Responsible Applied AI at Scale
summary
Starts with the claim 90% of AI projects fail and then gives concrete evidence: production models that grow from ~100 to 2.3–2.4 billion inferences/month, a developer who ships 100+ Alexa skills with ~2 million users, a computer-vision prototype trained on 21 images, and a case that boosts engineer productivity ~780%. Names actual tools and APIs (Alexa, AWS, Microsoft cognitive services, BigQuery, OpenAI/Codex, GitHub Copilot) and describes what was built, how it scaled, and which metrics changed.
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chapters (9)
- 0:00Start
- 6:39Mvp for Microsoft
- 10:28What Is Success
- 19:13Multimodal Building
- 21:01Open Ai
- 30:24Accessibility
- 30:41Computer Vision
- 33:16Translation
- 34:05Conversational Ai
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