#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
TON — LIVE: Telegram Rises in Popularity Rankings
#Telegram#apps
The channel TON — LIVE reports that Telegram has moved up one rank in the list of the most popular apps for 2025.
Source: link
@tonlines
⚡️Trending Apps: New Voting System in Telegram Apps Center
#Telegram#Apps
Trending Apps announces that users can now influence the ranking of Mini Apps through a new voting system in the Telegram Apps Center. Active participants will be rewarded with exclusive SBTs and Telegram Gifts.
Source: link
@tonlines
⚡️Trending Apps: Upcoming Feature in Apps Center
#Telegram#Apps
Trending Apps announced a new feature in the Apps Center, aiming to enhance user engagement by allowing users to influence developments directly. This innovative approach is set to launch within the next 30 days, with more details to be revealed gradually.
Source: link
@tonlines
A partir de hoy amigos, estaré entregando #apps, recursos, plataformas y tips para usar la tecnología a su favor y mejorar las condiciones de #empleo📄📈