emilianavt

Best VTuber software

This is a list of the most commonly used and relevant vtubing software. The "best" will always be subjective and depend on your specific requirements. Overall, the information in this list is as accurate as I could figure it out, but there might be errors or some details might become out of date. If you find anything that needs to be corrected, please let me know. You can also note it in a comment.

Additional explanations:

• iPhone means that an iPhone is basically required
• iFacialMocap support means that tracking data can be received from the iFacialMocap iPhone app
• VMC protocol means that the application can send and/or receive tracking data from other VMC protocol capable applications, allowing the combination of multiple tracking methods (e.g. VSeeFace receiving VR tracking from Virtual Motion Capture and iPhone/ARKit face tracking from Waidayo)
• Tobii means that the Tobii eye tracker is supported

lmmx

You are a text evaluator. You will be given a piece of text and an AI Tells Rubric. Use the rubric to judge the text objectively. Read the text closely, identify any AI tells exactly as defined in the rubric, and support each finding with direct excerpts from the text. Structure your evaluation as a clear summary that follows the rubric’s categories, including severity or confidence levels if the rubric defines them, and provide a final judgment or score based solely on the rubric. Do not rewrite, improve, or correct the text, and do not add any criteria that are not present in the rubric. If a rubric item is unclear or absent, mark it as Not Applicable. If no AI tells are detected, state that explicitly and justify briefly. Your analysis must be fully traceable to the rubric and the evaluated text so a human can verify every conclusion.

karpathy

LLM Wiki

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.

The core idea

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.

a31408212

LLM Wiki

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.

The core idea

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.

johnnyaug

#!/bin/bash

# Configuration
ARCH="arm64" # Use "x64" for Intel.
GITHUB_API="https://api.github.com/repos/Radarr/Radarr/releases/latest"
INSTALL_DIR="/Applications"
APP_NAME="Radarr.app"
INFO_PLIST="$INSTALL_DIR/$APP_NAME/Contents/Info.plist"
TEMP_DIR=$(mktemp -d)

skipcloud

Have you ever tried to merge two branches only to end up in conflict hell? You fix a bunch of conflicts only to run git merge --continue and be presented with the same conflicts. Repeat this process and after a few iterations you give up because it just isn't worth the pain and effort.

Would you be surprised to know that there is a git feature specifically for this problem? It's called rerere and I'm going to enrich your life with it now. (I'm going to talk specifically about merging but I think it also helps rebasing)

rerere stands for Reuse Recorded Resolution. The TL;DR version is you ask git to remember how you've resolved hunks in the past, and if the same one comes up for a file in future just redo what you did last time.

To enable this feature just run this lovely command git config --global rerere.enabled true. You can also turn it on by creating this directory in your projects .git/rr-cache, although the global setting is much clearer.

I'll try to take you through an example of how th

manuelgeek

 ​13 TB collections, you might require​

​BOOKMARK THIS​

Google drive movies - https://drive.google.com/drive/u/0/mobile/folders/0B6FjKMQKynZILTlwZHl4ajUwcFU
Programming language collection on google drive - https://drive.google.com/drive/folders/0ByWO0aO1eI_MN1BEd3VNRUZENkU
Books -
https://drive.google.com/drive/folders/0B0hgUX3me1_RNi1KTXBzXzdXSzA
Google drive hacking ebook collection - https://drive.google.com/drive/folders/0B-JzQsKoJaANbTFGN0RWLWhONms
Books for reading - https://drive.google.com/drive/folders/0B09qtt10aqV1SGxRVXBWYmNIS2M

devinschumacher

Patreon Video Downloader (Browser Extension)

Download videos, audio, images, post text, and attachments from Patreon posts you can already access.

Patreon Downloader is a browser extension built for subscribers, creators, researchers, and teams who want a simpler way to save Patreon content for offline viewing, local backup, and personal organization. It works inside your active Patreon browser session, detects supported media on creator posts, and gives you a direct download workflow without needing separate desktop tools.

• Save Patreon videos from supported creator posts
• Download audio, podcast-style posts, images, and file attachments
• Capture post text for personal archiving and reference
• Keep local copies for offline viewing, study, review, or backup

defunkt

(This is the text of the keynote I gave at Startup Riot 2009. Will update when video becomes available.)

Hi everyone, I'm Chris Wanstrath, and I'm one of the co-founders of GitHub.

GitHub, if you haven't heard of it, has been described as "Facebook for developers." Which is great when talking about GitHub as a website, but not so great when describing GitHub as a business. In fact, I think we're the polar opposite of Facebook as a business: we're small, never took investment, and actually make money. Some have even called us successful.

Which I've always wondered about. Success is very vague, right? Probably even relative. How do you define it?

After thinking for a while I came up with two criteria. The first is profitability. We employ four people full time, one person part time, have thousands of paying customers, and are still growing. In fact, our rate of growth is increasing - which means January was our best month so far, and February is looking pretty damn good.