Full Stack Neural Search

Henry AI Labs · Beginner ·🔍 RAG & Vector Search ·4y ago

Skills: RAG Basics90%

Key Takeaways

The video discusses Full Stack Neural Search, covering preprocessing, granularity of embeddings, and enabling different search applications, with references to Jina AI and Weaviate.

Original Description

This video explains one of the biggest lessons for me in interviewing Han Xiao from Jina AI. I hope this was a good explanation of the preprocessing / granularity of embeddings and how that can enable different kinds of search applications. Full-Length Podcast: https://www.youtube.com/watch?v=HIGAQAE_xaI Code Tutorial (Weaviate + Jina AI for Image Search): https://www.youtube.com/watch?v=rBKvoIGihnY Please check out Jina AI on YouTube: https://www.youtube.com/c/JinaAI Please check out SeMI Technologies on YouTube: https://www.youtube.com/c/SeMI-and-Weaviate/videos Chapters 0:00 Please check out SeMI YouTube! 0:15 My takeaways on Full Stack Neural Search 11:04 Podcast Clip - Han Xiao

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This video explains the basics of Full Stack Neural Search, covering key concepts such as preprocessing, embeddings, and search applications. It provides valuable insights from an interview with Han Xiao from Jina AI. By watching this video, viewers can gain a better understanding of how to build and optimize neural search systems.

Key Takeaways

Understand the basics of neural search
Learn about preprocessing techniques
Implement embedding granularity optimization
Explore search applications using Jina AI and Weaviate
Check out additional resources on SeMI Technologies and Jina AI YouTube channels

💡 Preprocessing and embedding granularity are crucial for enabling different kinds of search applications in Full Stack Neural Search.

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Chapters (3)

Please check out SeMI YouTube!

0:15 My takeaways on Full Stack Neural Search

11:04 Podcast Clip - Han Xiao

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