#jupyter_notebook#ai#llm#llms#multi_modal#openai#python#rag
Retrieval-Augmented Generation (RAG) is a technique that helps improve the accuracy of large language models by fetching relevant information from databases or documents. This approach ensures that the model's responses are based on up-to-date and accurate data, reducing errors and "hallucinations" where the model might provide false information. For users, RAG offers more reliable and trustworthy responses, allowing them to verify the sources used to generate those responses. This method also saves resources by avoiding the need to retrain models with new data.
https://github.com/FareedKhan-dev/all-rag-techniques
有消息称#小米#MIUI 安全组件即小米的杀毒引擎添加有国家反诈中心的扫描接口(nationalAntiFraudSingleAppScan)。
at com.miui.guardprovider.engine.mi.antidefraud.AntiDefraudAppManager.getSign(Unknown Source:0)
at com.miui.guardprovider.engine.mi.antidefraud.MiDetectAppsManager.virusInMiEngineRiskList(Unknown Source:30)
at com.miui.guardprovider.engine.mi.antidefraud.AntiDefraudAppManager.getDetectUnsafeAppStatus(Unknown Source:6)
at com.miui.guardprovider.manager.SecurityService$a.nationalAntiFraudSingleAppScan(Unknown Source:17)
at com.miui.guardprovider.aidl.IAntiVirusServer$Stub.onTransact(Unknown Source:38)
MIUI security components.apk源代码分析
viamogua.co