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I am glad that you are here! I was working on bioinformatics a few years ago and was amazed by those single-word bash commands which are much faster than my dull scripts, time saved through learning command-line shortcuts and scripting. Recent years I am working on cloud computing and I keep recording those useful commands here. Not all of them is oneliner, but i put effort on making them brief an
こんにちは．株式会社ゆめみの Keeth こと桑原です．Twitter には #つぶやきProcessing という魅力的なタグがあり，毎日数々の美しい作品がこのタグを付けて投稿されています．これを眺めるだけでも一日中過ごせるくらいです（個人の感覚です）． 今日はその中でも特に度肝を抜かれ，かつ感動した作品が 2022/11/04 に投稿されておりましたので，個人の拙い能力で解析に挑戦してみました💁 ※一部解析しきれていない部分がありますが，ご容赦いただけますと幸いです…何分勉強中の者でして… 作品 なにはともあれ今回対象の作品． 初めてみたときは思わず言葉を失いました．いや，これ twitter のツイートですのでかなり文字数も少ないんですよ！なのにこの表現ってどうなってんの！？と… これはかなり学びになると思い解析を試みようと思い立った次第です．それにしても美しい… ソースコード で
This article was discussed on Hacker News. I recently learned of csvquote, a tool that encodes troublesome CSV characters such that unix tools can correctly process them. It reverses the encoding at the end of the pipeline, recovering the original input. The original implementation handles CSV quotes using the straightforward, naive method. However, there’s a better approach that is not only simpl
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はじめに 趣味でノードエディタ形式の画像処理ツール「Image-Processing-Node-Editor」を作りました。 その紹介の記事です。中身にOpenCV���ッツリ使っているからアドカレOKですよね。。。👀？ ガッツリ使っているという意味では、GUI部分の DearPyGui のほうがガッツリ使っているかもしれませんが🤔 「Image-Processing-Node-Editor」とは 以下のように、ノードを接続していくことで、処理結果を可視化しながら画像処理が行えるツールです。 以下のような特徴があります。 主要な処理は全てPython ※ライブラリ部分除く 各処理を可視化しながら画像処理が試せる 自作ノードの追加が容易 (だと信じている) 記事書くために見直していましたが、イマイチ複雑ですわ、、、😇 OSS (Apache 2.0ライセンス) デフォルトでいくつかのAI機
Pycon APAC 2023で登壇した時の資料です。 https://pretalx.com/pyconapac2023/talk/G3LDSG/ https://2023-apac.pycon.jp/timetable?id=G3LDSG
ruby.wasm + p5.js の組み合わせです。ほとんどの API は移植したので大体同じことができると思います。 https://p5rb.ongaeshi.me/ https://p5rb.ongaeshi.me/examples に色々サンプル。 https://p5rb.ongaeshi.me/editor にオンラインエディタがあります。 使い方 p5.rb を HTML に読みこめばすぐに使えます。 <html> <head> <script src="https://cdn.jsdelivr.net/npm/ruby-3_2-wasm-wasi@next/dist/browser.script.iife.js"></script> <script src="https://cdn.jsdelivr.net/npm/p5@1.5.0/lib/p5.js"></script
tbsp - tree-based source-processing language tbsp is an awk-like language that operates on tree-sitter syntax trees. to motivate the need for such a program, we could begin by writing a markdown-to-html converter using tbsp and tree-sitter-md [0]. we need some markdown to begin with: # 1 heading content of first paragraph ## 1.1 heading content of nested paragraph for future reference, this markdo
Image Processing in WebAssembly Photon is a high-performance image processing library in WebAssembly that runs both natively and on the web. Features Photon outperforms even the fastest of libraries, and is powered with Rust, allowing for safe and secure image processing. Web-Assembly Friendly For web-based image processing, Photon is 4-10x faster than JS, leading to faster results, and less lag.
