1 option
Observability for large language models : understanding and improving your use of LLMs / Phillip Carter.
- Format:
- Book
- Author/Creator:
- Carter, Phillip, author.
- Language:
- English
- Subjects (All):
- Natural language processing (Computer science).
- Artificial intelligence.
- Observers (Control theory).
- Physical Description:
- 1 online resource (33 pages)
- Edition:
- First edition.
- Place of Publication:
- Sebastopol, CA : O'Reilly Media, Inc., 2023.
- Summary:
- An initial release of a large language model (LLM) makes for a nice marketing moment, but value lies in the work you do to make something a true "1.0"-level product experience. In this report, Phillip Carter, who spearheads AI initiatives at Honeycomb, provides an introduction to using observability tools and practices that will help you improve modern LLM and AI products after they've been released. MLOps professionals, SREs, software engineers, developers, and architects will learn not only the importance of OpenTelemetry, but also the methods of feeding observability data back into development. This report is also ideal for CTOs and other senior-level practitioners in your organization.
- Notes:
- OCLC-licensed vendor bibliographic record.
- ISBN:
- 9781098159757
- 1098159756
- OCLC:
- 1401631997
The Penn Libraries is committed to describing library materials using current, accurate, and responsible language. If you discover outdated or inaccurate language, please fill out this feedback form to report it and suggest alternative language.