Dynamic Information Updates
By connecting to real-time data sources, it ensures that the information provided is always fresh.
Deep Semantic Understanding
Going beyond keyword matching, it deeply analyzes the actual needs of users.
Personalized Experience
Providing customized suggestions and services based on different user preferences and history.
Extensive Knowledge Coverage
Not limited to knowledge in a specific field, but covering a wide range of topics.
The reason WestlakeChat can stand out among numerous intelligent applications lies in its deep integration of RAG technology with its architecture. In the process of generating answers, WestlakeChat does not solely rely on the pre-trained knowledge within the model but cleverly combines the power of external knowledge bases. When users ask questions, the system first uses RAG technology to analyze and process the question, determining whether external knowledge retrieval is necessary. If needed, it swiftly searches through a vast knowledge base that includes a wealth of academic literature, industry reports, news information, and other up-to-date resources.
For example, when a user inquires about the development trends of a certain emerging industry, WestlakeChat will not be limited to outdated data from the model’s training but will use RAG technology to retrieve key information from a vast array of the latest industry reports, research papers, etc., generating a detailed answer that combines deep understanding from the model with the latest news.
Question 1: “What important findings does the article The Surprising Effectiveness of Test-Time Training for Abstract Reasoning published in November 2024 have?”
“In this search result, the o1 model output exhibits hallucination. Due to the failure to find the newly published article, o1 merely speculates that the study might discuss fine-tuning the model during the testing phase (rather than the training phase) to improve its performance on abstract reasoning tasks, but cannot provide exact findings.”
“WestlakeChat can accurately find related articles and lists the main findings of the article in detail.”
“Due to the absence of RAG, its output contains ‘hallucination’. As seen in the image, o1 seems to misunderstand the search intent, mistakenly interpreting ‘SMR Portal Paper’ as content related to SMR (Smooth Model Repair) technology, and the provided content may be inaccurate or unfounded.”
Whereas WestlakeChat with RAG can accurately find content related to ‘SMR Portal’. It mentions that SMR Portal is an online platform aimed at integrating GWAS (Genome-Wide Association Studies) and xQTL (expression quantitative trait loci) data to identify genes associated with complex traits. It also detailed the main features and functionalities of SMR Portal, including data integration (GWAS data and xQTL data), statistical methods, etc., and mentioned technical details and application case-related content, providing an accurate and organized response..
“o1 can only list basic paper information, with relatively basic and brief content, unable to determine whether it covers important research and the latest developments in the field. Additionally, it lacks the ability to search for the latest research achievements, and the provided papers are dated, possibly failing to capture new breakthroughs and discoveries in the field.”
“WestlakeChat not only lists several of the latest related papers but also provides richer content, such as specific research content, mechanisms of action, structural characteristics, etc., giving a more detailed explanation of the AKR1C family 1-3 proteins, better meeting the user’s need for a comprehensive understanding of research in this field.”
Compared to applications that merely rely on encapsulated interfaces, WestlakeChat, leveraging RAG technology, has achieved a qualitative leap, successfully transforming from a traditional general model into a personalized knowledge companion for users. It breaks the monotonous response patterns of previous intelligent applications, providing customized information services accurately based on each user’s unique needs and usage habits. Whether in academic research, professional work, or daily life information inquiries, WestlakeChat, supported by its powerful RAG technology, can provide timely, accurate, and personalized assistance to users.
In the future, as RAG technology continues to develop and improve, WestlakeChat is expected to play an even more significant role in the field of intelligent interaction. On one hand, technology developers will continue to explore and optimize various components of RAG technology, further enhancing system performance and efficiency; on the other hand, with the maturation and application of multimodal technology, WestlakeChat may achieve more natural and smooth multimodal interactions, bringing users a more immersive intelligent experience. Let us look forward to WestlakeChat’s continuous innovation and development in the new journey of intelligent interaction, opening up a smarter and more convenient future for users.
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