Not Everything That Glitters Is Generative AI
summary
Discusses practical limits of large language models like ChatGPT-4 for specialized tasks, focusing on the gap between expectations and reality when building applications with these models. Covers the engineering and coordination effort required—communication, many expert contributors—and shares lessons learned about what worked well and what problems arose.
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chapters (15)
- 0:00Introduction
- 1:48Generative AI rise
- 3:09Failed generative AI project
- 8:04Redesign and access issues
- 10:14Delivery without feedback
- 11:58Technical success hidden costs
- 13:04Human experimentation failure
- 14:51Human responsibility in AI
- 16:16Data quality question
- 17:20AI failure examples
- 18:44Data governance importance
- 20:13Q&A
- 20:57Generative AI bubble?
- 22:26Real use cases
- 23:50Linear regression vs complex models
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