GitHub(微博搜索)-20240407-1

本条微博地址 爱可可-爱生活
【DrawDB：免费的、简单的和直观的在线数据库设计工具和 SQL 生成器】'DrawDB - Free, simple, and intuitive online database design tool and SQL generator.' GitHub: github.com/drawdb-io/drawdb #开源# #机器学习# #SQL#

本条微博地址 爱可可-爱生活
【faces.js：用于生成卡通脸矢量图片的 JavaScript 库】'faces.js - A JavaScript library for generating vector-based cartoon faces' GitHub: github.com/zengm-games/facesjs #开源#

本条微博地址 伤心大茄哥
一不小心把OSS密钥暴露在github上了怎么办

本条微博地址 爱可可-爱生活
【torchdbg：PyTorch 操作的跟踪器和反应式 UI，用于以调试器的形式可视化跟踪】'torchdbg - PyTorch centric eager mode debugger' GitHub: github.com/ezyang/torchdbg #开源# #机器学习# #人工智能#

本条微博地址 爱可可-爱生活
【OpenAI Streaming：一个 Python 库，提供易于使用的 Pythonic 接口，支持 OpenAI 的基于生成器的 Streaming，并支持回调机制来处理流内容】'OpenAI Streaming - Work with OpenAI's streaming API at ease with Python generators' GitHub: github.com/AlmogBaku/openai-streaming #开源# #机器学习# #人工智能#

本条微博地址 爱可可-爱生活
【Boehm-Demers-Weiser Garbage Collector：保守的 C/C++ 垃圾收集器，可以在使用时动态分配内存】'Boehm-Demers-Weiser Garbage Collector - The Boehm-Demers-Weiser conservative C/C++ Garbage Collector (bdwgc, also known as bdw-gc, boehm-gc, libgc)' GitHub: github.com/ivmai/bdwgc #开源# #C++#

本条微博地址 GitHubDaily
推荐 GitHub 上一款开源免费平替 Perplexity AI 工具 FreeAskInternet。

这是一款完全免费基于搜索的问答 AI 工具，可本地运行且无需 GPU 硬件支持，能很好确保隐私安全。

只需输入问题，工具便会通过 SearXNG 进行多引擎搜索，并利用 GPT-3.5 处理搜索结果，总结并生成答案。

GitHub：github.com/nashsu/FreeAskInternet

主要特性：

🈚️ 完全免费：无需支付任何费用或申请任何 API 密钥。
💻 本地化操作：不需 GPU 支持，任何电脑均可运行。
🔐 保障隐私：所有操作均在本地执行，确保隐私安全。
👻 无需专门的大语言模型硬件：免 GPU！
🤩 支持免费的 GPT-3.5 API：无需 API 密钥即可使用。
🚀 快速部署：支持 Docker Compose，便捷部署。
🌐 适配网络和移动端：无论是通过电脑还是移动设备，都能轻松访问。

项目提供了 docker-compose 快速部署方式，并且是在熟悉的 NextChat 页面上使用，可快速上手。 GitHubDaily的微博视频

本条微博地址 爱可可-爱生活
【twitter-web-exporter：使用 TypeScript 开发的开源项目，可用于从 Twitter 网页应用程序导出 tweets、书签、列表、搜索结果、用户关注列表等】'twitter-web-exporter - Export tweets, bookmarks, lists and much more from Twitter(X) web app. (推文/书签/收藏/列表导出工具)' GitHub: github.com/prinsss/twitter-web-exporter #开源#

本条微博地址 爱可可-爱生活
几篇论文实现代码：
《EgoExoLearn: A Dataset for Bridging Asynchronous Ego- and Exo-centric View of Procedural Activities in Real World》(CVPR 2024) GitHub: github.com/OpenGVLab/EgoExoLearn [fig1]
《PKU-DyMVHumans: A Multi-View Video Benchmark for High-Fidelity Dynamic Human Modeling》(CVPR 2024) GitHub: github.com/zhengxyun/PKU-DyMVHumans [fig3]
《HairFastGAN: Realistic and Robust Hair Transfer with a Fast Encoder-Based Approach》(2024) GitHub: github.com/AIRI-Institute/HairFastGAN [fig2]
《GIPC: Fast and Stable Gauss-Newton Optimization of IPC Barrier Energy》(2024) GitHub: github.com/KemengHuang/GPU_IPC
《P-MapNet: Far-seeing Map Generator Enhanced by both SDMap and HDMap Priors》(2024) GitHub: github.com/jike5/P-MapNet [fig4]
《MacGyver: Are Large Language Models Creative Problem Solvers?》(2024) GitHub: github.com/allenai/MacGyver [fig5]
《UltraLight VM-UNet: Parallel Vision Mamba Significantly Reduces Parameters for Skin Lesion Segmentation》(2024) GitHub: github.com/wurenkai/UltraLight-VM-UNet

