AOSHIMA ナンバープレートメーカー - AOSHIMA SCALE MODEL LINEUP
2023.9.29 図柄入りナンバープレートに新しい図柄が追加されました。(石川、香川、金沢、高知、成田、徳島) 今後も続々追加予定となっております。 2023.5.2 図柄入りナンバープレートに新しい図柄が追加されました。(苫小牧、新潟、長岡、飛鳥、福山、佐世保) 今後も続々追加予定となっております。
2023.9.29 図柄入りナンバープレートに新しい図柄が追加されました。(石川、香川、金沢、高知、成田、徳島) 今後も続々追加予定となっております。 2023.5.2 図柄入りナンバープレートに新しい図柄が追加されました。(苫小牧、新潟、長岡、飛鳥、福山、佐世保) 今後も続々追加予定となっております。
Democratizing access to large-scale language models with OPT-175B
Democratizing access to large-scale language models with OPT-175B Large language models — natural language processing (NLP) systems with more than 100 billion parameters — have transformed NLP and AI research over the last few years. Trained on a massive and varied volume of text, they show surprising new capabilities to generate creative text, solve basic math problems, answer reading comprehensi
DevOps for ML Data: Putting ML Into Production at Scale | Tecton
Getting machine learning (ML) into production is hard. In fact, it’s possibly an order of magnitude harder than getting traditional software deployed. As a result, most ML projects never see the light of production-day and many organizations simply give up on using ML to drive their products and customer experiences.1 From what we’ve seen, a fundamental blocker preventing many teams from building
GitHub - microsoft/unilm: Large-scale Self-supervised Pre-training Across Tasks, Languages, and Modalities
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Unification of the middle scale services by Nuxt.js
「Nuxt.jsで中規模サービスを統合した話」 InsideFrontend 2019のA-3で発表した内容です。
GitHub - matanolabs/matano: Open source security data lake for threat hunting, detection & response, and cybersecurity analytics at petabyte scale on AWS
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Building a large-scale distributed storage system based on Raft | Cloud Native Computing Foundation
Guest post by Edward Huang, Co-founder & CTO of PingCAP In recent years, building a large-scale distributed storage system has become a hot topic. Distributed consensus algorithms like Paxos and Raft are the focus of many technical articles. But those articles tend to be introductory, describing the basics of the algorithm and log replication. They seldom cover how to build a large-scale distribut
ZeRO-Infinity and DeepSpeed: Unlocking unprecedented model scale for deep learning training - Microsoft Research
ZeRO-Infinity and DeepSpeed: Unlocking unprecedented model scale for deep learning training Published April 19, 2021 By DeepSpeed Team Rangan Majumder , Vice President Andrey Proskurin , Corporate Vice President of Engineering Since the DeepSpeed optimization library was introduced last year, it has rolled out numerous novel optimizations for training large AI models—improving scale, speed, cost,
For every successful technology, there is a moment where its time comes. Something happens, usually external, to catalyze it — shifting it from being a good idea with promise, to a reality that we can’t imagine living without. Perhaps the best recent example was what happened to the cloud as a result of the introduction of the iPhone in 2007. Smartphones created a huge addressable market for small
AWS Config now supports periodic recording: Efficiently scale your change tracking
AWS Config announces the launch of periodic recording to track resource configuration changes more efficiently at scale. This launch extends AWS Config’s existing recording capabilities, which continuously track every change as it occurs. Periodic recording captures the latest configuration changes of your resources once every 24 hours, reducing the number of changes delivered. Both continuous and
Open sourcing Brooklin: Near real-time data streaming at scale
Open sourcing Brooklin: Near real-time data streaming at scale Editor's note: This blog has been updated. Brooklin—a distributed service for streaming data in near real-time and at scale—has been running in production at LinkedIn since 2016, powering thousands of data streams and over 2 trillion messages per day. Today, we are pleased to announce the open-sourcing of Brooklin and that the source c
GitHub - microsoft/DialoGPT: Large-scale pretraining for dialogue
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RT-1: Robotics Transformer for real-world control at scale
Philosophy We strive to create an environment conducive to many different types of research across many different time scales and levels of risk. Learn more about our Philosophy Learn more
