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AI in manufacturing - a technical perspective


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AI in Manufacturing – a Technical Perspective (#AIFightsBack series)

Presented by Steph Locke, CEO @ Nightingale HQ
T: @theStephLocke
Li: /stephanielocke

- Overview of AI: AI performs “cognitive” tasks
- Key areas of AI
+ Machine learning & data science
+ Robots may be AI
- AI & ML: What techniques are we most likely to use?
+ Core AI tasks
+ Computer vision
+ Speech
+ Language
+ Core ML tasks
+ Classification
+ Common classification methods
+ Decision trees: Identify ways to split data to get cleanest outcome groups
+ Regression: Predicts the chances of something happening
+ Neural networks: Uses multiple iterations to predict the chances
+ Anomaly detection
+ Anomaly detection types
+ Point anomalies: Unusual inside the whole dataset
+ Contextual anomalies: Unusual compared to neighbouring values
+ Collective anomalies: Connected records that are unusual
+ Patterns
+ K-means clustering: Group records based on “distance”
+ Hierarchical clustering: A multi-level grouping of records
+ Associations: Identify co-occurrences and correlations
- Critical infrastructure: What do we need to have in place?
+ Data
+ Data lake
- Conclusion
+ What should I do next?
+ Key areas of AI
+ The process

- 7 Quick-win AI Projects paper Quick Wins/7 Quick Win AI Projects-1.pdf
- AI in Manufacturing article
- More AI in manufacturing webinars
- McKinsey on the future of pharma QC
- Otis ONE
- ZEISS investment
- Amgen manufacturing deviation
- Edera Safety with Autodesk
- Speedy Hire inventory management

Published in: Technology
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