本条微博地址 _女鬼廚_
我再也不會放開源項目在GitHub了// @红西柚汁酱 :注视是什么超绝谐音梗

本条微博地址 Ngortchan
我发现我已经不会提交 Pull Request 了，上个 GitHub 一顿抓瞎。

本条微博地址 _鲁肃_
推荐 GitHub 上一款开源免费平替 Perplexity AI 工具 FreeAskInternet。

这是一款完全免费基于搜索的问答 AI 工具，可本地运行且无需 GPU 硬件支持，能很好确保隐私安全。

只需输入问题，工具便会通过 SearXNG 进行多引擎搜索，并利用 GPT-3.5 处理搜索结果，总结并生成答案。

GitHub：github.com/nashsu/FreeAskInternet

主要特性：

🈚️ 完全免费：无需支付任何费用或申请任何 API 密钥。
💻 本地化操作：不需 GPU 支持，任何电脑均可运行。
🔐 保障隐私：所有操作均在本地执行，确保隐私安全。
👻 无需专门的大语言模型硬件：免 GPU！
🤩 支持免费的 GPT-3.5 API：无需 API 密钥即可使用。
🚀 快速部署：支持 Docker Compose，便捷部署。
🌐 适配网络和移动端：无论是通过电脑还是移动设备，都能轻松访问。

项目提供了 docker-compose 快速部署方式，并且是在熟悉的 NextChat 页面上使用，可快速上手。 GitHubDaily的微博视频

本条微博地址 GitHubDaily
推荐 GitHub 上一款漂亮易用且功能强大的开源创意图片编辑器 poster-design。

适用于多种场景，如海报图片生成、电商分享图、文章长图等，无需客户端也可轻松在线编辑、迅速完成图文排版。

GitHub：github.com/palxiao/poster-design

支持功能：

- 导入 PSD 文件解析成模板、在线导出图片下载。
- 元素拖拽、组合、缩放、层级调整、对齐等操作。
- 图片素材插入、替换、裁剪，图片容器等功能。
- SVG 素材颜色、透明度编辑，文字花字组合。
- 画布自定义尺寸、滚轮缩放、自适应画布
- 吸附对齐、辅助引导线、标尺功能。
- 键盘快捷键、右键菜单快捷操作，复制删除等常用操作。
- 风格二维码编辑，支持单色、渐变、自定义 logo 等。
- 图层操作，支持拖拽变更层级。
- 颜色调色板，原生级取色器颜色吸管（Chrome）。 GitHubDaily的微博视频

本条微博地址 海辛Hyacinth
更新后的 IPAdapter 可以风格和构图分别参考了，感觉风格LoRA越来越不需要了 项目地址：github.com/cubiq/ComfyUI_IPAdapter_plus

本条微博地址 薛凌薛凌
分享 GitHub 上一份自动更新的 IPTV 直播源。

每两小时自动更新一次，含有超过 1w+ 数量的 IPTV 列表，丰富且全面！

GitHub：github.com/HerbertHe/iptv-sources

如果你在找一款开源免费的安卓电视直播软件，这里推荐 My TV。

内置了直播源，直接安装即可使用，具有稳定、快速、免费和无广告等特点。

GitHub：github.com/lizongying/my-tv

注意：仅支持安卓 4.2 及以上系统。

本条微博地址 爱可可-爱生活
【Loki: 由 Libra-AI 开发的一个开源工具，旨在将事实验证过程自动化】'Loki: An Open-source Tool for Fact Verification - Open-source solution designed to automate the process of verifying factuality' GitHub: github.com/Libr-AI/OpenFactVerification #开源# #机器学习# #人工智能#

本条微博地址 蚁工厂
一个Git统计工具，对git仓库的数据进行可视化和分析 地址：github.com/bakhirev/assayo 效果如图

本条微博地址 伯利恒01
GitHub COO Kyle Daigle on the “secret of good AI”
The technology is not a replacement for human labor — it's a way to complement existing human tasks.
Illustration of a smiling man wearing glasses against a geometric background, unraveling the secret of good AI.
Claire Merchlinsky
KEY TAKEAWAYS
In science fiction and real life, encountering advanced technology often leads to a period of confusion. This is true of AI today. The surge in AI has transformed industries, but there is still a need to calibrate and determine the best usage policies. AI should be seen as a tool to complement human tasks, reducing toil and enhancing productivity.

