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Vectorize Your Open Source Search Engine

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Vectorize Your Open Source Search Engine
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CC Attribution 3.0 Unported:
You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal purpose as long as the work is attributed to the author in the manner specified by the author or licensor.
Release Date2023

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Neural search (a.k.a. Vector search) has rewritten the standards of information retrieval in many different domains. Vector search can help you gather a better understanding of the user query intent, drive product recommendations, search across different source data (text, images, audio, video), deliver better results, improve personalization and create a more successful user experience. Vector search goes beyond keywords to harvest the potential of graphs and embeddings to match users to the intended document, product, job, picture, song, or video. As fascinating as this may sound it's easy to find ourselves lost in the deluge of new information. If you're struggling to get started, understand what vector search can bring to the party, add cool new models such as OpenAI models and want to avoid common pitfalls, this talk is for you.