¿Conoces mi sitio web? y ¿Qué te parece su aspecto visual y su contenido? Dame una #sugerencia, #observación, #consejo o #critica que me haga mejorar? #Linux #Linuxverso #Educacion #STEAM #Ciencia #Tecnologia #IA #AI #InteligenciaArtificial #Robotica - proyectotictac.com/

ESP32 这两周是真火，乐鑫自己都下场做了模拟器。 我把能找到的 ESP32 模拟器翻了一遍，挑出 3 个，又用自己的固件实测了一下官方那个模拟器，手里还没板子的先收藏👇 1. Velxio（3.3k 星，AGPL） 浏览器里拖线画电路，40 块板，ESP32 到 C6 都有。ESP32 系列在服务器上跑 QEMU，再把引脚和串口推回网页，也能自己部署。 github.com/davidmonterocresp… 2. esp32sim（364 星，MIT） 从芯片自带的 ROM 一路启动，屏幕、触摸、摄像头、声音都做了，S3 最成熟，连 Linux 都跑起来了。网页版打开就能玩。 github.com/mikroverk/esp32si… 3. 乐鑫官方 esp-emulator（190 星） 芯片最全：C3、C5、C6、H2、P4、S3，蓝牙、Thread、GDB 都有，本地版还能连真实互联网。 有三点要知道：经典 ESP32 不在列表里；网页版不联网；仓库目前只放了二进制，开不开源，官方在 issue 里回复还没决定。 github.com/espressif/esp-emu… 官方那个我拿自己的验收固件跑了一遍：点灯、双核、NVS、PSRAM、LVGL 都能跑，芯片和协议做得很全，但是外设这块还得等等。 最后预告一下我自己在做的：试板 TryBoard。 同样在浏览器里跑你编译好的 ESP-IDF / Arduino 固件（C3、S3），全在本地跑。板子、面包板、OLED、灯带、舵机摆在 3D 实验台上，跑完就知道该买哪块板🫡

Colorfigures skill work in progress update 👀 3D: you can drag a figure to turn it around See-through: look inside how the mechanism works Labelled: every part lights up as it does its job Here’s the demo video of washing machine doing a full wash cycle

Introducing FerroUI a cross-platform UI framework for Rust: a retained-mode control library with a styled property system, data binding, XAML markup, control themes and a composition-based renderer. A port of Avalonia. github.com/wieslawsoltes/Fer…

Linux phones: could they finally become a real alternative to Android and iOS? After years of stagnation, Linux phones may be approaching a turning point. In a recent article, Amos Batto explains how new hardware options, more mature interfaces like Phosh and Plasma Mobile, and tools such as Waydroid could make Linux phones more practical. But better technology alone won’t be enough. Projects like PINE64 and Purism have faced serious challenges. Building a phone is one thing; funding software development, maintaining hardware support and keeping a company afloat are much harder. Jolla’s latest phone also suggests there is a market for alternatives, particularly among people who want more control over their devices. Linux phones don’t need to replace Android or iOS to matter. They need to become a practical option for people who value privacy, software freedom and digital sovereignty. Would you consider switching to a Linux phone if it supported the apps and features you rely on every day? amosbbatto.wordpress.com/202… #Linux #LinuxPhone #Privacy #FOSS

Open source parametric 3D CAD written in pure Rust with constraint-based sketching and a feature timeline that rebuilds when parameters change

Have you tried this new free, open-source office suite alternative yet? A familiar MS Office experience with docs, sheets, and slides, optimized for performance and self-hosting via Docker or Nextcloud. Made in France 🇫🇷

Love this! This is how I wish someone had explained physics to me. I've been exploring the same idea with Claude! A skill for making everyday machines you can play with. Here's my little pencil sharpener. Two cutters orbit the pencil like planets and 12 turns of the crank make the point :) visual-learning.app

Un sabio es quien ha trascendido la inmediatez de la lujuria, al descubrir que la mente posee placeres más vastos.

