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slug: 8月25日内容汇总 | ||
title: 8月25日内容汇总 | ||
authors: [garfield] | ||
tags: [] | ||
--- | ||
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## 🌟 AI 相关 | ||
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[披上Agent盔甲的RAG,从此不再只是召回生成!](https://mp.weixin.qq.com/s/nNsJ3ZzyrP2bZUgL5oZIIw) | ||
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[Plan-based Retrieval,告别AI的胡言乱语](https://mp.weixin.qq.com/s/hQ5LGGWGhsFdfK8jCtdsDw) | ||
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[速度与精度的结合:Faster R-CNN模型的性能剖析](https://mp.weixin.qq.com/s/p3C_DvLdMU8YwrXSyb_1gg) | ||
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[Ilya Sutskever 预测:GPT-5 之后,AGI 将降临](https://mp.weixin.qq.com/s/ulmrLqvLgjK2ndLfTZfzJA) | ||
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[一文看懂GraphRAG:蚂蚁集团联合各所名校出品GraphRAG综述](https://mp.weixin.qq.com/s/NoxEMm94WgjI9CMR0hc6lA) | ||
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[不花一分钱!GPT-4o微调限时免费开放,每日附赠百万训练token](https://mp.weixin.qq.com/s/1iQmUOTHw_vOpFWkQ9zpUw) | ||
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[多图理解,更懂中文,支持function call的Phi-3.5来了!](https://mp.weixin.qq.com/s/QzwDumKV-A1-t9LYi8a15Q) | ||
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[大模型训练实战经验总结](https://mp.weixin.qq.com/s/ItpCTCcMjTWQJtgpvdwTfw) | ||
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[谢谢微软,又又又Open了!一口气发布3款Phi-3.5新模型,领先Llama3.1和谷歌同级模型](https://mp.weixin.qq.com/s/pST2aZI1VPc_4ruMtzGxYg) | ||
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[1000个样本胜过百万数据?Meta AI最新研究引发行业震动](https://mp.weixin.qq.com/s/6e4jnpFCLLaRBQ9af0wEWQ) | ||
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[极限套娃,Agent自动设计Agentic系统!](https://mp.weixin.qq.com/s/wb9VYJaQ3uViyRUGdnAMtA) | ||
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🌟 [RAG 检索大升级:BM25 与 RRF 助力 LLMs 精准破局](https://mp.weixin.qq.com/s/Cj27dsJp_hC8oNmsQd0x7g) | ||
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[使用 Dify 和 AI 大模型理解视频内容:Qwen 2 VL 72B](https://mp.weixin.qq.com/s/C1fHZKUl8KuS9uTV6b3BYg) | ||
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[一文讲明白大模型显存占用(只考虑单卡)](https://mp.weixin.qq.com/s/IBWobzTtJKT65UDNr8p81Q) | ||
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[使用FP8进行大模型量化原理及实践](https://mp.weixin.qq.com/s/4Mg7Zhgz45zt57QCDT339Q) | ||
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[大模型到底需要消耗多少GPU显存?公式和工具全都有](https://mp.weixin.qq.com/s/FFHCCXZypBZ4OJr9CNxjcg) | ||
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[Multi-Meta-RAG:langchain点名,评论爆吹的新研究](https://mp.weixin.qq.com/s/Jf3qdFR-o_A4FXwmOOZ3pg) | ||
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[RAG真的是LLM的未来吗](https://mp.weixin.qq.com/s/8lX6BkuhXk33HFaTP34z_A) | ||
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[OpenAI 绝密项目「草莓」技术详解](https://mp.weixin.qq.com/s/FCcBYT0y5FYQfmQ4BJBAdg) | ||
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[AgentWrite:为什么你的模型生成的内容长度总是不超过2K](https://mp.weixin.qq.com/s/1LpyH-mhsYVcJHVk7TQDXg) | ||
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[Meta-Rewarding :LLM对齐新技术](https://mp.weixin.qq.com/s/qW-e_ye3aqcQ63W6JJi-1g) | ||
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🌟 [RAG 进阶:一个 ctrl-c 就能拿走的图文检索框架](https://mp.weixin.qq.com/s/ttmLyw9idsfnxFYoOcfTXA) | ||
