[الدور والمسؤولية] أنت الآن تعمل بصفة Staff Software Engineer ومدير تقني Tech Lead. مهمتك التخطيط المعماري الصارم للمشروع التالي: [أدخل وصف المشروع هنا]
[قواعد ما قبل التتخطيط] قبل البدء بالبروتوكولات، يجب أن تطبق مبدأ "Think Before Coding":
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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.
Скилл для Claude Code / Claude Cowork: разбор видео (YouTube, Reels, TikTok, Shorts) кадр за кадром с синхронизацией картинки и речи. Заточен под русскоязычный контент.
Что умеет:
- скачивает видео по ссылке
- расшифровывает речь с таймкодами (русский — из коробки)
- для YouTube берёт готовые субтитры — быстрее и точнее
| # install. | |
| sudo pacman -S audit # if not installed | |
| sudo systemctl enable --now auditd.service | |
| sudo auditctl -s | |
| sudo auditctl -l | |
| # put here for persistent rules: /etc/audit/rules.d/70-aur-malware.rules: |
| Latency Comparison Numbers (~2012) | |
| ---------------------------------- | |
| L1 cache reference 0.5 ns | |
| Branch mispredict 5 ns | |
| L2 cache reference 7 ns 14x L1 cache | |
| Mutex lock/unlock 25 ns | |
| Main memory reference 100 ns 20x L2 cache, 200x L1 cache | |
| Compress 1K bytes with Zippy 3,000 ns 3 us | |
| Send 1K bytes over 1 Gbps network 10,000 ns 10 us | |
| Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD |
Linux:
timedatectl set-local-rtc 1 --adjust-system-clockWindows:
- Navigate to the following key in the left pane of the registry editor:
| After installing it http://sourceforge.net/projects/meld-installer/ | |
| I had to tell git where it was: | |
| git config --global merge.tool meld | |
| git config --global diff.tool meld | |
| git config --global mergetool.meld.path “C:\Program Files (x86)\Meld\meld\meld.exe” | |
| And that seems to work. Both merging and diffing with “git difftool” or “git mergetool” |
| """ | |
| 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 |
These are NOT product / license keys that are valid for Windows activation.
These keys only select the edition of Windows to install during setup, but they do not activate or license the installation.