去る10月にUbuntu DiscourseにてNVMe/TCPを使い仮想マシンをストレージレスでUbuntu Server 24.10をブートするというProof of Concept（PoC）デモが紹介されました。NVMe/TCPは2024年3月8日のUbuntu Weekly Topicsでも紹介されているように「iSCSIの後継」といえるものです。 このPoCについては、実際に試せるスクリプト群がGitHubのnvme-tcp-pocレポジトリ（以下、PoCレポジトリ）で公開されています。これを使えば、ネットワークの構成から仮想マシンのセットアップ、Ubuntu ServerのインストールやUEFIの設定までほとんど自動で済んでしまいます。つまり、動かしてみるだけならPoCレポジトリの案内に従えば（あまり問題に遭遇することなく）実現できます。 でも、それでは「なんとなく動いたことは
Lessons from Writing a Compiler
The prototypical compilers textbook is: 600 pages on parsing theory. Three pages of type-checking a first-order type system like C. Zero pages on storing and checking the correctness of declarations (the “symbol table”). Zero pages on the compilation model, and efficiently implementing separate compilation. 450 pages on optimization and code generation. The standard academic literature is most use
「500年後に日本人が佐藤だけになる」という試算の問題と改善 - ill-identified diary
この記事の要約 はじめに 問題点の要約 (追記) 先行研究について GARCH(っぽい)モデルによるシミュレーション シミュレーション前の理論分析 選択的夫婦別姓との比較 (追記) ゴルトン゠ワトソン分枝過程について 使用するデータ シミュレーションの技術的な補足 乱数生成について GARCHモデルの結果 シミュレーションの追試 より複雑なシミュレーションについて 男女別 世代重複 創作苗字 三親等の婚姻禁止ルール より高度な人口学的モデル 結論 2024/4/22: 先行研究とゴルトン゠ワトソン分枝過程の解説の追記 2024/4/23: 多数の言い回しのおかしい箇所の校正 2024/4/24: グラフ上の記載ミスとグラフ描画コードを修正 この記事の要約 先日報道された「500年後に日本人が佐藤だけになる」という試算の内容に違和感を覚えた. 資料を確認してみると, 大きな問題のある方法で試
There are millions of GitHub repos and filtering them is an insane amount of work. It takes a huge time, effort, and a lot more. We have done this for you. In this article, we’ll share a curated list of 100+ widely-known, recommended, and most popular repositories and open source GitHub projects for Machine Learning and Deep Learning. So without further ado, Let’s see all the hubs created by exper
TL;DR; We are changing std::sort in LLVM’s libcxx. That’s a long story of what it took us to get there and all possible consequences, bugs you might encounter with examples from open source. We provide some benchmarks, perspective, why we did this in the first place and what it cost us with exciting ideas from Hyrum’s Law to reinforcement learning. All changes went into open source and thus I can
Today we’re excited to announce the release of TypeScript 4.8! If you’re not yet familiar with TypeScript, it’s a language that builds on JavaScript and adds syntax for types. These types let you put your expectations and assumptions into your code, and those assumptions can then be checked by the TypeScript type-checker. This checking can help avoid typos, calling uninitialized values, mixing up
持ち運べる OpenStack 環境をつくる - NTT docomo Business Engineers' Blog
この記事は、NTT docomo Business Advent Calendar 2025 2 日目の記事です。 Android 15 から Android 端末上で Linux 環境を動かすことが可能になりました。せっかくなので、 OpenStack をインストールして VM を動かしてみました。 はじめに スマホの Linux 開発環境に SSH する 開発環境を探検する OpenStack のインストール方法について DevStack を実行して minimal な OpenStack 環境をつくる スマホ OpenStack に VM を建ててみる トラブルシューティング Linux 開発環境が落ちる VM が boot しない まとめ はじめに こんにちは。 Smart Data Platform (SDPF) クラウド/サーバー 仮想サーバーチームの杉浦 (@Kumassy_
Internet Engineering Task Force (IETF) K. Davis Request for Comments: 9562 Cisco Systems Obsoletes: 4122 B. Peabody Category: Standards Track Uncloud ISSN: 2070-1721 P. Leach University of Washington May 2024 Universally Unique IDentifiers (UUIDs) Abstract This specification defines UUIDs (Universally Unique IDentifiers) -- also known as GUIDs (Globally Unique IDentifiers) -- and a Uniform Resou
Golang Mini Reference 2022: A Quick Guide to the Modern Go Programming Language (REVIEW COPY)
Golang Mini Reference 2022 A Quick Guide to the Modern Go Programming Language (REVIEW COPY) Harry Yoon Version 0.9.0, 2022-08-24 REVIEW COPY This is review copy, not to be shared or distributed to others. Please forward any feedback or comments to the author. • feedback@codingbookspress.com The book is tentatively scheduled to be published on September 14th, 2022. We hope that when the release da
Write queries with Gemini assistance | BigQuery | Google Cloud Documentation
Send feedback Stay organized with collections Save and categorize content based on your preferences. Write queries with Gemini assistance This document describes how to use AI-powered assistance in Gemini in BigQuery to help you query your data with SQL queries and Python code. Gemini in BigQuery can generate and explain queries and code, complete queries and code while you type, and fix code erro
