Artificial Intelligence Reloaded - AI Apps in the Industry
summary
ThoughtWorks describes concrete industry work: data ingestion from SAP, POS and cloud sources, cleaning and feature engineering for forecasting and classification, then deploying models into Java-based production via automated pipelines. Examples include a retail demand-forecast model, an Austria real-estate estimator that combines multiple CNNs to predict bedrooms and price, an AdWorx Rasa-based dialog stack, and AutoScout price models moved from Random Forest training to production with automated validation. Emphasis on data lake is not a silver bullet, continuous intelligence, and DVC-style versioning for reproducible models.
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chapters (11)
- 0:00AI in industrial apps
- 3:58AI to production challenges
- 6:29Industrial AI requirements
- 9:49Data governance in AI
- 14:31Data to insights
- 17:48Continuous intelligence role
- 22:31AI models building blocks
- 27:41Natural language processing in AI applications
- 32:18CD for AI systems
- 39:06Version control for AI
- 41:20Research to production
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