Ubuntu 26.04 LTS on a Xiaomi 12T Pro, running on the mainline Linux kernel. The developer reports that most functions are working, including calls, navigation and YouTube. After a day of use and a few reboots, the battery was still at 50%. The project also targets the Redmi K50 Ultra and provides the sources needed to build your own image. It's an interesting experiment in bringing native Linux to smartphone hardware, beyond the usual Android-based alternatives. github.com/royka1/diting-ubu… Would you try Linux on a spare smartphone just to explore what's possible? #Linux #Ubuntu #MobileLinux

把手机直接变成一台随身携带的 Linux 电脑？开源社区最近又搞出了一个硬核神器——DroidDesk。 看到 GitHub 上已经冲到将近 4k Star 的 DroidDesk 仓库，彻底颠覆了很多人对“手机跑 Linux”就是开个黑框终端或套壳慢速模拟器的印象。 它的核心亮点非常直接：直接调用手机内核，零仿真、无中间转译损耗，实现近乎原生的运行性能。手机连上显示器和键鼠，瞬间变成完整的 Linux PC；拔掉线带走，整个工作环境毫秒不差地跟着你。 具体能跑什么？ 生产力与开发：完整的桌面级 VS Code（支持 Python、各类扩展及调试）、LibreOffice 办公套件。 安全与终端：开箱即用的 Wireshark 原生抓包分析、Metasploit 渗透测试框架。 AI 与本地大模型：终端直接跑 Claude Code 编码代理，甚至支持离线本地 LLM 推理（实测 5+ token/s），无需任何外部 API。 图形与渲染：内置了独立 Termux:X11 渲染架构（非发热卡顿的 VNC 方案）。搭载高通骁龙（Adreno）的机型还可开启 Turnip/Zink 硬件加速，连 Blender 都能直接安装并打开。 对免 Root 用户，它利用专属原生 userspace 搭配 X11/TUR 源自动化部署桌面（XFCE4/LXQt/MATE/KDE）；Root 用户更可以直接跑 chroot 完整 Ubuntu 根文件系统。只要手里有一台 ARM64 的安卓设备，插上便携屏，真正的“移动口袋工作站”时代可能真被开发者们一点点搓出来了。 喜欢折腾安卓与 Linux 融合生态的极客，建议直奔 Releases 刷个包体验一下！ github.com/orailnoor/DroidDe…

TERSİNE MÜHENDİSLİKLE İLGİLENENLER İÇİN GERÇEK BİR HİLE KODU 🔓🔥 Bir geliştirici, yapay zeka ajanlarının yazılım ve donanımları parçalarına ayırdığı tüm vakaları topluyor ve sayı şimdiden 286'ya ulaştı. Bunların 119'u, Claude Code ve Codex gibi ajanlara gerçek tersine mühendislik araçları kazandıran açık kaynaklı MCP aracı **REA** ile yapıldı. İşte listeden dikkat çekenler: → **67 Oyun:** Eski DOS dosyalarından 17 ajanın decompile ettiği Modern Warfare 2'ye kadar. → **64 Cihaz ve Donanım:** Mac menü çubuğundan kontrol edilebilen akıllı klozet dahil akıllı cihaz ürün yazılımları. → **128 Masaüstü ve Mobil Uygulama:** Yeniden inşa edilen veya açılan popüler yazılımlar. → **27 Algoritma:** Doğrudan ikili (binary) dosyalardan kurtarılan özel algoritmalar. Her kayıt hangi aracın kullanıldığını, sonucun onaylanıp onaylanmadığını belirtiyor ve liste günde 6 kez güncelleniyor. Tipik bir REA süreci nasıl işler? → REA, kodlama ajanınıza bir MCP olarak bağlanır. → Ajan ikili dosyayı haritalandırır ve fonksiyonları bulur. → Çalışma zamanı izlemeleri her fonksiyonun ne yaptığını doğrular. → Ajan özelliği yeni kod olarak yeniden inşa eder ve orijinaliyle karşılaştırarak test eder. Claude Code'a şunu yapıştırın: > "Install the REA reverse engineering MCP. Pick one small app I own, map its binary, trace the function behind one feature and rebuild that feature as a standalone script with a test that compares it to the original. Show me the plan first, no edits until I say go." GitHub: github.com/songshikang0111/a… Bu paylaşımı kaydet, tersine mühendislikteki bu devrimi kaçırma. KAYDET ve PAYLAŞ 📌 @DeepTechTR

There are more operating systems than just Linux. Here's a list of a few that are under active development. itsfoss.com/open-source-non-…

One of the best file manager alternatives for Windows, open source and completely free, with tabs, dual-pane view, column navigation, file tagging, QuickLook and muuuch more!

