#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
Curated Crypto | ꘜ
🤑WTF: ETH options open interest just hit a 1.5-year high!
Degens are loading up on longs, while whales are stacking ETH at all-time record pace!
But hedge funds are going mega short - CME ETH futures short positioning just keeps smashing new records!
Green But Red in real life!
#WTF
The suspect attempted to escape an interrogation room by breaking through the wall while no one was watching—only to be caught shortly after.
@Viral_Today / #wtf
Imagine a coffee table that moves around the house by itself—well, you don’t have to anymore because it’s real. It’s just as fascinating as it is creepy.
@Viral_Today / #wtf