Internet[(インターネット)]
VPN[(IP-VPN)]
J社営業部 --- VPN
VPN --- Internet
Internet --- FW
Storage --- クラウド事業者
subgraph J社情報システム部
FW[FW - ファイアウォール]
L3SW_IS[L3SW - レイヤー3スイッチ]
LAN1[LAN1 - インターネットに接続するサーバを設置するセグメント]
LAN2[LAN2 - LAN1及びLAN3だけからアクセス可能なセグメント]
Proxy[プロキシサーバ]
Mail[メールサーバ]
SalesMgmt[営業管理サーバ]
Virus[ウイルス対策サーバ]
FW --- LAN1
Proxy --- LAN1
Mail --- LAN1
SalesMgmt --- LAN2
Virus --- LAN2
L3SW_IS --- LAN1
L3SW_IS --- LAN2
FW --- L3SW_IS
end
subgraph クラウド事業者
Storage[業務データ]
end
図を読み上げるのめんどい。テキスト表現にしたところで構築できないし
graph TD
subgraph J社営業部
PC1[PC]
PC2[PC]
L3SW_J[L3SW]
LAN3[LAN3 - 営業部のPCを設置するセグメント]
PC1 --- L3SW_J
PC2 --- L3SW_J
L3SW_J --- LAN3
end
令和05年度春期午後Ⅰ【問2】 https://sm.ids0.com/r05pm1_2/
その🦜
さんがブースト
💎 Kaigi on Rails 2024 会場までの道案内 🎉
最寄りの駅から会場までの道案内動画を公開しました！
お越しの際はぜひ参考にしてください〜 👋
りんかい線 国際展示場駅から https://www.youtube.com/watch?v=ggu2-LZf6CE&feature=youtu.be
新交通ゆりかもめ 国際展示場正門前駅から https://youtu.be/iRoSE1p0FIE
#kaigionrails
その🦜
さんがブースト
Blink: Intent to Experiment: Translator API https://groups.google.com/a/chromium.org/d/msgid/blink-dev/CAM0wra9ArjjD0u%3DpFs1W_5%3DcMk49JXs5ObQ15dNHCHt3TKSW3g%40mail.gmail.com
その🦜
さんがブースト
A new #passkeys case study: Tokyu — a Japanese railway company achieved 12 times faster sign-in compared to email-based two-factor authentication. Imagine you have to handle 2FA when you are in hurry. People love passkeys for its simple and quick way to sign in.
https://web.dev/case-studies/tokyu-passkeys
今回のRust, ヒープ確保と初期化とか生借用演算子あたりが変わったらしい。嬉しみがわからないぐらいに疎い
https://aznhe21.hatenablog.com/entry/2024/10/18/rust-1.82
ts-blank-spaceつながりで
https://github.com/mizchi/mints
Computer scientists invent an efficient new way to count
https://news.ycombinator.com/item?id=40379175
その🦜
さんがブースト
日本につくとそこらじゅうで人間が案内しててびっくりするよね
その🦜
さんがブースト
In https://chatgpt.com/share/94152e76-7511-4943-9d99-1118267f4b2b I gave the new model a challenging complex analysis problem (which I had previously asked GPT4 to assist in writing up a proof of in https://chatgpt.com/share/63c5774a-d58a-47c2-9149-362b05e268b4 ). Here the results were better than previous models, but still slightly disappointing: the new model could work its way to a correct (and well-written) solution *if* provided a lot of hints and prodding, but did not generate the key conceptual ideas on its own, and did make some non-trivial mistakes. The experience seemed roughly on par with trying to advise a mediocre, but not completely incompetent, graduate student. However, this was an improvement over previous models, whose capability was closer to an actually incompetent graduate student. It may only take one or two further iterations of improved capability (and integration with other tools, such as computer algebra packages and proof assistants) until the level of "competent graduate student" is reached, at which point I could see this tool being of significant use in research level tasks. (2/3)