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There is a common plot device used in science fiction where a primitive life form will encounter some strange or more advanced technology. Initially, the creature simply stares at the device. Like a monkey with an iPhone, they bash and abuse the technology. Over time, either the protagonists or we, the audience, will work out the proper usage. For instance, the entire plot of Arthur C. Clarke’s Rendezvous with Rama features human explorers who board the alien spacecraft Rama to find themselves faced with technologies they cannot comprehend.

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The same is true, too, in real life. There have been many moments in history when humans have discovered or invented a thing, only for it to take a great deal longer to work out how to best use it. Once the steam engine gained popularity in the 18th century, it took nearly a century to figure out how to transform this energy into useful consumer and industrial products. When Heinrich Hertz discovered radio waves in the late 19th century, he speculated they might not have any practical value whatsoever. It took another few decades before Guglielmo Marconi invented the radio. The internet languished as military technology for twenty years until commercial and civilian use became obvious.

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So, too, with artificial intelligence. Even the most cursory observer will sense that we’re on the cusp of something momentous. The surge in AI has already transformed industries and societies in ways we couldn’t imagine ten years ago. But we are still in a calibration period. We’re still working out the best usage policy.

Earlier this year Big Think talked to the COO of developer platform GitHub, Kyle Daigle, about how he sees AI being used, and he put it like this: “Right now, we’re just trying to jam AI everywhere. It’s like saying, ‘Well, we could use this for mashed potatoes!’ But no, this thing is a butter churn. It’s not meant to do that. And we’re at that moment in the industrial revolution of software where we’re trying to figure out where we apply it.”

The distraction of a gimmick
Imagine you are a science fiction savage and you come across a pen-shaped, sleek metal object. You know it’s futuristic. You know it’s powerful. What do you do? Well, you monkey-bash it. You press along its side, you tap it on the table, you waft it like a wand, and so on. You desperately try everything you can to turn on or activate the object. But this wastes time and adds nothing in the long run. According to Daigle, this is exactly the problem facing AI right now.

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“Most employers or companies, when they’re adding AI to their product or bringing AI tools to their businesses, they’re looking for those sparkle moments, those shiny moments, and they’re usually just veneers,” he says. “They’re not actually improving the lives of anyone. And that’s the secret of good AI; it’s not that. I can chat with this tool and get the same answers back — but it should make me feel more productive and happier and get the result I’m looking for faster.”

Daigle’s point resonates. If you have spent any long period of time on AI, you will realize not only how much of a time sink it is but also that it can often make tasks longer. At times, LLMs can be a glorified Google search, but they are more expensive and take longer to produce. At other times, if their output requires serious fact-checking or re-editing, you might as well have solved the issue yourself. It’s similar to the early days of voice-to-text software — the gimmick distracted from reality. Even today, it’s often longer to reread and copy-edit Siri or Google Assistant than it is to type the message.

Integrated AI
In the mad rush to provide the killer AI application, GitHub has chosen to adopt a different approach. They see AI not as a replacement for human labor, nor is it an entirely new industry altogether. Rather, AI is a way to supplement and complement existing human tasks. As Daigle put it, “At GitHub, for our product [the code completion tool Copilot], we’re really looking at places where there’s no new behavior necessary. We’re not teaching you how to engage with the AI; we’re saying it’s something you’ve dealt with for years. But now let’s just let the AI fix it with a click of this button, as opposed to having to go build the fix. The AI is completely in the flow.”

“Right now, we’re just trying to jam AI everywhere … and we’re at that moment in the industrial revolution of software where we’re trying to figure out where we apply it.”

Kyle Daigle, COO of GitHub
The fundamental and philosophical point underpinning Daigle’s view is that humans do not radically change their behaviors overnight. In fact, if you look at the history of human progress, you can see humans doing the same things, but with different tools and with different degrees of efficiency. AI will not turn us into lounge-lizards reclining on spaceships in utopian immobility. It will not make human behaviors, or even work, entirely obsolete — at least overnight. That’s not how progress works. As Daigle puts it, “Every time you say to a customer or any human, ‘Well, everything will be better if you just change everything about the way you do it,’ then it won’t happen. Behavior change doesn’t work that way. It has to be small, incremental, and valuable.

A good fit for humans
No one is ruling out the possibility that AI will radically transform the world. In fact, it’s likely that it will. But not in the short-to-medium term. The AI tools we have at the moment are just that: tools.

“I think the first thing is that you have to start where your employees are experiencing toil in their day-to-day job,” says Daigle. “You can’t really come in and be like, ‘Oh, writing docs is long and hard. So, here’s a tool that’s going to help you write docs.’ If that’s a core part of your job, you might enjoy the benefit, but that’s not toil work — that’s the job. The benefits of bringing AI to normal employees are where we’re reducing toil.”

