This is introduction and motivation for my course Zero To Mastery AI Researcher & Engineer (in development)
I will build this in public so you can help me figure out what this should be like.
This article is under development but new parts and videos will come almost daily so you can start learning & participating now!
In the end we will try to break the world record on fastest GPT-2 pretraining, which is currently 3 minutes (we can do it by simply implementing DeepSeek's DeepGEMM for 30-50% faster matmuls on H100, but we want to first deeply understand the whole field and be able to build it all from scratch.
My plan is to reach level where I can reproduce GPT-3.5 as open source, this is why I will focus on depth of understanding.
I will publish videos on my YouTube, as well as big full YouTube course in the end.
I am looking for your feedback here and on YouTube.
Which title is best:
- 0 To World-Class AI Researcher & Engineer In 1 Article
- Learn AI Research & Engineering In 1 Article
- Everything To Become Researcher & Engineer In 1 Article
Ilya Sutskever:
- I found that if I read something very slowly, I will eventually uderstand it.
- Coming up with new ideas is modest, it’s more imprtant to understand the results, existing ideas and what’s going on. Main activity is understanding.
Reading new papers & ideas is cool but progress mostly comes from deeply understanding current ones.
Why Open Source
Future of AI & humanity should not be locked behind paywalls, APIs, or corporate vaults.
Big companies can build products, serve customers, and innovate — that’s their role, but the future must be shaped in the open and by everybody.
I believe you — the curious coder, the student with a second-hand laptop, the researcher with no access to H100s — will help build & direct the most powerful technology in human history.
We don’t need billion-dollar clusters — we need brilliant minds across MIT, Tsinghua, random cafes, and Discord channels.
By the people, for the people.
- 🤝 Help others
- 📺 Read, watch, learn
- 🧑💻 Fork the code
- 📈 Beat the benchmarks
- 🌍 Make AI open
Alignment Through Transparency
Safety in AI comes not from secrecy, but from exposure. Only through open code, open evaluations, and public scrutiny can we ensure that AI systems are robust, fair, and aligned with everybody.
Openness accelerates innovation, invites scrutiny, and ensures that knowledge does not become a weapon of the elite.
Understand. Create. Open.
I recommend you master every topic before going to the next one.
If there is not enough material or it's not explained well, please comment below with the feedback, that's why I'm building it in the open.
Top comments (0)