Simplify SaaS scale TLS certificate management | Google Cloud Blog
Introducing Certificate Manager to simplify SaaS scale TLS and certificate management We’re excited to announce the public preview of Certificate Manager and its integration with External HTTPS Load Balancing. Certificate Manager enables you to use External HTTPS Load Balancing with as many certificates or domains as you need. You can bring your own TLS certificates and keys if you have an existin
Delicious Donut Components An interactive guide to component composition with React Server Components Do you know how many calories are in a donut? I don’t either—the only thing I know about donuts is that they’re delicious. Oh, and that they’re a great way to build composable UIs. If you’ve been building with React Server Components, you might be familiar with a composition pattern that allows yo
Retrieval Augmented Generation at scale — Building a distributed system for synchronizing and…
Disclaimer: We will go into some technical and architectural details of how we do this at Neum AI — A data platform for embeddings management, optimization, and synchronization at large scale, essentially helping with large-scale RAG. As we’ve shared in other blogs in the past, getting a Retrieval Augmented Generation (RAG) application started is pretty straightforward. The problem comes when tryi
Introducing “Database Performance at Scale”: A Free, Open Source Book
Discover new ways to optimize database performance and avoid common mistakes that impact latency and throughput So many things have to align perfectly for impressive database performance. You need to think hard about factors like: The infrastructure your database sits on How it’s set up How you’re managing it How your application interacts with the driver How the driver interacts with your databas
Tricks of the Trade: Tuning JVM Memory for Large-scale Services
You’re seeing information for Japan . To see local features and services for another location, select a different city. Show more Running queries on Uber’s data platform lets us make data-driven decisions at every level, from forecasting rider demand during high traffic events to identifying and addressing bottlenecks in the driver sign-up process. Our Apache Hadoop-based data platform ingests hun
How to scale a large codebaseRecommendations for building and scaling large software projects. Scaling a codebase is an integral, and inevitable, part of growing a software company. You may have heard many terms thrown around as answers — monoliths, monorepos, micro frontends, module federation, and more. At Vercel, we’ve helped thousands of large organizations evolve their codebases, and we have
Building a high-scale chat server on Cloud Run Ahmet Alp Balkan published on 09 March 2021 In this blog, I will show you how to use WebSockets support to build a fleet of serverless containers that make up a chatroom server that can scale a high number of concurrent connections (250,000 clients). The point of this article is to illustrate WebSockets on Cloud Run and the scale you can reach by usin
Different security issues are a common problem for open source packages archived to and delivered through software ecosystems. These often manifest themselves as software weaknesses that may lead to concrete software vulnerabilities. This paper examines various security issues in Python packages with static analysis. The dataset is based on a snapshot of all packages stored to the Python Package I
Language modelling at scale: Gopher, ethical considerations, and retrieval
Responsibility & Safety Language modelling at scale: Gopher, ethical considerations, and retrieval Published 8 December 2021 Authors Jack Rae, Geoffrey Irving, Laura Weidinger Language, and its role in demonstrating and facilitating comprehension - or intelligence - is a fundamental part of being human. It gives people the ability to communicate thoughts and concepts, express ideas, create memorie
Emoji to Scale
Your favorite emojis. To scale (more or less).
Migrating Critical Traffic At Scale with No Downtime — Part 2
Shyam Gala, Javier Fernandez-Ivern, Anup Rokkam Pratap, Devang Shah Picture yourself enthralled by the latest episode of your beloved Netflix series, delighting in an uninterrupted, high-definition streaming experience. Behind these perfect moments of entertainment is a complex mechanism, with numerous gears and cogs working in harmony. But what happens when this machinery needs a transformation?
