Research TacticAI: an AI assistant for football tactics Published 19 March 2024 Authors By Zhe Wang and Petar Veličković As part of our multi-year collaboration with Liverpool FC, we develop a full AI system that can advise coaches on corner kicks 'Corner taken quickly… Origi!' Liverpool FC made a historic comeback in the 2019 UEFA Champions League semi-finals. One of the most iconic moments was a
どんな記事? Obsidianを使った個人的読書メモの残し方について紹介しています。 仕事関係で読んだ本については簡単にメモを残すようにしているのですが、いろんなツールを使った結果最終的にObsidianに落ち着いたので、自分の使い方を簡単に紹介しようと思います。 サンプル こんな感じでまとめてます。 読了日は結構つけ忘れるので適当なことが多いです。 メモり方 BookSearchプラグインを使ってファイル作成 まず本を読み始めたタイミングで、BookSearchを使ってファイルを作成します。 BookSearchプラグインのインストール方法については、以下公式Githubを参考にしてください。 今回は仮に今読んでいる『科学的根拠に基づく最高の勉強法』の読書メモを残していきます。 BookSearchとテンプレートを使えば簡単に以下のようなファイルが作成されます。
You’re probably a busy person, so here’s the CSS: section:not(:target) { display: none; } Demo: Open in a new tab Open in a new tab Explanation The :target CSS selector selects the element that is targeted by the URL fragment. Combined with :not, we can hide sections that are not referenced by the URL fragment. Just as JS routers use the fragment to hide/show sections in the DOM, this “CSS router”
A SQLite REST and Realtime server Installation Install Soul CLI with npm Usage 1. Running Soul Soul is command line tool, after installing it, Run soul -d sqlite.db -p 8000 and it’ll start a REST API on http://localhost:8000 and a Websocket server on ws://localhost:8000. Usage: soul [options] Options: --version Show version number [boolean] -d, --database SQLite database file or :memory: [string]
A few weeks ago we finally got access to the GPT-4 fine-tuning API (in limited early access), and were super excited to check out how well it works. We’d been a user of OpenAI’s fine-tuned models since fine-tuning the original GPT-3 davinci model first became available. Unsurprisingly, a fine-tuned GPT-4 greatly outperforms fine-tuned GPT-3.5 (more than 50% improvement for our use case!). We’ll go
Today, we’re announcing RAG 2.0, our approach for developing robust and reliable AI for enterprise-grade performance. Unlike the previous generation of RAG, which stitches together frozen models, vector databases, and poor quality embeddings, our system is optimized end to end. Using RAG 2.0, we’ve created our first set of Contextual Language Models (CLMs), which achieve state-of-the-art performan
Published March 22, 2020 Found something wrong? Submit a pull request! Discussion on Hacker News These paper reviews can be delivered weekly to your inbox, or you can subscribe to the Atom feed. As always, feel free to reach out on Twitter with feedback or suggestions! Today I read the original paper about the Google File System (GFS), a system that provided the storage layer for many of Google’s
リリース、障害情報などのサービスのお知らせ
最新の人気エントリーの配信
j次のブックマーク
k前のブックマーク
lあとで読む
eコメント一覧を開く
oページを開く