标签：#r

Have you ever wondered how vector databases like Pinecone, Milvus, Qdrant, or pgvector search through billions of high-dimensional documents in milliseconds? Under the hood, they map semantic concepts into dense numerical vectors, calculate multidimensional cosine similarity angles, and traverse proximity graphs to locate nearest neighbors without scanning the entire database. To help you visualize how vector databases and embeddings actually operate, I built a retro-vector arcade game: 🛰️ Vector Strike: Database Defender Play in Fullscreen Mode (if the embed sizing is tight) 🛠️ Choose Your Database Optimizations Your mission as a Vector Database (VDB) administrator is to configure your query settings and index structures to defend your index nodes: 📏 Similarity Threshold (τ): Tweak the match threshold slider. High thresholds require near-identical semantic matches but protect your index, whereas lower thresholds act like a splash-damage laser but risk matching incorrect clusters. 🪐 Embedding Dimensions (2D $\rightarrow$ 8D $\rightarrow$ 32D): Higher dimensions isolate categories and guarantee precise hits. Lowering dimensions collapses the projection space, causing spatial overlap that results in false deflections and friendly-fire query failures. ⚡ Proximity Indexing (Flat Scan $\rightarrow$ HNSW Graph): Flat Scan: Runs a brute-force linear search over all targets. It causes computation latency spikes as more query objects arrive. HNSW (Hierarchical Navigable Small World): Dynamically builds proximity links between adjacent node targets. The turret traverses vectors along the nearest-neighbor graph, snap-locking onto targets with zero lookup latency. 🧬 Playable ML Concepts Explained Here is how the arcade mechanics map to production vector databases: 1. 🔀 Multidimensional Projections (Dimension collapse) In-Game: You can toggle between 2D, 8D, and 32D space. In 32D space, the categories are cleanly separated. In 2D space, the database collapses, and you'll find sp

Joshua Achiam spent nearly nine years at OpenAI researching AI safety and made a memorable appearance in the Musk v. Altman trial.

I rebuilt aesencryption.net so text AES (128/192/256) runs fully in the browser - the key and plaintext never leave the page. The hard part is staying byte-compatible with common server-side AES libraries (mode, IV, padding, base64 output), so I ship copy-paste equivalents in PHP, Java, Python, Go, Rust, Kotlin and JS. Live tool (mine, free): https://aesencryption.net - feedback on the crypto choices welcome. My own site.

Plausible Analytics is an open-source, self-hosted web analytics tool that tracks traffic without cookies or personal data collection, a privacy-first alternative to Google Analytics. This guide deploys Plausible Community Edition using Docker Compose, fronts it with Nginx, and secures it with a Let's Encrypt certificate. By the end, you'll have Plausible tracking a website's traffic securely at your domain. Configure the Environment 1. Clone the Community Edition repo: $ mkdir ~/plausible $ cd ~/plausible $ git clone https://github.com/plausible/community-edition.git $ cd community-edition 2. Generate a secret key: $ openssl rand -base64 64 | tr -d '\n' 3. Create the environment file: $ nano .env ADMIN_USER_EMAIL = admin@example.com ADMIN_USER_NAME = admin ADMIN_USER_PWD = ADMIN_PASSWORD BASE_URL = https://plausible.example.com SECRET_KEY_BASE = YOUR_SECRET_KEY_BASE DATABASE_URL = postgres://postgres:postgres@plausible_db:5432/plausible_db CLICKHOUSE_DATABASE_URL = http://plausible_events_db:8123/plausible_events_db Fill in your email, a strong admin password, your domain, and the secret key generated above. 4. Expose the app port via a Compose override (auto-merged with compose.yml ): $ nano compose.override.yaml services : plausible : ports : - 127.0.0.1:8000:8000 Deploy with Docker Compose $ docker compose up -d $ docker compose ps Confirm the app, Postgres, and ClickHouse (events DB) containers are all running. Front with Nginx and Let's Encrypt 1. Install Nginx: $ sudo apt update $ sudo apt install nginx -y 2. Create the virtual host: $ sudo nano /etc/nginx/sites-available/plausible.conf server { listen 80 ; listen [::]:80 ; server_name plausible.example.com ; access_log /var/log/nginx/plausible.access.log ; error_log /var/log/nginx/plausible.error.log ; location / { proxy_pass http://127.0.0.1:8000 ; proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for ; proxy_http_version 1.1 ; proxy_set_header Upgrade $http_upgrade ; proxy_set_header Connection "Upgr

I've been working on rootless container checkpoint/restore in CRIU and wrote up some notes on the prototype, major failures, and the path toward the current implementation. Would appreciate any feedback, criticism, and corrections, especially from people familiar with CRIU, Podman, or container runtimes. submitted by /u/Ok-Job3177 [link] [留言]

The Log Is the Agent AI Engineer World's Fair Coverage Ishaan Sehgal Ishaan Sehgal Ishaan Sehgal Follow for Daily Context Jun 30 The Log Is the Agent # aie # agents # ai 48 reactions 89 comments 5 min read

Focus with others through synchronized Pomodoro sessions Discussion | Link

Long time since i last posted updated about dotenv-diff, a lot of new features since then

There's still a slew of questions about why some people develop alpha-gal syndrome.