In the field of artificial intelligence today, the most concerned thing is undoubtedly the large model. However, high training costs and long training time have become key bottlenecks that restrict most companies from entering large models.
In this context, vector databases, with their unique advantages, have become the key to solving the problem of low-cost and rapid customization of large models.
Vector database is a technology specifically designed to store and process high-dimensional vector data. It uses efficient indexing and query algorithms to achieve rapid retrieval and analysis of massive data. In addition to such excellent performance, vector databases can also provide customized solutions for specific fields and tasks.
As a pioneer and global leader in vector database systems has been deeply involved in the field since early on. It has always adhered to the mission of AI democratization and research and development for enterprise-level AI applications. Streamline AI data management infrastructure.
VectorDB application process, taking Zilliz Cloud as an example
Under the wave, technology giants such as Tencent, Alibaba and other companies have deployed vector database research and development, striving to achieve breakthroughs in the field of large models. At the same time, a large number of small and medium-sized companies are also using the capabilities of vector databases to quickly enter large models and seize market opportunities.
In addition, several recently released industry research reports on vector databases also indicate that vector databases will become the mainstream trend in data storage and processing in the future, and the market size is expected to expand rapidly.
It can be said that vector databases have become an important driving force in promoting the development of artificial intelligence technology. In this technological revolution, the first to seize the development opportunities of vector databases will be more likely to lead the future technological trend.
At present, low-cost and rapid customization of large models has become a reality.
For many developers, the learning threshold for fine-tuning large models is not high, and it is easy to get started by self-study. However, various problems still arise in practical applications.
How to maximize the value of plug-in knowledge bases and vector databases, how to build a vector database from 0 to 1, how to design technical architecture, how to break through key technical bottlenecks, how to use RAG and vector databases to build enterprise knowledge bases, and the technology implementation process Questions and confusions such as which detours are easy to take, are there any pitfall avoidance guides, etc. are all obstacles to technology application and industry development.
It can be seen that for the fields of RAG and vector databases, technical practices and first-line implementation scenarios still require continuous exploration and exploration.
In addition to best practices, an unavoidable challenge in the field of large models is that they change too quickly.
OpenAI’s first developer conference exploded a few days ago and was widely defined as changing the existing large model landscape. What impact will this have on the development of the vector database industry? RAG takes the stage again? Is this field still worth investing in now? What technology can replace it in the future...
This kind of thinking and discussion about the future of technology and technical vision is increasingly important in the era of rapid change, and will guide companies in the large model field to optimize their strategic layout and guide practitioners to complete career upgrades and career planning.
Based on this, Machine Heart specially planned an AI technology forum with the theme of " Vector Database in the Large Model Era ".
The forum lasted for two days. We not only focused on the technical implementation and technological breakthroughs of RAG and vector databases, but also focused on industry best practices to see how vector databases can be effectively implemented in the era of large models and what application scenarios there are. In addition, where will the future of vector databases go? How can companies and individuals take advantage of this opportunity to complete strategic layout and career upgrades?
At that time, Zilliz will discuss the above topics with colleagues in the field. I believe that this technology forum will definitely bring you inspiration and gain.
Double Eleven ticket discounts
During the Double Eleven promotion period, a 2-day pass to the forum is available for as low as 1,999 yuan per ticket, including a 2-day lunch buffet at a five-star hotel . Come and sign up!
Scan the QR code in the picture to go directly to the forum’s official website. From now until 23:55 on November 19, those who purchase tickets to participate in the conference can enjoy a direct discount of 2,000 yuan on tickets. Discounted tickets are first come, first served.
Participants of the first phase of the Heart of Machine AI Technology Forum "Llama 2 Large Model Algorithm and Application Practice", please add the WeChat account of the assistant Alice separately to directly access the exclusive discount link.
Forum schedule
The mysterious guests for the keynote speech are all in place. They are Professor Zhang Qi from Fudan University, Chen Qi, chief researcher at Microsoft Research Asia, and Luan Xiaofan, partner and technical director of Zilliz, who will also give in-depth sharing on site. Come and take a look at what they have to share. and the latest schedule.
This forum focuses on technical exchanges in the industry. The guests’ sharing is all technical information and does not contain product advertisements. (If you want to learn about related products or projects, please visit the booth area)
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