以下の記事が面白かったので、簡単にまとめました。 ・Introducing Structured Outputs in the API 1. Structured Outputs昨年のDevDayで、「JSONモード」を導入しました。これは、OpenAIのモデルを使用して信頼性の高いアプリを構築しようとしている開発者にとって便利な構成要素です。「JSONモード」は、有効なJSON出力を生成するためのモデルの信頼性を向上させますが、モデルの応答が特定のスキーマに準拠することを保証するものではありません。本日、APIに「Structured Outputs」を導入します。これは、モデルによって生成された出力が、開発者が提供するJSONスキーマと完全に一致するように設計された新機能です。 複雑なJSONスキーマのフォローの評価では、「Structured Outputs」を備えた新しいモデル「g
Tier 4 Support § Support for these targets is entirely experimental. If this target is provided by LLVM, LLVM may have the target as an experimental target, which means that you need to use Zig-provided binaries for the target to be available, or build LLVM from source with special configure flags. zig targets will display the target if it is available. This target may be considered deprecated by
Update 1.82.1: The update addresses this security issue. Update 1.82.2: The update addresses these issues. Update 1.82.3: The update addresses this security issue. Downloads: Windows: x64 Arm64 | Mac: Universal Intel silicon | Linux: deb rpm tarball Arm snap Welcome to the August 2023 release of Visual Studio Code. There are many updates in this version that we hope you'll like, some of the key hi
The new Assistants API is a stateful evolution of our Chat Completions API meant to simplify the creation of assistant-like experiences, and enable developer access to powerful tools like Code Interpreter and File Search. Chat Completions API vs Assistants API The primitives of the Chat Completions API are Messages, on which you perform a Completion with a Model (gpt-4o, gpt-4o-mini, etc). It is l
How a simple Linux kernel memory corruption bug can lead to complete system compromise
In this case, reallocating the object as one of those three types didn't seem to me like a nice way forward (although it should be possible to exploit this somehow with some effort, e.g. by using count.counter to corrupt the buf field of seq_file). Also, some systems might be using the slab_nomerge kernel command line flag, which disables this merging behavior. Another approach that I didn't look
Statically typed programming languages can help catch mismatches between the kinds of values a program is intended to manipulate, and the values it actually manipulates. While there have been many bytes spent on discussions of whether this is worth the effort, some programming language designers believe that the type checking in current languages does not go far enough. Koka, an experimental funct
Join a VS Code Dev Days event near you to learn about AI-assisted development in VS Code. Update 1.66.1: The update addresses these issues. Update 1.66.2: The update addresses these security issues. Downloads: Windows: x64 Arm64 | Mac: Universal Intel silicon | Linux: deb rpm tarball Arm snap Welcome to the March 2022 release of Visual Studio Code. There are many updates in this version that we ho
Solving Quantitative Reasoning Problems With Language Models
Solving Quantitative Reasoning Problems with Language Models Aitor Lewkowycz∗, Anders Andreassen†, David Dohan†, Ethan Dyer†, Henryk Michalewski†, Vinay Ramasesh†, Ambrose Slone, Cem Anil, Imanol Schlag, Theo Gutman-Solo, Yuhuai Wu, Behnam Neyshabur∗, Guy Gur-Ari∗, and Vedant Misra∗ Google Research Abstract Language models have achieved remarkable performance on a wide range of tasks that require
A Lisp Interpreter Implemented in Conway’s Game of Life
Lisp in Life is a Lisp interpreter implemented in Conway’s Game of Life. The entire pattern is viewable on the browser here. To the best of my knowledge, this is the first time a high-level programming language was interpreted in Conway’s Game of Life. Running Lisp on the Game of Life Lisp is a language with a simple and elegant design, having an extensive ability to express sophisticated ideas as
Random musings on React, Redux, and more, by Redux maintainer Mark "acemarke" Erikson Detailed thoughts on how React has been developed over time, and explanations for common community confusion and concerns Introduction 🔗︎ Today, the state of React and its ecosystem is complicated and fractured, with a mixture of successes, skepticism, and contention. On the positive side: React is the most wide
High Assurance Rust