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[RAG 如何选择 chunksize 和 splitter](https://mp.weixin.qq.com/s/ogDOyUhy1pAvSadTDt0pSA) | ||
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[工业界Agentic RAG方案-Golden-Retriever](https://mp.weixin.qq.com/s/_w7xV_V_8WHHDpiHqKvO1A) | ||
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[WeKnow-RAG:结合网络搜索和知识图谱的自适应检索增强生成方法](https://mp.weixin.qq.com/s/TdmtUN6zBn5R88jmv2CJIg) | ||
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[阿里开源通用多模态大模型mPLUG-Owl3:迈向多图长序列理解](https://mp.weixin.qq.com/s/Zm5HNCvbOiihF8KyH2lQiA) | ||
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## ⭐️ Go & 云原生 & Rust 相关 | ||
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[Range Over Function Types](https://go.dev/blog/range-functions) | ||
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[Go 1.23 is released](https://go.dev/blog/go1.23) | ||
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🌟 [Kitex Thrift Streaming 在字节跳动 Prompt 平台的实践](https://mp.weixin.qq.com/s/f6dF415o4JbzFbNoZSkOTg) | ||
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[一款支持自动流水线和客户端缓存的 Go 语言 Redis 客户端](https://mp.weixin.qq.com/s/6BTRDyjSQIHtLo3Azk8qmQ) | ||
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[Go必知必会:协程(上):进程、线程、协程的区别和联系](https://mp.weixin.qq.com/s/-QrMsdOmBqnz50fAS0K9yw) | ||
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[Golang面试题:strings 和 strconv 包](https://mp.weixin.qq.com/s/r6k3CGpP1qXz-vVmeChOIw) | ||
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[基于 Gin 框架的 Go 后端架构最佳实践](https://mp.weixin.qq.com/s/DaCkIznCqxHeInNP5fYNgA) | ||
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[继Ollama之后,Go在AI领域再下一城](https://mp.weixin.qq.com/s/HPCdIwREB_wgylOWjxIsHQ) | ||
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[了解 Golang 中的内存管理:Stack vs Heap](https://mp.weixin.qq.com/s/BxBcX3gzIqaZfqziSvs1HA) | ||
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[Go必知必会:构建复杂数据模型的基石](https://mp.weixin.qq.com/s/LnDH9o4B3Vo3Dts_NjiD6A) | ||
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[Go 1.23中值得关注的几个变化](https://mp.weixin.qq.com/s/GvPDgWP6BjxllLPNnSNS3A) | ||
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[写给go开发者的gRPC教程-通信模式](https://mp.weixin.qq.com/s/SLQWWmOgqoj-8Ah3lsM3aQ) | ||
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[Golang面试题:基本类型和运算符](https://mp.weixin.qq.com/s/ygKWKp8TSfc1GGbPiUaKWg) | ||
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## 📒 后端相关 | ||
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[一线实战:运维人少,我们是如何从 0 到 1 实践 DevOps 和云原生](https://mp.weixin.qq.com/s/QwFmQDCNl83HMSc6pkQZnA) | ||
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[千万级数据的全表update的正确姿势!](https://mp.weixin.qq.com/s/5q1E2whNqaM3J2dAZFQwlg) | ||
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[系统设计:在搜索系统实现缓存的策略与思考](https://mp.weixin.qq.com/s/7SSFCj50SLS2g_u2opc_Dg) | ||
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[ByteHouse高性能向量检索实践——“以图搜图”](https://mp.weixin.qq.com/s/-cKEnIUvn1Fhn_UjA-qVRg) | ||
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[AI 网关零代码解决 AI 幻觉问题](https://mp.weixin.qq.com/s/_Ssm_AkiyAsfid2vSIucvw) | ||
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## 📒 前端相关 | ||
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