Engineering
Are CPUs Enough? A Review Of Vector Search Running On Novel Hardware
The rapid advancements in hardware technology are paving the way for more efficient and powerful vector search capabilities. As illustrated by the NeurIPS BigANN competition and Zilliz's contributions, the intersection of advanced hardware and innovative algorithms is key to the future of data retrieval technologies.
Engineering
Building RAG with Snowflake Arctic and Transformers on Milvus
This article explored the integration of Snowflake Arctic with Milvus.
Engineering
Building RAG with Zilliz Cloud and AWS Bedrock: A Narrative Guide
A comprehensive guide on how to use Zilliz Cloud and AWS Bedrock to build RAG applications
Engineering
Ensuring Data Privacy in AI Search with Langchain and Zilliz Cloud
This blog showed how to use Zilliz Cloud with LangChain to implement a question-answer bot.
Engineering
Enhancing ChatGPT with Milvus: Powering AI with Long-Term Memory
By integrating GPTCache and Milvus with ChatGPT, businesses can create a more robust and efficient AI-powered support system. This approach leverages the advanced capabilities of generative AI and introduces a form of long-term memory, allowing the AI to recall and reuse information effectively.
Engineering
Large Language Models and Search
Explore the integration of Large Language Models (LLMs) and search technologies, featuring real-world applications and advancements facilitated by Zilliz and Milvus.
Engineering
NLP and Vector Databases: Creating a Synergy for Advanced Processing
Finding photos, recommending products, or enabling facial recognition, the power of vector databases lies in their ability to make sense of the complexity of the world around us.
Engineering
NLP Essentials: Understanding Transformers in AI
This article will introduce you to the field of Natural Language Processing (NLP) and the breakthrough architecture, the transformer.
Engineering
Mastering Text Similarity Search with Vectors in Zilliz Cloud
We explore the fundamentals of vector embeddings and demonstrated their application in a practical book title search using Zilliz Cloud and OpenAI embedding models.