Lessons Learnt From Consolidating ML Models in a Large Scale Recommendation System
by Roger Menezes, Rahul Jha, Gary Yeh, and Sudarshan Lamkhede In this blog post, we share system design lessons from consolidating several related machine learning models for large-scale search and recommendation systems at Netflix into a single unified model. Given different recommendation use cases, many recommendation systems treat each use-case as a separate machine-learning task and train a b
1/1スケールで劇中アイテムをお送りするFull Scale Worksシリーズに 『機動戦士ガンダム』40周年を記念して発売した「シャア・アズナブル シュタールヘルム」が再び登場。 ヘルメット本体の全高は約30cm。完全新規金型のABS製ヘルメットは軽量かつ各部エッジのリアルな再現を実現しました。 ヘッドギアは眼部にマジックミラーシートを採用することで良好な視界を確保。 専用台座が付属しディスプレイし雰囲気を楽しめる事も出来ます。 そんな誰もが憧れる大佐になれるFull Scale Works「シャア・アズナブル シュタールヘルム」。 イベント毎やコレクションなど幅広い用途でご堪能ください。 ※本製品はフリーサイズです。着用には個人差があります。 -----------------------------------------------------------------------
Ankerの「Eufy Smart Scale P2 Pro」で、次の健康診断が楽しみになったよ | ROOMIE（ルーミー）
冬は寒くてついつい出不精になってしまいがち。 体を動かす時間が減っても食べる量は変わらないから、当然のごとく体重が増えちゃうんですよね。 そして、運動不足&体重増加は体に良いわけがなく、健康診断の数値を見て焦る……というのが恒例でした。 次こそは絶対改善させるぞ！ということで、今年から軽めのトレーニングを始めたんです。体のあらゆる数値を測定できるアイテムを導入して……。 16もの指標を測定できちゃう Anker 「Eufy Smart Scale P2 Pro」 6,990円（税込） 健康診断を受診するといろんな測定結果が見れるわけなんですが、自宅でもそれを可能にするのが、Ankerの「Eufy Smart Scale P2 Pro」。 体重計のように量ると10数秒で「体重・体脂肪・BMI・心拍数・筋肉量」など、16の指標を一度に測定できちゃう優秀な体重体組成計。 健康診断の測定結果と比較
TELEXISTENCE inc. – テレイグジスタンス株式会社(TELEXISTENCE inc.)- the systematic innovator of scale in robotics. Our Mission is to create the world where every single person at every corner on planets benefits from robotic revolution.
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Fluid Type Scale - Generate responsive font-size variables
Minimum (Mobile)At this minimum viewport width, all font sizes in your type scale are computed as the base font size times a power of your chosen ratio. Base font size (px)Screen width (px)Type scale ratioMinor secondMajor secondMinor thirdMajor thirdPerfect fourthAugmented fourthPerfect fifthGolden ratio Maximum (Desktop)At this maximum viewport width, all font sizes in your type scale are comput
How to build large-scale end-to-end encrypted group video calls
How to build large-scale end-to-end encrypted group video calls peter-signal on 15 Dec 2021 Signal released end-to-end encrypted group calls a year ago, and since then we’ve scaled from support for 5 participants all the way to 40. There is no off the shelf software that would allow us to support calls of that size while ensuring that all communication is end-to-end encrypted, so we built our own
Building a cost efficient, petabyte-scale lake house with Amazon S3 lifecycle rules and Amazon Redshift Spectrum: Part 1 | Amazon Web Services
AWS Big Data Blog Building a cost efficient, petabyte-scale lake house with Amazon S3 lifecycle rules and Amazon Redshift Spectrum: Part 1 The continuous growth of data volumes combined with requirements to implement long-term retention (typically due to specific industry regulations) puts pressure on the storage costs of data warehouse solutions, even for cloud native data warehouse services such
Prompt Tuning : Model Tuningの精度に迫る最新チューニング手法 (The Power of Scale for Parameter-Efficient Prompt Tuningまとめ) - Qiita
Prompt Tuning : Model Tuningの精度に迫る最新チューニング手法 (The Power of Scale for Parameter-Efficient Prompt Tuningまとめ)自然言語処理DeepLearningチューニング深層学習論文読み こんにちは，Nakaiと申します． 今回はGoogle Researchから2021/04/18にarXivに投稿されたチューニング手法であるPrompt Tuningについてゼミで紹介するので，ついでにQiitaにも投稿させていただこうと思います． 原論文 : The Power of Scale for Parameter-Efficient Prompt Tuning codeの公開は今の所なさそうです(2021/05/01現在) 数式及び図は基本的に論文から引用しています． また，私は普段は画像認識の領域に関
AWS Step Functions launches large-scale parallel workflows for data processing and serverless applications
