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Source channel @githubtrending · Post #14791 · Jun 5

#python#ai#ai_agents#ai_memory#cognitive_architecture#cognitive_memory#contributions_welcome#good_first_issue#good_first_pr#graph_database#graph_rag#graphrag#help_wanted#knowledge#knowledge_graph#neo4j#open_source#openai#rag#vector_database Cognee is an open-source AI memory engine that helps improve how AI systems understand and process data. It mimics human cognitive processes, creating "memories" from various data types like text and images. This enhances the accuracy of large language models (LLMs) and allows them to recall past interactions and documents. Cognee is scalable, cost-effective, and integrates easily with existing systems, making it a valuable tool for developers seeking to boost AI performance without relying on expensive APIs. https://github.com/topoteretes/cognee

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AIGC

@aigcrubbish · Post #158 · 01/27/2026, 05:06 PM

[$] Implicit arguments for BPF kfuncs Linux 内核的 kfunc 机制允许 BPF 程序直接调用内核函数。目前内核中有超过 300 个 kfunc,功能涵盖字符串处理(如 `bpf_strnlen()`)到自定义调度器(如 `scx_bpf_kick_cpu()`)等。 有时,这些 kfunc 需要访问 BPF 程序无法直接获取的上下文信息,因此无法通过参数传递。Ihor Solodrai 提交的“隐式参数”补丁集旨在解决这个问题,它允许 kfunc 隐式地接收额外的上下文参数。 原文链接:https://lwn.net/Articles/1055559/ #Linux#内核#BPF#kfunc #AIGC Read more