making ai production-ready · • data-focused tech career started in 1985. ai beyond the...
TRANSCRIPT
Andy Cross
COO & co-owner, Elastacloud
With host Andrew Brust
Market Strategy Advisor, Io-Tahoe
CEO, Blue Badge Insights
Making AI
Production-Ready
For external use
Speaker bios
2
Andy Cross
• Chief Operating Officer, Elastacloud
• Background as developer, consultant
• Influencer
Andrew Brust
• Covers Big Data and analytics for ZDNet
• Strategy Advisor to Io-Tahoe
• Data-focused tech career started in 1985
AI beyond the laboratory
How are AI and ML used in industry,
beyond pilots and experimental
contexts?
3
For external use
“Gee Whiz” vs. Production
4
Gee Whiz
• New features, libraries, frameworks
• Innovations, disruption, standards be damned?
Production
• Methodology
• Repeatability
• Manageability
For external use
A differentiated approach
5
Detached
Primitive tooling
Data scientist builds model,
hands it off, withdraws
Mutual lack of understanding
between data scientists and
developers
Coordinated
Working in tandem
Design and deployment
considerations balanced
Mutual empathy
For external use
Best Practices
Data Engineer:
owns cloud
account, pushes
model to
production
Data Scientist
does research
Work in tandem Like pair programming
6
For external use
Production Considerations
7
Model Management
Deployment
Retraining
Make scoring easy for
developers
Apache Spark
Notebooks
Python vs. R
Technologies
Core Platform vs.
peripheral technologies
Old role, new
responsibilities (e.g. DBA
in charge of model
management)
Approach
For external use
AI and Data
Management
Thank you
9
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