This is an OPML version of the HN Popularity Contest results for 2025, for importing into RSS feed readers.

Plug: if you want to find content related to your interests from thousands of obscure blogs and noisy sources like HN Newest, check out Scour. It's a free, personalized content feed I work on where you define your interests in your own words and it ranks content based on how closely related it is to those topics.

Note on sizes: a lot of those might be inaccurate as there might be many microservices required aside from the core release/docker image. I haven't tested these recently so I'm not sure

• Designed explicitly as an open source Firebase alternative
• Typescript based
• Docker support
• Full Postgres database with Realtime subscriptions

1. Open Discord client, press Ctrl + Shift + I to open DevTools (Discord client only, Browser is not supported)
2. Go to Console tab
3. Type allow pasting and press Enter
4. Paste the snippet below and press Enter

This guide describes how to set up an Obsidian vault that syncs across devices while maintaining a separate Git backup without interfering with the sync mechanism. This guide should work with either official Obsidian Sync solution or with unofficial sync plugins like Obsidian Livesync or Remotely Save.

• Git installed on your system
• Obsidian installed
• Either Obsidian Sync subscription or LiveSync plugin configured
• Basic familiarity with command line

A hands-on one semester course where students build their own compiler from scratch, starting from elementwise programs and ending with training SOTA LLMs on GPUs. This course aggressively builds on the previous week, and is an exercise in slop management. If you let any slop in early, it will compound and you will not finish the class.

Course description: This course covers the design and implementation of a modern machine learning compiler, and examines the interaction between IR design, hardware capabilities, and the structure of machine learning programs. Topics covered include term rewriting, code generation, movement operators, kernel fusion, memory hierarchies, GPU architecture, automatic differentiation, and flash attention. It is a project course, providing experience with performance-oriented programming, managing a codebase that grows all semester, and working in 1 or 2 person teams, culminating in a compiler capable of training modern LLMs.

Prerequisites: This c

A pattern for building personal knowledge bases using LLMs.

This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.

Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.