Scaling Search and Retrieval for Contextual AI
From Data Structures to Distributed Systems
$134.74
- Paperback
350 pages
- Release Date
2 February 2027
Summary
AI models are only as good as the context they can retrieve. Without the right data at the right moment, even the most powerful models fail. You might even say that search and retrieval is the most important layer of the AI stack.
Scaling Search and Retrieval for Contextual AI is your guide to designing modern search infrastructure for contextual AI. Written by Nicholas Knize, the creator of AWS OpenSearch, this book explores the full lifecycle of search systems–from indexing…
Book Details
| ISBN-13: | 9798341669017 |
|---|---|
| Author: | Nicholas Knize |
| Publisher: | O'Reilly Media |
| Imprint: | O'Reilly Media |
| Format: | Paperback |
| Number of Pages: | 350 |
| Release Date: | 2 February 2027 |
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Nicholas Knize
Nicholas is a leading authority in search and retrieval systems. He is the Founder and CEO of Lucenia, which provides cost-effective Hybrid Search solutions that cut cloud costs by over 40% and prevent vendor lock-in.
Previously, Nicholas was a Principal Engineer for Amazon Search Services, where he created AWS OpenSearch. As the Geospatial Lead at Elastic, he was a key contributor to Elasticsearch and served as a Lucene Committer and PMC member. He also held the position of Chief Scientist at Thermopylae Sciences and Technology, where he invented XTree Hyperspatial indexing.
Nicholas holds seven patents and a trade secret, and has received multiple accolades, including the Corporate Excellence in Engineering Technology Individual Award. His work encompasses his professional career and personal projects such as SocialEyez TV for Google TV 2.0. His expertise lies in spatial indexing, distributed computing, and mobile technologies, demonstrating his significant impact on modern data systems.
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