Today is my birthday. Here's my gift to you all. Introducing: Muxin - one app for all my computers. Macs, Linux servers, Windows PCs, cloud machines. I run AI coding agents on all of them from one window, and my agents can use it too. Free and open source. 🧵

ElixirOffice: la alternativa gratuita a Microsoft Office creada con IA Gaël Duval ha creado ElixirOffice, una alternativa gratuita y de código abierto a Microsoft Office desarrollada con IA y compatible con Windows, Linux y macOS blog.elhacker.net/2026/10/el…

Link to the original Marble Curriculum: withmarble.com/curriculum/

Wow. I woke up to an impressive number of upset people who apparently don’t understand how LLMs work and can’t cope well with me pointing it out. An LLM is a statistical next-token prediction model. That’s how it works. It’s an extraordinarily sophisticated calculator performing math you could theoretically do by hand (if you were sufficiently masochistic). Math doesn’t know what it’s calculating. Pi doesn’t spend its evenings contemplating the nature of circles, and c doesn’t ponder the relationship between matter and energy. That doesn’t make the results any less accurate, impressive, or useful. Between inference requests, an LLM isn’t sitting around thinking. It isn’t reconsidering its answers, wondering whether it made a mistake, contemplating its existence, or questioning whether it’s conscious. Its weights remain fixed (it doesn’t learn), and computation resumes when it receives input. We know this because we designed these systems. The architectures, mathematics, implementations, and research are extensively documented. You can study them yourself. Of course, some people immediately lean into comparisons of biological intelligence or philosophical debates over consciousness because that is what they know. But biological intelligence and artificial neural networks are fundamentally different systems. Similar outputs don’t establish equivalent internal experiences. I experience consciousness directly. I infer that other humans do too because we share biological structures and processes. We don’t have equivalent evidence for an LLM, and nothing about its known operation gives evidence of conscious experience. Which brings me back to my original point. To me, understanding is conscious comprehension. It means being aware of information, recognizing its meaning, and experiencing that comprehension. If I wasn’t conscious I could not understand. We can perform actions unconsciously. We can produce correct results without knowing why they’re correct. But I distinguish those capabilities from consciously understanding what we’re doing. An LLM can solve complex problems, explain difficult concepts, and produce remarkably accurate information. I give it full credit for those capabilities. But producing an answer that we rationalize as understanding isn’t the same as experiencing understanding. You don’t have to agree with my definitions. We can debate functional understanding versus conscious comprehension all day, but that won’t establish whether an LLM actually experiences anything. The right debate is this… Could machines exhibit something different from human consciousness, something measurable, meaningful, and worth studying? I think so, absolutely! I’m entirely open to discussing “machine consciousness” in terms of observable, testable computational properties. We built these systems, we can instrument them, examine their internal mechanisms, and investigate what they’re capable of. That seems far more productive than endlessly arguing over whether a machine experiences life the way humans do. So here’s my question: How would you define machine consciousness, and more importantly, how would you measure it?

You can now run the biggest open AI models on a 4 GB graphics card. AirLLM loads a model one layer at a time instead of all at once, so it fits in a tiny amount of video memory: → Kimi K3, 2.8 trillion parameters, in 3.72 GB → DeepSeek-V3, 671 billion parameters, in about 12 GB → 70B models on a single 4 GB card, without quantizing them → It can now fine-tune a 125B model in under 6 GB, too pip install airllm, then load almost any model from Hugging Face in one line. It trades speed for memory, and you need plenty of disk space for the model files. 38K+ GitHub stars. Apache-2.0. github.com/lyogavin/airllm

Hugging Face y el equipo de Llama han lanzado Llama Windows, una aplicación gratuita y de código abierto que permite descargar y utilizar modelos de IA locales con un solo clic desde el repositorio de Hugging Face blog.elhacker.net/2026/10/ia…

🐺💻ElixirOffice, discover the modern suite created by Gaël Duval, the creator of Mandrake Linux. 📦 Install it with: sudo apt install elixiroffice-desktop 🔗More info: github.com/leag1234/elixirof… #VendefoulWolf #ElixirOffice #Linux #OpenSource