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Source channel @githubtrending · Post #14777 · Jun 3

#other#applications#coderquad#college#fulltime#hacktoberfest#jobs#newgrad#position#posting#university This resource is a regularly updated list of entry-level jobs for new graduates in software, tech, computer science, product management, and quantitative roles for 2024 and 2025, organized by Coder Quad and Simplify[1][2][4]. It features a wide range of open positions from top companies, sorted by category like software engineering, data science, AI, quantitative finance, and hardware engineering. The list is easy to browse, with direct links to apply for each job, and is updated daily so you always see the latest opportunities. You can also use tools like Simplify’s browser extension to autofill job applications and get email alerts for new roles, saving you time and effort. This helps you quickly find and apply for jobs that match your skills and interests, making your job search much easier and more efficient[1][2][4]. https://github.com/SimplifyJobs/New-Grad-Positions

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@githubtrending · Post #15295 · 11/11/2025, 05:00 PM

#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

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

#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