How to prepare data for LLMs
Key Takeaways
Preparing data for LLMs to ensure quality and security
Original Description
How can developers prepare data for usage in a large language model (LLM)? How can developers ensure sensitive data is not accidentally passed around? Join Googlers Aja Hammerly and Jason Davenport as they have a technical discussion about data’s impact on LLM quality and security. Watch along and Aja and Jason share their methods for solving data problems for building applications that use LLMs.
Chapters:
0:00 - Data considerations for LLMs
2:00 - Data residency/sovereignty requirements
3:10 - Data sensitivity considerations
4:40 - Controlling input/output data in LLMs
6:57 - Conclusion
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Speakers: Aja Hammerly, Jason Davenport
Products Mentioned: Gemma, Gemini
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Chapters (5)
Data considerations for LLMs
2:00
Data residency/sovereignty requirements
3:10
Data sensitivity considerations
4:40
Controlling input/output data in LLMs
6:57
Conclusion
🎓
Tutor Explanation
DeepCamp AI