Logistics Lectures: are on Tuesday/Thursday 4:30 PM - 5:50 PM Pacific Time in NVIDIA Auditorium. The lectures will also be livestreamed on Canvas via Panopto. Lecture videos for enrolled students: are posted on Canvas (requires login) shortly after each lecture ends. Unfortunately, it is not possible to make these videos viewable by non-enrolled students. Publicly available lecture videos and vers
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A Quick Overview �to Unlock the Potential of LLMs �through Prompt Engineering
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Bring real-time materialized views to your existing databases
インテル、新デバイス「Infrastructure Processing Unit」（IPU）発表。スマートNICを拡張しストレージ仮想化やネットワーク仮想化処理などCPUからオフロード可能に インテルは、クラウド事業者や通信サービス事業者向けに、インフラストラクチャー・プロセシング・ユニット（IPU）を発表しました（インテルジャパンの発表）。 Introducing the Infrastructure Processing Unit. https://t.co/qro7AYYA9o #SixFiveSummit pic.twitter.com/LY9e6G7Yn2 — Intel News (@intelnews) June 14, 2021 IPUは、ネットワークカードをインテリジェントにしたスマートNICをさらに拡張したもの。これまでCPUで行われていたストレージ仮想化処理やネット
Step Functions Distributed Map – A Serverless Solution for Large-Scale Parallel Data Processing | Amazon Web Services
AWS News Blog Step Functions Distributed Map – A Serverless Solution for Large-Scale Parallel Data Processing I am excited to announce the availability of a distributed map for AWS Step Functions. This flow extends support for orchestrating large-scale parallel workloads such as the on-demand processing of semi-structured data. Step Function’s map state executes the same processing steps for multi
こんにちは。 GMOリサーチ株式会社の向井と申します。 システム部でプログラマーをしています。 また、売上向上/経費削減のために、社内の他部署での作業の効率化もおこなっています。 今日は、弊社GMOリサーチで開催されたオンライン社内勉強会、「【DP⇔システム】Pythonについて話そう！会」の参加レポートをお送りします。 現在、コロナ禍で在宅勤務をしている関係でオンラインでの勉強会となりました。 情報共有は、オンラインチャットツールであるchatworkにて。 ビデオ通話ソフトはGoogle Meetを使いました。 イベント内容について 「【DP⇔システム】Pythonについて話そう！会」がどんな会だったかについて説明させていただきます。 簡単に言うと、DPチームの課題をシステム部の人に共有して、何か解決策がないか皆んなで話しあう会です。 今回が第一回目の開催となります。 参加者はDPチー
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There’s a common thread that connects Google services such as Google Search, Street View, Google Photos and Google Translate: they all use Google’s Tensor Processing Unit, or TPU, to accelerate their neural network computations behind the scenes. We announced the TPU last year and recently followed up with a detailed study of its performance and architecture. In short, we found that the TPU delive
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みなさんこんにちは。機械学習チームのたかぱい（@takapy0210）です。 2021年もあと1ヶ月となりましたね。皆様いかがお過ごしでしょうか。 ...さて12月といえば、毎年恒例のアドベントカレンダーの季節ですね！ というわけで、2021年もコネヒト Advent Calendarが始まります！🎉 初日となる本エントリでは、機械学習チームで使用しているSageMaker*1の機能である、Processing*2について、活用事例とともにご紹介しようと思います。 目次 SageMaker Processingとは? SKLearnProcessor / PySparkProcessor Processor / ScriptProcessor これまでの課題感 SageMaker Processorの活用方法 SageMakerからECRにあるコンテナを指定してProcessor Job
A fundamental feature of first-order neurons in the tactile system is that their distal axon branches in the skin and forms many transduction sites, yielding complex receptive fields with many highly sensitive zones. We found that this arrangement constitutes a peripheral neural mechanism that allows individual neurons to signal geometric features of touched objects. Specifically, we observed that
Google Cloud、インテルと共同開発したASIC「Infrastructure Processing Unit（IPU）」採用を発表。FPGAベースのSoCでサーバ本体の処理をオフロード Google Cloudとインテルは、両社が共同開発したクラウド基盤用のASIC「Intel Infrastructure Processing Unit」（Intel IPU）のGoogle Cloudでの採用を明らかにしました。 Data center infrastructure that is more secure, flexible and performant.@GoogleCloud C3 VM is first to feature custom Intel IPUs and 4th Gen Intel #XeonScalable processors in private pr
New General Purpose, Compute Optimized, and Memory-Optimized Amazon EC2 Instances with Higher Packet-Processing Performance | Amazon Web Services
The r6in and r6idn instances are available in the US East (Ohio, N. Virginia), US West (Oregon), and Europe (Ireland) regions in On-Demand and Spot form. Savings Plans and Reserved Instances are available. Inside the Instances As you can probably guess from these specs and from the blog post that I wrote to launch the c6in instances, all of these new instance types have a lot in common. I’ll do a
