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Search by Meaning

Blog post from Vectara

Post Details
Company
Date Published
Author
Amr Awadallah
Word Count
1,280
Company Posts That Month
4
Language
English
Hacker News Points
-
Post removed?
No
Summary

The current state of search techniques has been limited by keyword matching, which suffers from semantic loss, making it difficult to capture the true meaning of queries. The advent of natural language understanding via neural networks and large language models (LLMs) has enabled computers to comprehend human language at a high level, leading to advancements in LLM-powered search or Neural Search. This technology uses word vectors, transformers, and BERT to map keywords from human language space to a meaning/concept multi-dimensional space, allowing for more accurate and relevant results. With Neural Search, users can search by the true essence of concepts, removing language barriers and reducing costs associated with building and maintaining search systems.

Trends Found in this Post
Trend Post Mentions Total Month Mentions Posts Companies MoM
LLM 3 278 61 29 +150%
AI Model Fine-tuning 1 64 24 23 +60%
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