogleMay 19, AIOps, MicrosoftMay 26, AI Technology, AspenJune 2, Consulting, Deloitte (panel)
March 2021 © D. Gorinevsky: www.stanford.edu/~gorin 21
/SLACStanford
GreylockVC
I-AI Lecture Map
March 2021 © D. Gorinevsky: www.stanford.edu/~gorin 22
Industrial AI
AIOps
Technology Business Enterprise
Alibaba
HitachiRobotics
HubVC
Microsoft
Deloitte
Aspen Tech
Accenture