PyText: A seamless path from NLP research to production – Facebook Research
We introduce PyText1 – a deep learning based NLP modeling framework built on PyTorch. PyText addresses the often-conflicting requirements of enabling rapid experimentation and of serving models at scale. It achieves this by providing simple and extensible interfaces for model components, and by using PyTorch’s capabilities of exporting models for inference via the optimized Caffe2 execution engine
Blender Bot 2.0: An open source chatbot that builds long-term memory and searches the internet
Blender Bot 2.0: An open source chatbot that builds long-term memory and searches the internet Facebook AI Research has built and open-sourced BlenderBot 2.0, the first chatbot that can simultaneously build long-term memory it can continually access, search the internet for timely information, and have sophisticated conversations on nearly any topic. It’s a significant update to the original Blend
ML Platform Meetup: Infra for Contextual Bandits and Reinforcement Learning
Infrastructure for Contextual Bandits and Reinforcement Learning — theme of the ML Platform meetup hosted at Netflix, Los Gatos on Sep 12, 2019. Contextual and Multi-armed Bandits enable faster and adaptive alternatives to traditional A/B Testing. They enable rapid learning and better decision-making for product rollouts. Broadly speaking, these approaches can be seen as a stepping stone to full-o
Name
Name JP 栗原 啓輔 / くりばら けいすけ EN Keisuke Kuribara Bio 1996年生まれ Skills and Knowledge ブロックチェーン分析、金融犯罪対策、AML/CFT、トラベルルール、デジタルマーケティング、営業、基礎的なコンピューターサイエンス、ウェブ開発 Language 日本語: ネイティブ 英語: 読み書き Certification Google アナリティクス個人認定資格 Google 広告「検索広告」認定資格 Google 広告「ディスプレイ広告」認定資格 Google 広告の測定認定資格 Chainalysis Reactor Certification (CRC) Bible 闇金ウシジマくん ナニワ金融道 銀と金 カイジ グラップラー刃牙 ミナミの帝王 サンクチュアリ Contact Email: keisukeniko7 [
Powered by AI: Instagram’s Explore recommender system
Over half of the Instagram community visits Instagram Explore every month to discover new photos, videos, and Stories relevant to their interests. Recommending the most relevant content out of billions of options in real time at scale introduces multiple machine learning (ML) challenges that require novel engineering solutions. We tackled these challenges by creating a series of custom query langu
Facebook News Feed インフラ責任者がスマニュー新VPoEに。「社内開発プラットフォームを作り、エンジニアを全力支援する」 - スマQ（スマキュー）｜スマートニュースの「はたらく」をみつける
Youlin Li（左）と前田俊太郎（右） Facebook で News Feedのインフラ責任者を務めた Youlin Liが、スマートニュースの Vice President of Engineering, Backend System and Foundation に就任しました。 about.smartnews.com Youlin の来日に合わせて、Vice President of Ad Product の前田俊太郎がインタビューしました。Facebook でどんなことをしてきたのか、その経験を生かしてスマートニュースで何を成し遂げようと考えているのか、徹底的に聞きました（構成：スマートニュース通訳・翻訳チーム＆スマQ編集部）。 Facebook を支える「社内開発プラットフォーム」の重要性 前田 よろしくお願いします。まずは自己紹介を。 Youlin Youlin Li で
Machine Learning at Facebook: Understanding Inference at the Edge - Meta Research | Meta Research
Machine Learning at Facebook: Understanding Inference at the EdgeIEEE International Symposium on High-Performance Computer Architecture (HPCA) At Facebook, machine learning provides a wide range of capabilities that drive many aspects of user experience including ranking posts, content understanding, object detection and tracking for augmented and virtual reality, speech and text translations. Whi
Introducing FBLearner Flow: Facebook’s AI backbone
Many of the experiences and interactions people have on Facebook today are made possible with AI. When you log in to Facebook, we use the power of machine learning to provide you with unique, personalized experiences. Machine learning models are part of ranking and personalizing News Feed stories, filtering out offensive content, highlighting trending topics, ranking search results, and much more.
Applied Machine Learning at Facebook: A Datacenter Infrastructure Perspective - Meta Research | Meta Research
Applied Machine Learning at Facebook: A Datacenter Infrastructure PerspectiveInternational Symposium on High-Performance Computer Architecture (HPCA) Machine learning sits at the core of many essential products and services at Facebook. This paper describes the hardware and software infrastructure that supports machine learning at global scale. Facebook’s machine learning workloads are extremely d
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What I Learned From Attending Scale Transform 2021 — James Le
Facebook London に入社することになりました
http://learningsys.org/nips17/assets/papers/paper_14.pdf
“Predictive Learning” is the New Buzzword in Deep Learning