AI Owes its Rebirth to Open Source and the Cloud
summary
Argues that open source plus cloud enabled practical AI by showing deployed examples: Rolls‑Royce streams engine telemetry to predict failures and tweak fuel use (airlines spend ~40% of revenue on fuel; avoiding on‑airport part delays saves ~ $1M/day), and a diagnostic pipeline trains on 112,000 chest images (30,000 patients, 14 labels) using DenseNet‑121 with PyTorch and Keras on Azure deep‑learning VMs, publishes code on GitHub and exports models via ONNX for runtime deployment.
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chapters (11)
- 0:00Intro
- 2:06Diagnostic X
- 4:12LinkedIn
- 4:40Whats powering this trend
- 8:02Open Source in ML
- 9:53Why Open Source
- 11:31Data Science Tools
- 12:24Data Science Languages
- 13:06Community
- 14:17Open Source Architecture
- 16:38The Rise of AI ML
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