<?xml version="1.0" encoding="UTF-8"?>
<rss version="2.0" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:wfw="http://wellformedweb.org/CommentAPI/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:sy="http://purl.org/rss/1.0/modules/syndication/" xmlns:slash="http://purl.org/rss/1.0/modules/slash/" xmlns:memo="https://memo.d.foundation/ns/feed/1">
  <channel>
    <title>vector-database - Dwarves Memo</title>
    <atom:link href="https://memo.d.foundation/topics/applied-llm/tags/vector-database/rss.xml" rel="self" type="application/rss+xml" />
    <link>https://memo.d.foundation/topics/applied-llm/tags/vector-database</link>
    <description>The newest notes tagged vector-database on Dwarves Memo.</description>
    <lastBuildDate>Fri, 28 Jun 2024 00:00:00 GMT</lastBuildDate>
    <language>en-US</language>
    <sy:updatePeriod>hourly</sy:updatePeriod>
    <sy:updateFrequency>1</sy:updateFrequency>
    <item>
      <title>Multimodal: in rag</title>
      <link>https://memo.d.foundation/llm/multimodal-in-rag</link>
      <pubDate>Fri, 28 Jun 2024 00:00:00 GMT</pubDate>
      <dc:creator><![CDATA[nnhuyhoang]]></dc:creator>
      <description><![CDATA[In spite of having taken the world by storm, Large Language Models(LLM) still has some limitations such as limited context window and a knowledge cutoff date. Retrieval-Augmented Generation(RAG) steps in to bridge this gap by allowing LLMs to access and utilize external knowledge sources beyond their training data. However, data is not text based only, it also can be image, audio, table in docs,...]]></description>
      <guid isPermaLink="true">https://memo.d.foundation/llm/multimodal-in-rag</guid>
    </item>
    <item>
      <title>Building blocks of a RAG pipeline</title>
      <link>https://memo.d.foundation/llm/rag-building-blocks</link>
      <pubDate>Fri, 09 Jun 2023 00:00:00 GMT</pubDate>
      <dc:creator><![CDATA[zlatanpham]]></dc:creator>
      <description><![CDATA[How chunking, hierarchical tree summaries, re-ranking, query caching and vector-store chat memory fit together around a vector database in an LLM application.]]></description>
      <guid isPermaLink="true">https://memo.d.foundation/llm/rag-building-blocks</guid>
    </item>
    <item>
      <title>Choosing a vector database for LLM applications</title>
      <link>https://memo.d.foundation/llm/select-vector-database-for-llm</link>
      <pubDate>Thu, 18 May 2023 00:00:00 GMT</pubDate>
      <dc:creator><![CDATA[thanhpn]]></dc:creator>
      <description><![CDATA[An overview of vector databases and their application in LLM systems. This article covers the history and core concepts of vector databases, their use cases, implementation considerations with LLMs, and a comparison of popular vector database options.]]></description>
      <guid isPermaLink="true">https://memo.d.foundation/llm/select-vector-database-for-llm</guid>
    </item>
  </channel>
</rss>