Wow, this tweet went very viral! I wanted share a possibly slightly improved version of the tweet in an "idea file". The idea of the idea file is that in this era of LLM agents, there is less of a point/need of sharing the specific code/app, you just share the idea, then the

Karpathy又一次，用最简单的方式，点透了AI时代最该用的生产力玩法。 这条帖子能一夜爆火，真的太合理了。 非常接地气和好复制，不用学复杂的工具，不用搞繁琐的RAG配置，学生、研究员、程序员、所有知识工作者，都能立刻上手用。

Nice

let me explain what Karpathy just shared he’s spending way less time using AI to write code and more time using it to build personal knowledge bases the full breakdown:  → he dumps raw sources (articles, papers, repos, datasets, images) into a folder. then has an LLM organize

This is Farzapedia. I had an LLM take 2,500 entries from my diary, Apple Notes, and some iMessage convos to create a personal Wikipedia for me. It made 400 detailed articles for my friends, my startups, research areas, and even my favorite animes and their impact on me complete

Farzapedia, personal wikipedia of Farza, good example following my Wiki LLM tweet. I really like this approach to personalization in a number of ways, compared to "status quo" of an AI that allegedly gets better the more you use it or something: 1. Explicit. The memory artifact

This is a great idea, I’ve been doing this in some form for over a decade. My Staff Eng co-host davidnoelromas reached out this week to ask for more details on how I’ve been using obsidian and AI. This an expanded version of what I told him. I’ve collected possibly too many

Best breakdown of Karpathy's "second brain" system I've seen. My co-founder turned it into an actual step-by-step build. The 80/20: 1. Three folders: raw/ (dump everything), wiki/ (AI organizes it), outputs/ (AI answers your questions) 2. One schema file (CLAUDE.md) that tells

x.com/i/article/2040…

Nine billion miles of driving data just became a chip. Tesla AI5 is finalized for production. The design files are at Samsung in Texas and TSMC in Arizona. The transistors are locked. There is no going back. Tape-out is the hardest gate in semiconductor engineering because

Teslaconomics Tesla AI Best was working with such a great team of AI hardware & software engineers! It was more fun than going to parties on Saturdays by far. Least awesome was that we had to make several design concessions to move fast, but were able to finish tapeout 45 days ahead of schedule. AI6

Getting better

x.com/i/article/2044…

Expanding…

No safety monitors

The best article I read about the LiDAR + HD map behind the Waymo Robotaxis. Clearly, Waymo will die.

Tesla is now rolling out an updated machine learning model to better identify vehicles that have an intent to charge so that wait times at Superchargers are lower: • The model is trained on 9M miles of aggregated and anonymized vehicle trajectory data within the geofence of

Read, please. Important