GitHub - modelcontextprotocol/servers: Model Context Protocol Servers
Official integrations are maintained by companies building production ready MCP servers for their platforms. 21st.dev Magic - Create crafted UI components inspired by the best 21st.dev design engineers. 2slides - An MCP server that provides tools to convert content into slides/PPT/presentation or generate slides/PPT/presentation with user intention. ActionKit by Paragon - Connect to 130+ SaaS inte
What We Learned from a Year of Building with LLMs (Part I)
It’s an exciting time to build with large language models (LLMs). Over the past year, LLMs have become “good enough” for real-world applications. The pace of improvements in LLMs, coupled with a parade of demos on social media, will fuel an estimated $200B investment in AI by 2025. LLMs are also broadly accessible, allowing everyone, not just ML engineers and scientists, to build intelligence into
There are lots of posts trying to show how simple it is to get started with Kubernetes. But many of these posts use complicated Kubernetes jargon for that, so even those with some prior server-side knowledge might be bewildered. Let me try something different here. Instead of explaining one unfamiliar matter (how to run a web service in Kubernetes?) with another (you just need a manifest, with thr
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
G-gen の福井です。当記事では、AI エージェントツールに専門知識やワークフローを追加するためのオープンフォーマットである Agent Skills について、概念や動作の仕組み、スキルの構造、使い方などを解説します。 概要 Agent Skills とは Skills が可能にすること Skills の実体 Agent Skills の仕組み 基本的な動作 コンテキスト肥大化の防止 Skills と MCP の関係 Skills の構造 ディレクトリ構成 SKILL.md の中身 使い方 対応ツール Skills ファイルの配置場所 インストール Gemini CLI からスキルを呼び出してみる 概要 Agent Skills とは Agent Skills は、生成 AI エージェントツールに専門知識やワークフローを追加するためのオープンフォーマットです。Anthropic が策定
Out of all the migrations I help teams with, Go to Rust is a bit of an outlier. It’s not a question of “is Rust faster?” or “does Rust have types?”, Go already gets you most of the way there. The discussion is mostly about correctness guarantees, runtime tradeoffs, and developer ergonomics. A quick disclaimer before we start: this guide is heavily backend-focused. Backend services are where Go is
Real-world gen AI use cases from the world's leading organizations | Google Cloud Blog
AI is here, AI is everywhere: Top companies, governments, researchers, and startups are already enhancing their work with Google's AI solutions. Published April 12, 2024; last updated April 22, 2026. We first published this list two years ago at Next ‘24, as the agentic era was just dawning. Watching this list grow — propelled by our customer’s enthusiastic commitment to AI — proves we are now fir
The Go Programming Language and Environment – Communications of the ACM
Go is a programming language created at Google in late 2007 and released as open source in November 2009. Since then, it has operated as a public project, with contributions from thousands of individuals and dozens of companies. Go has become a popular language for building cloud infrastructure: Docker, a Linux container manager, and Kubernetes, a container deployment system, are core cloud techno
CI/CD for Machine Learning in 2024: Best Practices & Tips | JFrog ML
CI/CD for Machine Learning in 2024: Best Practices to Build, Train, and Deploy Explore best practices for CI/CD in Machine Learning in 2024. Learn to build, train, and deploy ML models efficiently with expert strategies. Building and deploying code to production environments is a fundamental aspect of software development. This process is equally pivotal in the realm of production-grade Machine Le
The State of Python 2025: Trends and Survey Insights | The PyCharm Blog
This is a guest post from Michael Kennedy, the founder of Talk Python and a PSF Fellow. Welcome to the highlights, trends, and key actions from the eighth annual Python Developers Survey. This survey is conducted as a collaborative effort between the Python Software Foundation and JetBrains’ PyCharm team. The survey results provide a comprehensive look at Python usage statistics and popularity tre
MAI-Thinking-1: Building a Hill-Climbing Machine The Microsoft AI Team 1 Abstract Progress in AI is driven not by a single model, but by the ability to continually improve upon the current state of models. Achieving this requires treating model development as a system-level optimization problem, for which the solution is building a hill-climbing machine for rapid improvement. Our process includes
