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Dr June Andrews
Principal Data Scientist
Counter Intuitive Machine Learning
for the Industrial Internet of Things
First Define Intuitive Machine Learning Product Development.
… bit more of an art than a science.
Ellsworth Kelly
Optimize and refine products by cycling multiple times with improvements.
Machine Learning Product Development Cycle - Pha...
Plan
Source
Ideas
Good companies
make good
decisions. Great
companies forgo
good decisions to
make great ones. 

Proper pl...
Plan
Build
Source
Ideas
Building &
Optimizing models
is largely a solved
problem.

Identify & prioritize
unsolved problems...
Plan
BuildTest
Source
Ideas
Testing should
match the diversity
of the user base &
the gravity of the
ML Product’s
responsi...
Plan
BuildTest
Learn
Source
Ideas
Take the time to
learn.

Small changes in
complex
environments often
reveal cascading
ef...
Plan
BuildTest
Learn
Release
Source
Ideas
Model life
expectancy is
increasing.

Model Robustness
should follow.
Prioritize...
Plan
BuildTest
Learn
Release
Source
Ideas
All stages should
be addressed, even
if they are skipped.

A modification to
an ...
Source
Ideas
Each stage may
involve input from
many roles including
users & customers,
but each stage should
have an Owner...
Plan
BuildTest
Learn
Release
Source
Ideas
Platforms will
automate many
stages & focus
efforts on stages
that yield a
compe...
What is Counter-Intuitive about Industrial Internet of Things?
…research is driven by need based innovations.
Context. Pro...
The Industrial Internet of Things Connects Power, Engines & People
1/3 of the World’s Power is Generated by GE.
60% of Air...
ML + IIoT Involves an Ongoing Negotiation to Figure Out What is Possible
Done: Real Time In Production Service Suggesting ...
Aviation: History of Innovation & Excellence
Best Practices & Decision Design has Evolved over 15+ Years of Monitoring Fle...
New Workflow Preserves Baseline Reliability with Increasing Speed & Accuracy
Delivered an Augmented Human Interpretable Mo...
Plan
BuildTest
Learn
Release
Source
Ideas
Compliance with
regulations &
customer
agreements is a
competitive
advantage.
Pr...
Global Domination
is not the top line
goal.

Safety, Reliability &
Efficiency are.
IIoT Counter-Intuitive*
Plan
BuildTest
...
Plan
BuildTest
Learn
Release
Source
Ideas
Big Data, but

not infinite &

not cheap.

Take the time,

to be clever.
Priorit...
Machine Learning Experts Transform Domain Knowledge into Model Inputs
Aviation Experts are a Strategic Advantage in IIoT
Turing Test, tests a mastery of communication.
Bob Test, tests a master of communication, data synthesis & problem solving...
5 Months to Augment Aviation — Eta 2 Months to Augment Power
First Order Effects are When Innovations for Planes Help Plan...
To Dive Deeper Visit the Wise.io Booth
/DrAndrews
Thank You
Competitive Machine Learning Requires Strategic Talent Contributions
Augmenting Fleet Monitor was an Orchestration of Alig...
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Dr. June Andrews, Principal Data Scientist, Wise.io, From GE Digital at MLconf SF 2017

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Counter Intuitive Machine Learning for the Industrial Internet of Things:
The Industrial Internet of Things (IIoT) is the infrastructure and data flow built around the world’s most valuable things like airplane engines, medical scanners, nuclear power plants, and oil pipelines. These machines and systems require far greater uptime, security, governance, and regulation than the IoT landscape based around consumer activity. In the IIoT the cost of being wrong can be the catastrophic loss of life on a massive scale. Nevertheless, given the growing scale through the digitalization of industrial assets, there is clearly a growing role for machine learning to help augment and automate human decision making. It is against this backdrop that traditional machine learning techniques must be adapted and need based innovations created. We see industrial machine learning as distinct from consumer machine learning and in this talk we will cover the counterintuitive changes of featurization, metrics for model performance, and human-in-the-loop design changes for using machine learning in an industrial environment.

Bio: June Andrews is a Principal Data Scientist at Wise.io, From GE Digital working on a machine learning and data science platform for the Industrial Internet of Things, which includes aviation, trains, and power plants. Previously, she worked at Pinterest spearheading the Data Trustworthiness and Signals Program to create a healthy data ecosystem for machine learning. She has also lead efforts at LinkedIn on growth, engagement, and social network analysis to increase economic opportunity for professionals. June holds degrees in applied mathematics, computer science, and electrical engineering from UC Berkeley and Cornell.