AI might be the most impressive technology humans have ever invented, but it still has to fit into a human hand.

One example, he continues, is “how no one wants to say, ‘Hey, my computer doesn’t work. Let me go submit a ticket and then wait a day.’ That’s just toil work for everyone involved. And at GitHub, what we did was find a vendor that can help answer these questions and take actions on behalf of employees in a chat room. So you go to the IT help desk; you don’t create a new ticket, and you don’t do anything new. You just type, ‘Hey, my computer is really old.’ And the AI says, ‘Oh well, it looks like you’re eligible for a refresh. Here, click this button, and we’ll send you a new laptop.’ No one had to do anything. That’s a real reduction in toil.”

Daigle’s point is that we have to make AI practical and meaningful. Artificial intelligence could be a hammer for a nail, a microscope to see better, or a pen to write better. We don’t entirely know what it’s best at yet, but the fact is that it has to complement existing behaviors. AI might be the most impressive technology humans have ever invented, but it still has to fit into a human hand.

本条微博地址 AI范
#AI探索计划# 与 AI 结对编程：GitHub Copilot 使用入门。

本条微博地址 黄建同学
免费开源 perplexity AI 平替：FreeAskInternet

🈚️ 完全免费 ( 无需任何 API key)
💻 完全本地运行 ( 无需 GPU )
🔐 完全隐私 (本地运行)
🚀 Docker一键部署

借助 FreeGPT35 以及 searxng #程序员#

项目： github.com/nashsu/FreeAskInternet

——
来自作者的自述：
这个项目是我的一个小实验，今天下午花了3小时完成，借助 FreeGPT35 以及 searxng。

这个项目灵感来源其实是 ChatGPT3.5 免费开放使用，以及发现了 searxng 这个宝藏项目，使得做一个免费的基于搜索的问答AI成为可能。

同时在线服务存在很多隐私问题，一直想做一个本地运行的、完全免费的、不需要硬件支持的开源平替。

ChatGPT 黄建同学的微博视频

本条微博地址 量子位
#Claude最全使用指导#

一份由 GitHub 广大网友共同创建的 【Claude 使用指南】，每小节均提供可复制的代码片段。

目录：

1. 工具使用：了解如何将 Claude 与外部工具和功能集成以扩展其功能（包括如何提示 Claude 进行 SQL 查询）

2. 检索增强生成：了解如何从向量数据库、维基百科、特定网页和互联网检索的数据来补充 Claude 的知识

3. 引文：了解如何提示 Claude 在回复中引用来源

4. 子代理：了解如何将 Haiku 作为子代理与 Opus 结合使用

5. 嵌入：了解如何使用 Voyage AI 处理嵌入

6. 与 Claude 一起探索视觉：了解如何有效提示 Claude 解释和分析图表或从表单中提取内容

7. 使用 Claude 生成图像：如何让 Claude 通过 Stable Diffusion 生成图像

8. 将 PDF 上传到 Claude：了解如何解析 PDF 并将其作为文本传递给 Claude

9. 自动评估：了解如何使用 Claude 自动执行即时评估过程

10. 启用 JSON 模式：确保始终使用此快速简便的说明书获取 JSON，或者使用工具来获得结构化输出

11. 使用 Claude 创建审核筛选器：了解如何使用 Claude 为应用程序创建内容审核筛选器

……（持更中）

PS：使用指南前需要注册一个Anthropic API 密钥（免费注册地址： 网页链接 ）

GitHub: 网页链接

本条微博地址 疯狂的我们耶耶耶
啥也干不了一个github搞一天

本条微博地址 桂酒椒浆
我再也不会放开源项目在github了

本条微博地址 是思来又想去
小米14的设备树有大佬在做吗，github上关注了两个项目，都是写了几天就删库跑路了

本条微博地址 occhidio
我姑且也会csdn GitHub ChatGPT一下

本条微博地址 GitHubDaily
分享 GitHub 上一份精选的计算机科学视频课程列表 cs-video-courses。

基本涵盖了计算机方面的所有视频课程，包括计算机科学导论、数据结构和算法、系统编程、软件工程、人工智能、机器学习等。

其中不少都是知名大学的相关公开课程以及各种专业讲师的课程。

GitHub：github.com/Developer-Y/cs-video-courses

列表一直持续定期更新中，已获得了 64.2k Star。

本条微博地址 沉默入射角
草🌿没事封我github账号干什么🖕🏼 🖕🏼 🖕🏼 🖕🏼 毫无预警，神经啊啊啊

本条微博地址 whatsoever8472
发一下疯 github功能实在太强大了！

本条微博地址 宝玉xp