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Source channel @githubtrending · Post #15168 · Sep 25

#python#ai#context#embedded#faiss#knowledge_base#knowledge_graph#llm#machine_learning#memory#nlp#offline_first#opencv#python#rag#retrieval_augmented_generation#semantic_search#vector_database#video_processing Memvid lets you store millions of text pieces inside a single MP4 video file using QR codes, making your data 50-100 times smaller than usual databases. You can search this video instantly in under 100 milliseconds without needing servers or internet after setup. It works offline, is easy to use with simple Python code, and supports PDFs and chat with your data. The upcoming version 2 will add features like continuous memory updates, shareable capsules, fast local caching, and better video compression, making your AI memory smarter, faster, and more flexible. This means you get a powerful, portable, and efficient way to manage and search huge knowledge bases quickly and easily. https://github.com/Olow304/memvid

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Crypto M - Crypto News

@CryptoM · Post #65047 · 04/10/2026, 04:10 PM

🚀 Whop Introduces Treasury Yield Product Following Tether Investment Whop has launched its Treasury yield product on March 25, following a significant investment from Tether in February, which valued the company at $1.6 billion. According to NS3.AI, the product was introduced after Tether's $200 million investment. Steven Schwartz noted that 3% of users engaged with the beta version within a week, despite the absence of a marketing campaign. The product channels funds through a Veda vault on Plasma into Aave lending markets, offering an annual percentage yield (APY) of up to 6%. The investment from Tether will enable Whop to integrate on-platform USDT wallets and payment options. #Whop#Tether#TreasuryYield#Investment#Crypto#APY#Aave#USDT#Fintech#Blockchain#AAVE