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A perceptual color space for image processing A perceptual color space is desirable when doing many kinds of image processing. It is useful for things like: Turning an image grayscale, while keeping the perceived lightness the same Increasing the saturation of colors, while maintaining perceived hue and lightness Creating smooth and uniform looking transitions between colors Unfortunately, as far
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Modern web technologies provide ample ways to work with video. Media Stream API, Media Recording API, Media Source API, and WebRTC API add up to a rich tool set for recording, transferring, and playing video streams. While solving certain high-level tasks, these APIs don't let web programmers work with individual components of a video stream such as frames and unmuxed chunks of encoded video or au
Artificial Intelligence (AI) advancements have enabled the development of Large Language Models (LLMs) that can perform a variety of tasks with remarkable semantic understanding and accuracy. ChatGPT is one such LLM that has gained significant attention due to its impressive capabilities for assisting in various knowledge-intensive tasks. Due to the knowledge-intensive nature of engineering secure
Processing large JSON files in Python without running out of memory by Itamar Turner-Trauring Last updated 06 Jan 2023, originally created 14 Mar 2022 If you need to process a large JSON file in Python, it’s very easy to run out of memory. Even if the raw data fits in memory, the Python representation can increase memory usage even more. And that means either slow processing, as your program swaps
Essentia.js is a JavaScript (JS) library for music/audio signal analysis and processing developed at the Music Technology Group, UPF, Barcelona. The core of library is powered by Essentia C++ library back-end using WebAssembly built via Emscripten along with a high-level JS and TypeScript API and add-on utility modules. ie, You can run an extensive collection of music/audio processing and analysis
2020.11.16 週刊Railsウォッチ（20201116前編）6.1のActive Storageでimage_processing gemが必須に、Webアプリ設計の変遷とフロントエンド領域の再定義ほか こんにちは、hachi8833です。 各記事冒頭には⚓でパーマリンクを置いてあります: 社内やTwitterでの議論などにどうぞ 「つっつきボイス」はRailsウォッチ公開前ドラフトを（鍋のように）社内有志でつっついたときの会話の再構成です👄 お気づきの点がありましたら@hachi8833までメンションをいただければ確認・対応いたします🙇 ⚓Rails: 先週の改修（Rails公式ニュースより） 以下のコミットリストのChangelogを中心に見繕いました。ドキュメントの更新が増えているようです。 コミットリスト: Comparing @{2020-11-05}...maste
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Apache AGE™ Graph Database for PostgreSQL Apache AGE™ is a PostgreSQL Graph database compatible with PostgreSQL's distributed assets and leverages graph data structures to analyze and use relationships and patterns in data. Get Started with Apache AGE Download Apache AGE Apache AGE™ is a PostgreSQL that provides graph database functionality. The goal of Apache AGE™ is to provide graph data process
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To help fellow engineers wrap their head around Apache Kafka and event streaming, I wrote a 4-part series on the Confluent blog on Kafka’s core fundamentals. In the series, we explore Kafka’s storage and processing layers and how they interrelate, featuring Kafka Streams and ksqlDB. In the first part, I begin with an overview of events, streams, tables, and the stream-table duality to set the stag
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株式会社クリアコード > ククログ > RubyKaigi 2022 - Fast data processing with Ruby and Apache Arrow #rubykaigi 関連リンク： スライド（Rabbit Slide Show） スライド（SlideShare） リポジトリー 内容 RubyKaigi Takeout 2021のRed ArrowのトークではRed Arrowを中心にできることをたくさん紹介しました。その発展形として今年は実際に使えそうな感じになっていることを紹介したかったので、高速データ処理機能にフォーカスすることにしました。が、採択されて資料を作り始めてみると「実際に使えそう」というには各機能の実装にもう少しブラッシュアップが必要なことがわかりました。なんと。。。 ということで、Apache Arrowを使って高速にデータ処理できる各種方法につい
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