#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
🗣#Superposition: Week 3 Galxe Quests
Superposition is an L3 built on Arbitrum, offering native liquidity and DeFi incentives.
It also uses Conduit tech — so by completing these, you’re farming two ecosystems at once.
New quest wave announced
What to do:
✔ Swap or add at least $10 liquidity on Camelot
✔ Make a swap on Longtail
✔ Claim 30 points on Galxe
☝️ Start trading on Bybit
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🌎 Quantum physics allows for the concept of “superposition,” where particles exist in multiple states at once. This principle forms the basis for theories suggesting that parallel worlds or dimensions might exist alongside our own. The famous “double-slit experiment” demonstrates superposition, as particles act as if they travel through two paths simultaneously. ✨
#quantum⚡#superposition⚡#multiverse
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