Press ← or → to navigate between chapters Press S or / to search in the book Press ? to show this help Press Esc to hide this help This book is an introduction to building performant software we can justifiably trust. That means having sufficient data to support confidence in our code's functionality and security. Trustworthiness is a hallmark of high assurance software. With assurance as our driv
I see people make the same mistakes over and over again when learning Rust. Here are my thoughts (ordered by importance) on how you can ease the learning process. My goal is to help you save time and frustration. Let Your Guard Down Stop resisting. That’s the most important lesson. Accept that learning Rust requires adopting a completely different mental model than what you’re used to. There are a
Aug 6, 2023 People sometimes ask me: “Alex, how do I learn X?”. This article is a compilation of advice I usually give. This is “things that worked for me” rather than “the most awesome things on earth”. I do consider every item on the list to be fantastic though, and I am forever grateful to people putting these resources together. Learning to Code I don’t think I have any useful advice on how to
At Endcrawl we're always thinking about the hard work that goes into making film and TV, and how that work translates to on-screen credits. A feature film may involve thousands of people, hundreds of distinct job titles or "roles," and dozens of departments. So there's plenty for a producer to worry about, like: Did we forget or misspell a name? Is this the correct way to credit that role? Do all
I’m a fairly frequent Hacker News lurker, especially when I have some other important task that I’m avoiding. I normally head to the Active page (lots of comments, good for procrastination) and pick a nice long discussion thread to browse. So over time I’ve ended up with a good sense of what topics come up a lot. “The Bay Area is too expensive.” “There are too many JavaScript frameworks.” “Bootcam
17 types of similarity and dissimilarity measures used in data science. | Towards Data Science
The following article explains various methods for computing distances and showing their instances in our daily lives. Additionally, it… Various ML metrics. Inspired by Maarten Grootendorst. "There is no Royal Road to Geometry." – Euclid Quick note: Everything written and visualized has been created by the author unless it was specified. Illustrations and equations were generated using tools like
Part1 なにはなくともEDA＆ベースモデルつくりから！ Shimpei Ikeno 2022-07-12 本連載の目的：実践的な”多系列”時系列予測モデルの解き方を紹介 みなさんはじめまして。NRIのデータサイエンティスト、時系列予測プラクティスチームの池野です。Wikipediaによれば、時系列とは、“ある現象の時間的な変化を、連続的に（または一定間隔をおいて不連続に）観測して得られた値の系列（一連の値）のこと”をさします。時系列予測の大家であるRob J. Hyndman教授によれば、予測とは、“将来を、過去のデータや影響を与える将来のイベントなどの活用可能な情報に基づいて、できるだけ正確に見通すこと”とあります。したがって、時系列予測は、時間的な変化の観測結果に基づき将来をできるだけ正確に見通す取組といえましょう。時系列予測モデルは、そのような時間的変化の観測結果からパターンを見
はじめに 機械学習エンジニアの大庭です。普段はマイクロアドが提供する広告配信プラットフォーム UNIVERSE Ads に接続する機械学習 API の研究開発をしています。 マイクロアドでは、機械学習モデルの学習側との連携が容易なこととメンテナンス性を重視して Python で機械学習 API を実装しています。Python は使いやすい反面、基本文法は速いとは言えない言語です。そのため、実行時間制約の厳しい Real Time Bidding (RTB) のなかで使うには高速化を意識しておく必要があります。今回は様々ある Python の高速化手法の理解と整理のため記事にしました。 個人的にですが、Python の高速化は以下の手順で行っていくのがいいと思っています。この記事では、この手順毎に便利なツールやライブラリをまとめました。 ボトルネックの特定 計算量（オーダー）を減らす コード
Database Fundamentals
About a year ago, I tried thinking which database I should choose for my next project, and came to the realization that I don't really know the differences of databases enough. I went to different database websites and saw mostly marketing and words I don't understand. This is when I decided to read the excellent books Database Internals by Alex Petrov and Designing Data-Intensive Applications by
Amazon FSx for NetApp ONTAPファイルシステム上のiSCSI LUNをマウントしてみた | DevelopersIO
Amazon FSx for NetApp ONTAPは単純なファイルサーバーじゃないぞ こんにちは、のんピ(@non____97)です。 皆さんはMulti-AZのEBSボリュームを欲しいなと思ったことはありますか? 私はあります。 EBSボリュームはAZ単位なのでAZ障害のことを考えるとちょっと心配です。かと言って自分でブロックレベルのレプリケーションを実装するのも何だか大変です。 そこで、Amazon FSx for NetApp ONTAPの出番です。 Amazon FSx for NetApp ONTAPはファイルサーバーとしての機能だけではなく、ブロックストレージとしての機能も有しています。 Q: Amazon FSx for NetApp ONTAP はどのプロトコルをサポートしていますか? A: Amazon FSx for NetApp ONTAP は、ネットワークファイ