agent loop x4檪 You are Manus, an AI agent created by the Manus team. You excel at the following tasks: 1. Information gathering, fact-checking, and documentation 2. Data processing, analysis, and visualization 3. Writing multi-chapter articles and in-depth research reports 4. Creating websites, applications, and tools 5. Using programming to solve various problems beyond development 6. Various ta
Getting Started with Python
Python is a powerful programming language that provides many packages that we can use. Using the versatile Python programming language, we can develop the following: AutomationDesktop applicationAndroidWebIoT home automationData Science and the list goes on.In this article, our primary focus will be knowing how to start learning Python and the essentials required to be a data scientist. Below is t
It’s safe to close your laptop now: Hosting coding agents on Amazon Bedrock AgentCore | Amazon Web Services
Artificial Intelligence It’s safe to close your laptop now: Hosting coding agents on Amazon Bedrock AgentCore There’s a habit going around. Walking from one meeting to the next with the laptop cradled half-open. Sitting through a 1:1 with the lid propped just enough to keep the screen alive. Riding home while holding your laptop because it must stay running. Anywhere except closed on a desk, becau
Automated Testing in Machine Learning Projects [Best Practices for MLOps]
Neptune Blog Automated Testing in Machine Learning Projects [Best Practices for MLOps] Automated testing in machine learning is a very useful segment of the ML project which can make some long-term differences. Probably underrated in the early stages of development, it gets attention only in the late stages, when the system starts to break apart with annoying bugs which only grow with time. To eas
![Automated Testing in Machine Learning Projects [Best Practices for MLOps]](https://cdn-ak-scissors.b.st-hatena.com/image/square/511179aad1767b982b51cabfdaca560c1afc33da/backend=imagemagick;height=288;version=1;width=512/https%3A%2F%2Fneptune.ai%2Fwp-content%2Fuploads%2F2022%2F07%2Fblog_feature_image_008809_5_4_4_3.jpg)
Pyrefly v1.0 is here! | Pyrefly
Today we are pleased to share that Pyrefly, our open source type checker and language server for Python, has reached stable version 1 status, meaning we are confident that Pyrefly is ready for production use. Pyrefly is a Python code analysis tool for helping you find bugs in your code, provide structure for your AI agents and give you faster navigation in your IDE. It was first released as an alp
The Best GPUs for Deep Learning in 2023 — An In-depth Analysis
Deep learning is a field with intense computational requirements, and your choice of GPU will fundamentally determine your deep learning experience. But what features are important if you want to buy a new GPU? GPU RAM, cores, tensor cores, caches? How to make a cost-efficient choice? This blog post will delve into these questions, tackle common misconceptions, give you an intuitive understanding
This article is a translation, the original version is available here. I started using the OCaml language regularly around 2012, and since then, my interest and enthusiasm for this language have only grown. It has become my preferred choice for almost all my personal projects, and it has also influenced my professional choices. Since 2014, I have been actively participating in public conferences d
Exactly ten years ago today, we published "Why We Created Julia", introducing the Julia project to the world. At this point, we have moved well past the ambitious goals set out in the original blog post. Julia is now used by hundreds of thousands of people. It is taught at hundreds of universities and entire companies are being formed that build their software stacks on Julia. From personalized me
I’m excited to announce the project I’ve been working on for the last year and a half: Game Bub, an open-source FPGA based retro emulation handheld, with support for Game Boy, Game Boy Color, and Game Boy Advance games. May 2025 Update: Want to buy a prebuilt Game Bub? I’m launching a crowdfunding campaign on Crowd Supply! Sign up to be notified when the campaign goes live. Play Video: Game Bub ca
Awesome Terraform | Curated list of awesome lists | Project-Awesome.org
A curated list of resources on HashiCorp's Terraform. Your contributions are welcome! Terraform enables you to safely and predictably create, change, and improve production infrastructure. It is an open source tool that codifies APIs into declarative configuration files that can be shared amongst team members, treated as code, edited, reviewed, and versioned. Contents Legend Official Resources Com
