As the wave of digitalization sweeps the world, artificial intelligence (AI) technology is changing the way we live at an unprecedented rate. In the rapid development of AI technology, vector databases play a pivotal role. Recently, at the GTC2024 conference, NVIDIA and China's vector database pioneer Zilliz jointly released the GPU-accelerated Milvus 2.4 version, which undoubtedly injected new vitality into the development of AI large models.
A vector database is a database system that specializes in processing vector data, and it plays an important role in machine learning and artificial intelligence applications. From recommender systems to image recognition to natural language processing, vector databases provide strong support for AI applications with their efficient data processing capabilities. As a graphics processing unit, GPUs are ideal for accelerating complex computing tasks with their powerful parallel processing capabilities. As a global leader in GPU technology, NVIDIA's deep accumulation in the GPU field provides the possibility for the acceleration of vector databases.
Zilliz, a start-up born in China, has been focusing on the research and development of vector database systems since its establishment in 2016. Its Milvus vector database has been favored by users around the world for its high performance, scalability, and ease of use. Now, with the release of Milvus 2.4, the performance of vector databases has been improved to a new level.
The innovation of Milvus 2.4 is that it takes advantage of the high-speed computing characteristics of the GPU to accelerate vector similarity search and analysis. By leveraging the efficient parallel processing capabilities of NVIDIA GPUs and the new CAGRA technology in the RAPIDS cuVS library, the new version of Milvus provides GPU-based vector indexing and search acceleration capabilities. The introduction of this technology not only improves the performance of vector search, but also reduces latency, making Milvus an ideal tool to support real-time decision-making and complex data analysis.
Benchmark data shows that the new GPU-accelerated Milvus delivers up to 50x faster vector search performance than the most advanced CPU-based indexing technology on the market. This means that when processing massive amounts of vector data, Milvus can complete search tasks more quickly, providing users with a more efficient AI application experience.
As an indispensable software for the development of AI large models, vector databases play an important role in AI large model technology. Traditional AI models are often unable to deal with the problems of knowledge timeliness, limited input capacity, and low accuracy in answering questions, while the capabilities of vector databases such as fast retrieval, hybrid storage, and vector embedding can effectively solve these problems. Therefore, with the continuous development of AI large model technology, the application of vector database will become more and more extensive.
From the perspective of practical application cases, vector databases have shown its potential to reduce costs and increase efficiency in the training and inference process of large AI models. ChatGPT Plugins not only expands the scope of AI large model interaction information but also protects user privacy by connecting to an external vector database. The collaboration between Qdrant Vector Database and Pienso also demonstrates the feasibility of vector databases in developing large models in the private domain. These successful cases provide strong support for the application of vector databases in the field of AI large models.
GF Securities pointed out in the report that with the increasing amount of data and the increasing variety of data types for AI model training, the demand for vector databases has also begun to form a scale. In particular, driven by benchmark products such as Microsoft 365 Copilot and ChatGPT Enterprise Edition, the development of AI applications is gradually spreading from point to surface. In the future, with the growth of the development and usage of generative AI large models, the application of vector databases is expected to grow rapidly.
In terms of commercialization, although the vector database industry is still in the market cultivation period, many companies have launched related products. Vendors such as Zilliz, Pinecone, and Tencent Cloud have launched free versions of their products for users to try out. At the same time, vendors such as HUAWEI CLOUD and Transwarp have also accumulated certain technical experience in unstructured data processing, and have successively launched vector database products. The active participation of these vendors will further drive the growth of the vector database market.
To sum up, the GPU-accelerated vector database Milvus 2.4 jointly released by NVIDIA and Zilliz is undoubtedly an important innovation in the field of AI large models. The introduction of this technology will further improve the performance and efficiency of vector databases, and inject new impetus into the development of AI applications. In the future, with the continuous progress of AI technology and the continuous expansion of application scenarios, the application prospect of vector database will be broader.