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Introducing layered ranking for RAG applications
Introducing layered ranking: The missing piece for context engineering at scale.
Perplexity builds AI Search at scale on Vespa.ai
Perplexity chose to build on Vespa.ai to provide the world's most used RAG application.
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Created by NanoBanana
Embedding Tradeoffs, Quantified
The embedding strategy you choose has a major impact on both cost, quality and latency. We ran a bunch of experiments to help you make better and more informed tradeoffs....
Image from thinkhubstudio on Shutterstock.
How Tensors Are Changing Search in Life Sciences
Tensor-based retrieval preserves context across queries, maintains "chain of thought" and ranking relevance of multiple scientific factors simultaneously.
Image from Golden Dayz on Shutterstock.
The Search API Reset: Incumbents Retreat, Innovators Step Up
Google and Bing are restricting their search APIs, creating opportunities for new players to build the next generation of search infrastructure.
Image from Gerd Altmann from Pixabay.
Enterprise AI Search vs. the Real Needs of Customer-Facing Apps
Customer-facing AI search must optimize for low-latency relevance, responsiveness and personalization rather than compliance with internal policies.
Image from Gerd Altmann on Pixabay.
Eliminating the Precision–Latency Trade-Off in Large-Scale RAG
A look at three techniques that together eliminate this trade-off: multiphase ranking, layered retrieval and semantic chunking.
Image from Overearth on Shutterstock.
Why AI Search Platforms Are Gaining Attention
Users expect search not just to return accurate results, but to do the heavy lifting: Answer a question, summarize research, or even solve a problem.
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Ashraful Islam
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Why Life Sciences AI Is a Search Problem (Part 5 of 5)
The future of GenAI in pharma and healthcare isn’t about building bigger models — it’s about smarter retrieval.
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Ousa Chea
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Why Life Sciences AI Is a Search Problem (Part 4 of 5)
The future of GenAI in pharma and healthcare isn’t about building bigger models — it’s about smarter retrieval.
Vespa Newsletter, December 2025
Advances in Vespa features and performance include automated ANN tuning, accelerated vector distance calculations with Google Highway, precise chunk-level matching with enhanced sameElement, and expressive proximity queries with nested NEAR...
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National Cancer Institute
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Why Life Sciences AI Is a Search Problem (Part 3 of 5)
The future of GenAI in pharma and healthcare isn’t about building bigger models — it’s about smarter retrieval.
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CHUTTERSNAP
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Why Life Sciences AI Is a Search Problem (Part 2 of 5)
The future of GenAI in pharma and healthcare isn't about building bigger models - it's about smarter retrieval.
Photo by
Louis Reed
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Why Life Sciences AI Is a Search Problem (Part 1 of 5)
The future of GenAI in pharma and healthcare isn't about building bigger models - it's about smarter retrieval.
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