| Action | Shortcut |
|---|---|
| Scroll line up | ctrl+shift+up (also ⌥+⌘+⇞ and ⌘+↑ on macOS) |
| Scroll line down | ctrl+shift+down (also ⌥+⌘+⇟ and ⌘+↓ on macOS) |
| Scroll page up | ctrl+shift+page_up (also ⌘+⇞ on macOS) |
| Scroll page down | ctrl+shift+page_down (also ⌘+⇟ on macOS) |
Discover gists
ARKit face tracking is shrouded in a ton of myth and mystique.
I reverse engineered the internal face tracking API, and this is how it actually works.
This is based on reverse engineering the API of Apple's face detection framework and testing it with my own code. Some of it is educated guesswork based on names and strings. I did not reverse engineer the details of how ARKit/FaceKit works, but given what I've seen, I'm quite confident in the overall big picture.
Updated 2018-03-23 Version 1802 (Build 16.0.9029.2167)
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| """ | |
| The most atomic way to train and run inference for a GPT in pure, dependency-free Python. | |
| This file is the complete algorithm. | |
| Everything else is just efficiency. | |
| @karpathy | |
| """ | |
| import os # os.path.exists | |
| import math # math.log, math.exp |
Think and work in English. Reply in Korean.
Covers code, identifiers, log/error messages, comments, docs, examples, commit messages.
- Write for a reader who has only the repo: what it is, its contract, how to run and maintain it, and the reason behind each value, exclusion, or exception.
- Say what that reader needs once and briefly; link instead of repeating.
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.
All you need is an Android buildsystem (LineageOS is recommended)
NOTE: For Lineage 21 and newer, different steps are required.
- Export your infos (replace examples with your infos)
subject='/C=US/ST=California/L=Mountain View/O=Android/OU=Android/CN=Android/emailAddress=android@android.com'
C: Country shortform
The "Magic" Wand is a simple motion-sensitive toy that triggers actions you can use in Home Assistant.
The "spell-casting" gesture is activated by:
- Waking it up via the button (LEDs pulse gently)
- Connecting to Wi-Fi (LEDs pulse brighter)
- "Arming" (moving to a vertical position — brightest pulse)
- First, you need to open cmd in the admin mode, then run all commands below one by one.
- For x86 and x64
cd /d %ProgramFiles(x86)%\Microsoft Office\Office16
cd /d %ProgramFiles%\Microsoft Office\Office16