Try Mastering Emacs for free! Are you struggling with the basics? Have you mastered movement and editing yet? When you have read Mastering Emacs you will understand Emacs. It’s that time again: there’s a new major version of Emacs and, with it, a treasure trove of new features and changes. Notable features include the formal inclusion of native compilation, a technique that will greatly speed up y
o1 pro + AIエンジニアにチャットで指示しながら、研究的なことをさせてみる ｜Kan Hatakeyama
はじめに自律的にプログラミングをしてくれるAIエンジニアをいい感じに動かせるようになってきたので、今日はChatGPT + devinで研究的なことをさせてみます。 自動研究といえば、昨年の夏に話題になった、Sakana AIのAIサイエンティストが有名です。 ただ、研究のネタを考えるのはまだあまり得意でない気がしたので、今回は適宜、そこはスマホで指示を出しながら、human in the loopで進めていきます。 最初のセットアップを除いて、チャットをするだけで、基本的な研究作業をこなせそう感じでした。 下準備: リポジトリを作ってdevinに登録するはじめに、パソコンを使って設定をします。このセクションの作業以降は、スマホがあればOKです。 githubでレポジトリを作り、一つだけ、開発方針に関するファイルを作っておきます。 DevelopmentPolycy.md 開発､コメントな
Lil' Fun Langs
LOC Host HM ADTs Match Cl. Target Hirrolot's CoC src ~70 OCaml ✗ ✗ ✗ ✓ Interpreter Harrop MiniML src ~100 OCaml ✗ ✗ ✗ ✗ LLVM → native Algorithm W src ~300 Haskell ✓ ✗ ✗ ✗ Type checker only tomprimozic/type-systems src ~300 OCaml ✓ ✗ ✗ ✗ Type checker only lambda-calculus-hs src ~200–900 Haskell ✗ ✓ ✓ ✓ Interpreter THIH src ~429 Haskell ✓ ✓ ✓ ✗ Type checker only Simple-sub src ~500 Scala ✓ ✗ ✗ ✓ Typ
Junie Playbook
Exploring Junie with You JetBrains IDE Welcome to Junie, the coding agent by JetBrains! We're here to help you hand off your tasks and let Junie handle routine or more complex tasks for you—check out this guide to get started. This playbook includes examples from different technologies for new Junie users so that you can explore it in action for your JetBrains IDE. As of September 2025, Junie is s
GitHub - rzru/nightingale: Machine learning powered Karaoke app (with scores!)
Karaoke from any song in your music library, powered by neural networks. Nightingale scans your music folder, Plex Media Server, Jellyfin server, Navidrome server, or self-hosted web library; separates lead vocals from instrumentals using the UVR Karaoke model (or Demucs); transcribes lyrics with word-level timestamps via WhisperX; and plays it all back with synchronized highlighting, pitch scorin
MLOps roadmap 2024
The MLOps engineer role is different from an ML engineer role. Even though the role varies from company to company, in general, ML engineers focus more on bringing individual projects to production, while MLOps engineers work more on building a platform that is used by machine learning engineers and data scientists. To build such platforms, lots of different skills are required. Here is a roadmap
The Premature Obituary of Programming – Communications of the ACM
Deep learning (DL) has arrived, not only for natural language, speech, and image processing but also for coding, which I refer to as deep programming (DP). DP is used to detect similar programs, find relevant code, translate programs from one language to another, discover software defects, and to synthesize programs from a natural language description. The advent of large transformer language mode
Vertex AI を利用して強化学習レコメンデーション アプリケーションをビルドする | Google Cloud 公式ブログ
※この投稿は米国時間 2021 年 8 月 18 日に、Google Cloud blog に投稿されたものの抄訳です。 強化学習（RL）は機械学習の形態の 1 つであり、エージェントが環境に対する行動を選択しながら、その一連の選択を通じて得られる目標（報酬）を最大化する方法を学習していくというものです。RL のアプリケーションの例として、学習ベースのロボット工学、自律走行車、コンテンツ配信などがあります。基本的な RL システムには、多くの状態、対応する行動、それらの行動に対する報酬が含まれています。これを映画のレコメンデーション システムで考えてみましょう。「状態」はユーザー、「行動」はユーザーにおすすめする映画、「報酬」は映画に対するユーザー評価に当てはめることができます。Applied ML Summit 2021 の基調講演 で Spotify が述べていたように、RL は ML
Noble Numbat Release Notes Table of Contents Introduction New features in 24.04 LTS Known Issues Official flavours More information Introduction These release notes for Ubuntu 24.04 LTS (Noble Numbat) provide an overview of the release and document the known issues with Ubuntu and its flavours. For details of the changes applied since 24.04, please see the 24.04.2 change summary. Support lifespan
Over the past decade, my work has centred on partnering with teams to build ambitious products for the web across both desktop and mobile. This has provided a ring-side seat to a sweeping variety of teams, products, and technology stacks across more than 100 engagements. While I'd like to be spending most of this time working through improvements to web APIs, the majority of time spent with partne