AWS Step Functions expands support for iterating and processing large sets of data such as images, logs and financial data in Amazon Simple Storage Service (Amazon S3), a cloud object storage service. AWS Step Functions is a visual workflow service capable of orchestrating over 10,000 API actions from over 220 AWS services to automate business processes and data processing workloads. Now, AWS Step
【NovelAI Diffusion】パラメータ変化が絵に与える影響：step, scale, etc - MarkdownとBullet Journal
NovelAIDiffusionの編集画面 NovelAIDiffusionの画面右側には画像調整に使える色々なパラメータが揃っている。そこで各パラメーターを調整することで絵がどの様に変化するか実証してみた。 実証①：Add Quality Tags 本日サービスがアップデートされ、リッチなイメージで生成する「masterpiece, best quality, 」をプロンプトの先頭に付与するAdd Quality Tagsボタンが追加された。 デフォルトの画像生成の品質を向上させるために、Add Quality Tags(画質タグを追加)の設定を有効/無効にできるボタンを追加しました。有効にされた場合、再度設定を無効にしない限り、すべてのプロンプトのテキストの先頭に「masterpiece, best quality, 」が自動的に追加されます。 pic.twitter.com/jnhd
Apache Airflow : 10 rules to make it work ( scale )
if you are not careful your shortcuts will cost you a lot afterwardsAirflow permissive approach will let you schedule any custom code (jobs) but you will create a spaghetti stack if you do not follow very strict SEPARATION OF CONCERN design between the airflow dags and your jobs. Airflow allow you to run your jobs without isolation with the framework itselfAt the origin Airflow was sort of a “supe
Introducing Scalar: Git at scale for everyone - Azure DevOps Blog
Git is a distributed version control system, so by default each Git repository has a copy of all files in the entire history. Even moderately-sized teams can create thousands of commits adding hundreds of megabytes to the repository every month. As your repository grows, Git may struggle to manage all that data. Time spent waiting for git status to report modified files or git fetch to get the lat
How we learned to improve Kubernetes CronJobs at Scale (Part 1 of 2)
At Lyft, we chose to move our server infrastructure onto Kubernetes, a distributed container orchestration system in order to take advantage of automation, have a solid platform we can build upon, and lower overall cost with efficiency gains. Distributed systems can be difficult to reason about and understand, and Kubernetes is no exception. Despite the many benefits of Kubernetes, we discovered s
Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.
The Scale Plugin Framework drastically reduces the need to rewrite middleware in different languages by giving developers the ability to chain together functions written across any language. Functions can optionally call and return the response of the next function in their chain, or they can respond directly. This powerful pattern makes it possible to combine Scale Functions with native HTTP hand
Batch normalization is a key component of most image classification models, but it has many undesirable properties stemming from its dependence on the batch size and interactions between examples. Although recent work has succeeded in training deep ResNets without normalization layers, these models do not match the test accuracies of the best batch-normalized networks, and are often unstable for l
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Real-Time Communications at Scale
Delicious Donut Components | Frontend at Scale
How to scale a large codebase – Vercel
Building a high-scale chat server on Cloud Run
A Large-Scale Security-Oriented Static Analysis of Python Packages in PyPI
Full Scale Works 機動戦士ガンダム シャア・アズナブル シュタールヘルム 【再販】| プレミアムバンダイ
How sewage could reveal true scale of coronavirus outbreak
Scale | Write Once, Run Everywhere
High-Performance Large-Scale Image Recognition Without Normalization