Veröffentlicht in: Technologie
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Dr. June Andrews, Principal Data Scientist, Wise.io, From GE Digital at MLconf SF 2017

  1. 1. Dr June Andrews Principal Data Scientist Counter Intuitive Machine Learning for the Industrial Internet of Things
  2. 2. First Define Intuitive Machine Learning Product Development. … bit more of an art than a science. Ellsworth Kelly
  3. 3. Optimize and refine products by cycling multiple times with improvements. Machine Learning Product Development Cycle - Phases Extending Boehm Spiral Model from Software Engineering Plan BuildTest Learn Release
  4. 4. Plan Source Ideas Good companies make good decisions. Great companies forgo good decisions to make great ones. Proper planning leads to efficiently executing great ideas. Prioritize Define Success Design Roadmap
  5. 5. Plan Build Source Ideas Building & Optimizing models is largely a solved problem. Identify & prioritize unsolved problems early on. Prioritize Define Success Design Roadmap Find & ETL Data Feature Engineer Build & Train Optimize
  6. 6. Plan BuildTest Source Ideas Testing should match the diversity of the user base & the gravity of the ML Product’s responsibility. Prioritize Define Success Design Roadmap Find & ETL Data Feature Engineer Productionize A/B Test Build & Train OptimizeEvaluateDog Food
  7. 7. Plan BuildTest Learn Source Ideas Take the time to learn. Small changes in complex environments often reveal cascading effects. Prioritize Define Success Design Roadmap Find & ETL Data Feature Engineer Productionize A/B Test Analyze Product Review Build & Train OptimizeEvaluateDog Food Evangelize
  8. 8. Plan BuildTest Learn Release Source Ideas Model life expectancy is increasing. Model Robustness should follow. Prioritize Define Success Design Roadmap Find & ETL Data Feature Engineer Productionize A/B Test Analyze Product Review Build & Train OptimizeEvaluateDog Food Evangelize Release 100% Retrain & Maintain
  9. 9. Plan BuildTest Learn Release Source Ideas All stages should be addressed, even if they are skipped. A modification to an upstream stage triggers changes to all downstream stages. Prioritize Define Success Design Roadmap Find & ETL Data Feature Engineer Productionize A/B Test Analyze Product Review Release 100% Retrain & Maintain Build & Train OptimizeEvaluateDog Food Evangelize
  10. 10. Source Ideas Each stage may involve input from many roles including users & customers, but each stage should have an Owner. Who owns Prioritize is a reflection of {Product, Data, Engineering, Design}- Driven Companies. Prioritize Define Success Design Roadmap Find & ETL Data Feature Engineer Productionize A/B Test Analyze Product Review Release 100% Retrain & Maintain Build & Train OptimizeEvaluateDog Food Evangelize Product Data Science Data Engineering ML Engineering Software Engineering Per Company
  11. 11. Plan BuildTest Learn Release Source Ideas Platforms will automate many stages & focus efforts on stages that yield a competitive advantage. Prioritize Define Success Design Roadmap Find & ETL Data Feature Engineer Productionize A/B Test Analyze Product Review Release 100% Retrain & Maintain Build & Train OptimizeEvaluateDog Food Evangelize
  12. 12. What is Counter-Intuitive about Industrial Internet of Things? …research is driven by need based innovations. Context. Process and people are strikingly similar. Context forces changes.
  13. 13. The Industrial Internet of Things Connects Power, Engines & People 1/3 of the World’s Power is Generated by GE. 60% of Airplane Engines are made by GE. … Preventative Maintenance Failure/ Anomaly Detection Assistive Diagnosis & Treatment Systems Optimization
  14. 14. ML + IIoT Involves an Ongoing Negotiation to Figure Out What is Possible Done: Real Time In Production Service Suggesting Actions on Airplane Engine Alerts
  15. 15. Aviation: History of Innovation & Excellence Best Practices & Decision Design has Evolved over 15+ Years of Monitoring Fleets
  16. 16. New Workflow Preserves Baseline Reliability with Increasing Speed & Accuracy Delivered an Augmented Human Interpretable Model
  17. 17. Plan BuildTest Learn Release Source Ideas Compliance with regulations & customer agreements is a competitive advantage. Prioritize Define Success Design Roadmap Find & ETL Data Feature Engineer Productionize A/B Test Analyze Product Review Release 100% Retrain & Maintain Build & Train OptimizeEvaluateDog Food Evangelize IIoT Counter-Intuitive*
  18. 18. Global Domination is not the top line goal. Safety, Reliability & Efficiency are. IIoT Counter-Intuitive* Plan BuildTest Learn Release Source Ideas Prioritize Define Success Design Roadmap Find & ETL Data Feature Engineer Productionize A/B Test Analyze Product Review Release 100% Retrain & Maintain Build & Train OptimizeEvaluateDog Food Evangelize
  19. 19. Plan BuildTest Learn Release Source Ideas Big Data, but not infinite & not cheap. Take the time, to be clever. Prioritize Define Success Design Roadmap Find & ETL Data Feature Engineer Productionize A/B Test Analyze Product Review Release 100% Retrain & Maintain Build & Train OptimizeEvaluateDog Food Evangelize IIoT Counter-Intuitive*
  20. 20. Machine Learning Experts Transform Domain Knowledge into Model Inputs Aviation Experts are a Strategic Advantage in IIoT
  21. 21. Turing Test, tests a mastery of communication. Bob Test, tests a master of communication, data synthesis & problem solving. Challenge to AI - The Bob Test Bob gathers input from the monitoring team, synthesizes the data & calls the airline. Bob works with experts from the airline to determine root cause & design safe plans of action for quick resolution.
  22. 22. 5 Months to Augment Aviation — Eta 2 Months to Augment Power First Order Effects are When Innovations for Planes Help Planes. Second Order Effects are When Innovations for Planes Help Power.
  23. 23. To Dive Deeper Visit the Wise.io Booth /DrAndrews Thank You
  24. 24. Competitive Machine Learning Requires Strategic Talent Contributions Augmenting Fleet Monitor was an Orchestration of Aligning Talents with Needs

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