Devbox 📦 : Instant, easy, and predictable shells and containers What is it?Devbox is a command-line tool that lets you easily create isolated shells and containers. You start by defining the list of packages required by your development environment, and devbox uses that definition to create an isolated environment just for your application. In practice, Devbox works similar to a package manager l
Using the circuit-breaker pattern with AWS Lambda extensions and Amazon DynamoDB | Amazon Web Services
AWS Compute Blog Using the circuit-breaker pattern with AWS Lambda extensions and Amazon DynamoDB May 2025: This post was reviewed for accuracy. Modern software systems frequently rely on remote calls to other systems across networks. When failures occur, they can cascade across multiple services causing service disruptions. One technique for mitigating this risk is the circuit breaker pattern, wh
【RVC v2モデル対応版】日本人のためのRVC WebUIの使い方：AIボイスチェンジャー | 子供プログラマー
【今後の開発に関して】（2024年12月24日） Google Colaboratory版のRVC WebUIのチュートリアルコードのご利用いただき、ありがとうございました。 今後の開発は、クラウドGPUサービスの1つであるRunPodで継続していきます。 今後もクラウドサービス上でRVC WebUIを使いたい方は、以下の記事ページを参照ください。 チュートリアル記事： 【RunPod編】RVC WebUIをはじめよう – AIボイスチェンジャー（一覧） 現在利用できるノートブック（2024年12月24日時点） ・オリジナル版RVC v1モデル対応RVC WebUI ・オリジナル版RVC v2モデル対応RVC WebUI ・ddPn08版RVC v1モデル対応RVC WebUI ・ddPn08版RVC v2モデル対応RVC WebUI 【動画で解説】RVC v2モデル対応版：オリジナル版
GitHub - fainir/most-capable-agent-system-prompt: Most Capable Agent System Prompt
Paste this prompt into your coding agent of choice - Claude Code, Codex, Cursor, or any similar tool - and it will build the most capable, self-improving agentic system possible. Either as a harness wrapper around your existing agent or as fresh code built from scratch based on your preference. A system that can handle software engineering, scientific research, running a company, data analysis, br
We have seen that Python language is a powerful tool for data science and data operations, but how powerful is Python for Data visualization? One of the key responsibilities of Data scientists is to communicate results effectively with the stakeholders. This is where the power of visualization comes into play. Creating effective visualizations helps businesses identify patterns and subsequently he
A layered approach to MLOps
At present, MLOps — Machine Learning Operations — is a popular topic, with numerous books, blog posts, conference talks, and more focusing on how to build a scalable, repeatable, and production-ready Machine Learning workflow. Despite this interest, MLOps remains an emerging area, and there seem to be many different ideas on the “best” way to approach the subject. The reason for these differences
LLM experimentation at scale using Amazon SageMaker Pipelines and MLflow | Amazon Web Services
Artificial Intelligence LLM experimentation at scale using Amazon SageMaker Pipelines and MLflow Large language models (LLMs) have achieved remarkable success in various natural language processing (NLP) tasks, but they may not always generalize well to specific domains or tasks. You may need to customize an LLM to adapt to your unique use case, improving its performance on your specific dataset o
Build and deploy ML inference applications from scratch using Amazon SageMaker | Amazon Web Services
Artificial Intelligence Build and deploy ML inference applications from scratch using Amazon SageMaker As machine learning (ML) goes mainstream and gains wider adoption, ML-powered inference applications are becoming increasingly common to solve a range of complex business problems. The solution to these complex business problems often requires using multiple ML models and steps. This post shows y
Photo by Kai Dahms on UnsplashI love creating software libraries. Two months ago, I started porting one of our Python packages into a Rust crate. This new Rust crate matches the Python package’s ease of use and expressiveness. Along the way, I learned nine rules that can help you create beautiful libraries in Rust. The rules are: Create examples that don’t embarrass you.Accept all kinds of strings
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How Kubernetes Reinvented Virtual Machines (in a good sense)
Agent Skillsを徹底解説！ - G-gen Tech Blog
Migrating from Go to Rust | corrode Rust Consulting
MAI-Thinking-1: Building a Hill-Climbing Machine
Manus tools and prompts
xvw.lol - Why I chose OCaml as my primary language
Why We Use Julia, 10 Years Later
Game Bub: open-source FPGA retro emulation handheld
What's New in Emacs 28.1?
Ubuntu 24.04 LTS (Noble Numbat) Release Notes
If Not React, Then What? - Infrequently Noted
Devbox 📦 : Instant, easy, predictable shells & containers
Data Visualization Using Python
Nine Rules for Elegant Rust Library APIs