Authors: Zhi Jing, Yongye Su, Yikun Han, Bo Yuan, Chunjiang Liu, Haiyun Xu, Kehai Chen

Published on: January 30, 2024

Impact Score: 8.07

Arxiv code: Arxiv:2402.01763

Summary

• What is new: The paper explores the intersection of Large Language Models and Vector Databases, which is a relatively unexamined area.
• Why this is important: Large Language Models face challenges like hallucination, bias, and high costs.
• What the research proposes: Integrating Large Language Models with Vector Databases to improve data handling and efficiency.
• Results: This integration enhances AI systems’ capabilities in information retrieval and semantic search.

Technical Details

Technological frameworks used: Vector Databases integration

Models used: Large Language Models

Data used: High-dimensional data for semantic search and information retrieval

Potential Impact

AI technology providers, search engines, content management platforms, and companies in need of efficient data processing and retrieval solutions.

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