Dynamic information processing mechanism based on Google PaLM 2
Chatly builds a unique information update system by deeply integrating Google PaLM 2's search API. When a user query involves current news, stock price fluctuations or academic frontiers, the system initiates a multi-search engine federated query (including Google Scholar and News API) in real time, and screens the top 5 highest quality result sources through a semantic matching algorithm, generating summaries after de-emphasis and credibility weighting. Tests show that this feature improves the information accuracy to 92%, which is 57% higher than the traditional static knowledge base solution.
Two stages of validation are used in the implementation: firstly, the initial results are obtained through PaLM 2, and then the logical coherence is verified by GPT-4. For example, when searching for "New Crown Vaccine Update", the system will exclude old studies older than 3 months and prioritize clinical trial data from authoritative medical journals. Administrators can adjust the search depth (from concise summaries to detailed reports) and source preference (academic/commercial/government) in the settings.
This answer comes from the articleChatly: Intelligent Chat and Content Generation Tool with Integration of Multiple AI ModelsThe
