Introduction With the development of large models, vector databases have also ushered in broader application prospects. They not only assist large models in inference acceleration but also save costs for users. Moreover, vector databases are an effective means to address the limitations of large models. As a result, more and more large model deployment projects … Read more
How to Build a Face Recognition Application from Scratch? Try the combination of native Java AI algorithm: EasyAi + Milvus. The software and tools used in this article include: EasyAi: Face feature vector extraction Milvus: Vector database for efficient storage and retrieval of data. 01. EasyAi: The Most Popular Java AI Algorithm Framework in China … Read more
Written by: Dluck Cover: GitHub Official Blog The code we write while programming usually exists in plain text format before compilation. Therefore, we can actually use any text editor to write code, including the built-in Notepad of the system. However, good tools can make us more efficient. When facing complex tasks, we need productivity tools … Read more
In the past two years, multi-task learning has been gradually replacing traditional single-task learning and becoming a mainstream research direction in the field of artificial intelligence. The reason is that multi-task learning allows us to gain as much AI capability as possible with minimal human input. For example, ChatGPT is a natural language generation model … Read more
Milvus is an open-source vector similarity search engine that supports the use of various AI models to vectorize unstructured data and provides search services for vector data. Milvus integrates widely used vector indexing libraries such as Faiss and Annoy, allowing developers to choose different indexing types for different scenarios. Using Milvus, one can develop a … Read more
The combination of AI and smart healthcare is an inevitable trend for future development. In recent years, the National Health Commission has promoted smart healthcare and AI technologies, such as intelligent triage, pre-consultation, and diagnostic assistance, to improve the efficiency of medical services and the accuracy of diagnoses, enhancing the patient experience. Quanzhentong is a … Read more
In recent years, the technology of Retrieval-Augmented Generation (RAG) has gained significant attention in the field of artificial intelligence. However, as demands have become more complex, traditional RAG has shown limitations in handling multi-step reasoning and external tool calls. To address this, Agentic RAG has emerged as an upgraded version of RAG, showcasing more powerful … Read more
The field of new drug development has long been known for its lengthy timelines, high costs, significant risks, and low return on investment. The average development cost for a new drug has reached $2.6 billion, with an average time frame of ten years. Despite such high R&D costs and prolonged timelines, there is no guarantee … Read more
So far, we have discussed the architecture of Agent systems, how to organize the system into sub-Agents, and how to build a unified mechanism to standardize communication. Today, we will turn our attention to the tool layer and one of the most important aspects you need to consider in Agent system design: data retrieval. Data … Read more
Today is January 18, 2025, Saturday, Beijing, clear weather. Let’s continue discussing RAG. Recently, there has been some work on Agentic RAG, which integrates autonomous agents to overcome the limitations of traditional RAG systems that perform well in knowledge retrieval and generation but struggle with dynamic, multi-step reasoning tasks, adaptability, and complex workflow orchestration. So, … Read more