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Chaîne source @OnePlusGuide · Post #3192 · 4 nov.

🔻NUOVE INDISCREZIONI SUL NORD 2 PACMAN🔻 #OP#NORD#PACMAN Tempo fa, un team di sviluppatori aveva scoperto un tema segreto ispirato al famoso gioco Pac Man all'interno di un aggiornamento per Nord 2. Oggi, il leaker Max Jambor, ha pubblicato l'immagine che vedete qui sopra su Twitter. All'apparenza potremmo concludere che il telefono con il tema Pac Man non sarà altro che un'edizione speciale di Nord 2. Resta però un nodo da sciogliere: le prime indiscrezioni parlavano anche di uno Snapdragon 778G come processore. Vedremo una versione di Nord 2 con Snapdragon? Pierre — Il nostro canale 👉🏻@oneplusguide I nostri gruppi 👉🏻@oneplusitcommunity

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GitHub Trends

@githubtrending · Post #15295 · 11/11/2025 17:00

#python#ai#faiss#gpt_oss#langchain#llama_index#llm#localstorage#offline_first#ollama#privacy#python#rag#retrieval_augmented_generation#vector_database#vector_search#vectors LEANN is a tiny, powerful vector database that lets you turn your laptop into a personal AI assistant capable of searching millions of documents using 97% less storage than traditional systems without losing accuracy. It works by storing a compact graph and computing embeddings only when needed, saving huge space and keeping your data private on your device. You can search your files, emails, browser history, chat logs, live data from platforms like Slack and Twitter, and even codebases—all locally without cloud costs. This means fast, private, and efficient AI-powered search and retrieval on your own laptop. https://github.com/yichuan-w/LEANN

GitHub Trends

@githubtrending · Post #15168 · 25/09/2025 12:30

#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