整数計画法メモ トップページへ戻る 本ページのURLが https://www.tuat.ac.jp/~miya/ipmemo.html から https://web.tuat.ac.jp/~miya/ipmemo.html へ変更になりました． それに応じて，本ページからリンクされているダウンロード可能なファイルについても，URLが変更になっています． はじめに このページには，数理最適化問題，特に整数最適化問題（整数計画問題）をソルバーで解く際に，知っていると役に立つかもしれない情報を雑多に記しています． 数理最適化および整数最適化（整数計画法）は強力な最適化手法の一つなのですが，「実際に解きたい時に日本語の情報があまり無い」と耳にしたのがこのページを作ったきっかけです． おことわり このページに書いてある情報は無保証であり，筆者は一切の責任を持ちません． 自己責任でご利用ください．
Type Parameters Proposal
Ian Lance Taylor Robert Griesemer August 20, 2021 StatusThis is the design for adding generic programming using type parameters to the Go language. This design has been proposed and accepted as a future language change. We currently expect that this change will be available in the Go 1.18 release in early 2022. AbstractWe suggest extending the Go language to add optional type parameters to type an
Exploiting Authentication in AWS IAM Authenticator for Kubernetes
Exploiting Authentication in AWS IAM Authenticator for Kubernetes Amazon Elastic Kubernetes Service (Amazon EKS) is a managed service that helps you to create, operate, and maintain Kubernetes clusters. Amazon EKS has several deployment options including AWS cloud and on-premises (Amazon EKS Anywhere). Amazon EKS uses IAM to provide authentication to the cluster through the AWS IAM Authenticator f
Python behind the scenes #11: how the Python import system works
If you ask me to name the most misunderstood aspect of Python, I will answer without a second thought: the Python import system. Just remember how many times you used relative imports and got something like ImportError: attempted relative import with no known parent package; or tried to figure out how to structure a project so that all the imports work correctly; or hacked sys.path when you couldn
Update 1.73.1: The update addresses these issues. Downloads: Windows: x64 Arm64 | Mac: Universal Intel silicon | Linux: deb rpm tarball Arm snap Welcome to the October 2022 release of Visual Studio Code. There are many updates in this version that we hope you'll like, some of the key highlights include: Search include/exclude folders - Quickly set folders to include/exclude in the tree view. Comma
After a long time it’s time for a big upgrade of my computer hardware orchestra. Here it is! The bigger and better Floppotron 3.0. 512 floppy disk drives, 4 scanners and 16 hard disk drives. My noise-making contraption grew a little bit since last update. It has its own „studio” space and became a relatively complex device. There is a ton of cables, a lot of custom electronic circuits, but the who
Quickly build high-accuracy Generative AI applications on enterprise data using Amazon Kendra, LangChain, and large language models | Amazon Web Services
Artificial Intelligence Quickly build high-accuracy Generative AI applications on enterprise data using Amazon Kendra, LangChain, and large language models June 2023: This post was updated to cover the Amazon Kendra Retrieve API optimized for RAG use cases, and Amazon Kendra retriever now being part of the LangChain GitHub repo. This revision also updates the instructions to use new version sample
2024-01-20 Discussion on HackerNews and Lobsters. Roughly a year ago I moved into my new apartment. One of the reasons I picked this apartment was age of the building. The construction was finished in 2015, which ensured pretty good thermal isolation for winters as well as small nice things like Ethernet ports in each room. However, there was one part of my apartment that was too new and too smart
An AI-native software engineer is one who deeply integrates AI into their daily workflow, treating it as a partner to amplify their abilities. This requires a fundamental mindset shift. Instead of thinking “AI might replace me” an AI-native engineer asks for every task: “Could AI help me do this faster, better, or differently?”. The mindset is optimistic and proactive - you see AI as a multiplier
Pandas is a very popular tool for data analysis. It comes built-in with many useful features, it's battle tested and widely accepted. However, pandas is not always the best tool for the job. SQL databases have been around since the 1970s. Some of the smartest people in the world worked on making it easy to slice, dice, fetch and manipulate data quickly and efficiently. SQL databases have come such
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第843回 UbuntuでNVMe over TCPを試す | gihyo.jp
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