vltansky

Skills: https://github.com/vltansky/foundry-skills
GDrive: https://drive.google.com/drive/folders/1ajHwhzXWOHwMTu1yljxsSBD_Oqa0Ord9?usp=sharing

Recommendations:
https://impeccable.style/
https://github.com/garrytan/gstack
https://openspec.dev/
https://docs.bmad-method.org/
https://jakub.kr/skills/make-interfaces-feel-better
https://www.agentation.com/

karpathy

"""
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

kiraio-moe

There are many ways and tools to use proxy in Linux. But, let's use what I already used.

GUI

• This is the easiest way. If you have a GUI settings, just search for Network > Network Proxy > Manual.
• Fill in the input with your own proxy settings.

Manual with CLI

vwkd

MSN MoneyCentral - Strategy Lab - Value Doc - Dr. Michael Burry

Michael operates on out-of-favor industries to find best-of-breed companies trading at steep discounts.

Biography

Michael focuses on free cash flow and private market valuation as he scours out-of-favor industries and overlooked securities.

tricolorpaulista

#EXTM3U
#PLAYLISTV: pltv-logo="http://megafilmeshdplus.org/wp-content/uploads/2017/08/Mega-Filmes-HD-Plus-.Org_.png" pltv-name="CINEMA" pltv-description="Marcus" pltv-cover="XXX CAPA DA LISTA XXX" pltv-author="XXX AUTOR DA LISTA XXX" pltv-site="XXX SITE CASO HOUVER XXX" pltv-email="XXX E-MAIL XXX"

#EXTINF:-1 tvg-logo="https://goo.gl/dMrVaZ" group-title="Seriado" pltv-subgroup="2 Garotas em Apuros",2GEA T1|EP01
https://cdn2.canais.ink/RCServer09/ondemand/2BRKGLT01EP01.mp4?expires=1581552100&token=f1093bb907fb240d5b2721638c8116cf
#EXTINF:-1 tvg-logo="https://goo.gl/dMrVaZ" group-title="Seriado" pltv-subgroup="2 Garotas em Apuros",2GEA T1|EP02
https://cdn2.canais.ink/RCServer09/ondemand/2BRKGLT01EP02.mp4?expires=1581546741&token=0e2d8a7b3fd27dc9319ca18abe47e75c
#EXTINF:-1 tvg-logo="https://goo.gl/dMrVaZ" group-title="Seriado" pltv-subgroup="2 Garotas em Apuros",2GEA T1|EP03
https://cdn2.canais.ink/RCServer09/ondemand/2BRKGLT01EP03.mp4?expires=1581546741&token=0e2d8a7b3fd27dc9319ca18abe47e75c

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.

ryerh

注意：本文内容适用于 Tmux 2.3 及以上的版本，但是绝大部分的特性低版本也都适用，鼠标支持、VI 模式、插件管理在低版本可能会与本文不兼容。

Tmux 快捷键 & 速查表 & 简明教程

启动新会话：

tmux [new -s 会话名 -n 窗口名]

恢复会话：

briansalvattore

import { GoogleGenAI, Modality } from "https://esm.sh/@google/genai";
import { key } from './_key.js'

const API_KEY = key;

let audioContext;
let nextStartTime = 0;
const audioSources = new Set();

let audioInputContext;