AGLコミュニティは、8/9-10に台湾の台北で行われるCOSCUPでSDVに関するトラックと展示を行う予定です。詳細は追ってアナウンスします！ COSCUPに興味がある方は、coscup.org/2025/を参照ください。 #COSCUP

在嵌入式板子上跑開源，真的沒你想的那麼簡單—— 尤其是當你還想讓 AI 在裝置端跑得順！ SoC 周邊搞不懂、相容性踩雷、授權流程又卡關？ 這些痛點，Sparrow Hawk 開發板通通幫你踩過去了。由 Renesas 與台灣團隊 Retronix 聯手推出，針對開源友善打造，不只免 NDA、不用授權費，還給你 30 TOPS AI 加速力、多鏡頭支援直接上！ 這場我們會實際帶你看看它怎麼搭配開源工具，從硬體架構到開發環境都怎麼設計，幫助嵌入式 AI 開發者不再原地卡關。想把開源推進邊緣運算世界的你，千萬別錯過。 技術演講 | 8/9（六）11:20~11:50 @ TR411 Open Source Hardware/Software Collaboration by Renesas & Retronix 📌 感謝 Retronix 成為 COSCUP 的贊助夥伴！ 📍 會期兩日 Retronix 也有設置攤位，歡迎前往現場交流，了解更多關於 Sparrow Hawk 與 Retronix 的資訊！ 📍 歡迎至部落格閱讀完整文章：blog.coscup.org/2025/07/Spar… #COSCUP20週年 #COSCUPxRubyConfTW2025 #COSCUP2025 #RubyConfTW #Retronix #Sponsor

一昨日になってしまいましたが、登壇資料アップロードしました！ #oteljp ML Pipelineの開発と運用を OpenTelemetryで繋ぐ @ OpenTelemetry Meetup 2025-07 speakerdeck.com/getty708/ml-…

The OpenChain and friends event is about to start and we're more than just ready! Not joining yet? Hurry up and head over to openchainproject.org/news/20…. Huge thanks to our community enthusiasts Jan, Josef (not picture), Sussan and Thomas❤️

OpenTelemetry の GenAI SIG 紹介のブログ記事を日本語化しました。大事なので。 #opentelemetry opentelemetry.io/ja/blog/202…

共通約数があるものには引力を、互いに素なものは斥力を働かせるというシンプルなプログラムを作ってみたら、決して安定しないものが生まれた。複雑な人間模様を見ているよう・・

DRAを使ってSR-IOV VF, RDMA NIC等をPodに刺すプラグイン。Multi Networkのユースケースの中でもこれらのケースだとNetworkPolicyとかServiceとかはいらないだろうからいい落とし所かもしれない。Multusとかにあったスケジューリングの問題もDRAだからクリアできている。 github.com/google/dranet

Cats are invariant under SO(3) transformations! 😼

UNIX開発史、Space Travel、AT&T社内GE機撤去に関し独自に研究された良記事です。私のいんちき話の (1)「UNIX誕生の主たる動機はSpace Travel」(2)「GE機を会社が撤去しようとしたことが重要な契機」説は誤りだという大変素晴らしい分析です。関連の参考書籍2件も紹介します。 qiita.com/ko1nksm/items/1b11…

UNIXの起源面白い #devsumi

Debian Celebrates 31 years! dlvr.it/TC1BmX

ブログ書きました： オープンソースとは違う新しい取り組み「Fair Source」登場。ビジネスの持続性とソースコード公開の両立を目指す publickey1.jp/blog/24/fair_s…

各プロセッサのメモリオーダリングについては昔調べたのでよかったらどうぞ keisanki.blog.jp/archives/15… #kernelvm

NW subsystem の Big Kernel Lock こと rtnl_mutex について LPC 2024 で話します 今回も AWS ならでは？の話で、シングルホスト上で 2K の netns 内にそれぞれ ~10 個のデバイスを作る処理がほとんどシリアライズされてめちゃくちゃ時間がかかる問題への解決策を提案します lpc.events/event/18/contribu…

|￣￣￣￣￣￣￣￣￣￣￣￣￣￣￣￣￣| | Don't Push To Production On Friday | |＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿＿| \ (•◡•) / \ / —— | | |_ |_

A common learning mistake - jumping to "hot" advanced topics and skipping the "boring" fundamentals. ❌ Service Mesh, Ingress Controller, Gateway API ✅ Writing a simple web server to play with sockets iximiuz.com/en/posts/writing…

SSH Tunnels Cheat Sheet 🔽 I've put together a visual memo on how to publish local and remote ports using nothing but a standard SSH client and server.

Things Every Developer Should Know: Concurrency is 𝐍𝐎𝐓 parallelism. In system design, it is important to understand the difference between concurrency and parallelism. As Rob Pyke(one of the creators of GoLang) stated:“ Concurrency is about 𝐝𝐞𝐚𝐥𝐢𝐧𝐠 𝐰𝐢𝐭𝐡 lots of things at once. Parallelism is about 𝐝𝐨𝐢𝐧𝐠 lots of things at once." This distinction emphasizes that concurrency is more about the 𝐝𝐞𝐬𝐢𝐠𝐧 of a program, while parallelism is about the 𝐞𝐱𝐞𝐜𝐮𝐭𝐢𝐨𝐧. Concurrency is about dealing with multiple things at once. It involves structuring a program to handle multiple tasks simultaneously, where the tasks can start, run, and complete in overlapping time periods, but not necessarily at the same instant. Concurrency is about the composition of independently executing processes and describes a program's ability to manage multiple tasks by making progress on them without necessarily completing one before it starts another. Parallelism, on the other hand, refers to the simultaneous execution of multiple computations. It is the technique of running two or more tasks or computations at the same time, utilizing multiple processors or cores within a computer to perform several operations concurrently. Parallelism requires hardware with multiple processing units, and its primary goal is to increase the throughput and computational speed of a system. In practical terms, concurrency enables a program to remain responsive to input, perform background tasks, and handle multiple operations in a seemingly simultaneous manner, even on a single-core processor. It's particularly useful in I/O-bound and high-latency operations where programs need to wait for external events, such as file, network, or user interactions. Parallelism, with its ability to perform multiple operations at the same time, is crucial in CPU-bound tasks where computational speed and throughput are the bottlenecks. Applications that require heavy mathematical computations, data analysis, image processing, and real-time processing can significantly benefit from parallel execution. -- Subscribe to our weekly newsletter to get a Free System Design PDF (158 pages): bit.ly/3KCnWXq

If the result confirms the hypothesis, then you've made a measurement. If the result is contrary to the hypothesis, then you've made a discovery. - Enrico Fermi

Visualization of Euler's polyhedron formula: V - E F = 2 or Vertices - Edges Faces = 2 [🎞️ Beau Janzen / reason4math] x.com/i/status/1774087987640…