Andrej Karpathy spent 8 years at OpenAI and Tesla
Last week, he compressed everything he knows into one free 2-hour lecture
Agents → Loops → Graphs → Self-Improving Systems
People spend $15K on bootcamps that teach less than this
This lecture beats most paid AI engineering courses
You probably don't have 2 hours right now
Don't let this vanish from your feed
Watch it
Then read the guide below
MF retweeted
one way to update one's knowledge on llm improvements is to check out the nanogpt speedrun leaderboard
btw - muon, the optimizer that state of the art opensource models use, was discovered by Keller Jordan in this competition in 2024, before that adam/adamw was the algorithm most models used since 2014
github.com/kellerjordan/modd…
MF retweeted
We have had a few questions about our perfect applicant, so here are a few made up examples:
You graduated from a Phd in machine learning a couple of years ago and have been doing great work at one of the frontier labs, pushing the limits of the current paradigm. Now you think it's time to aim higher. We want you to apply.
You are about to graduate from a stellar Phd in machine learning during which you have made contributions that have started to shape the field. We want you to apply.
You graduated from a stellar Phd in machine learning and have been doing a postdoc since. We want you to apply.
You are an academic in machine learning, leading your own group but have been wondering whether this really is the right setup to make a difference. We want you to apply.
You are brilliant and a great team player. You focus on creating exponentially large pies rather than fighting over the size of your slice. We want you to apply.
TL;DR: This is one of the most important and exciting opportunities in AI on the planet - please read on.
The British Open-ended Learning & Discovery Lab is creating the perfect place for paradigm breaking AI research in the name of open-source and open-science. We have agency, we funding, we have unprecedented amounts of compute*, but WE NEED YOU!
..and we have created the dream job for you: The BOLD Fellow. This job combines a fast-moving, high agency, collaborative environment with full academic freedom and a salary that pays the bills.
Apply by noon UK time on the 15th of September for this once in a lifetime opportunity to shape the history of our field and of our planet:
my.corehr.com/pls/uoxrecruit…
*by academic standards
MF retweeted
Your gaming PC can now serve frontier models at interactive speed using official checkpoints without extreme quantization!
Qwen3.6 35B → 8GB RTX 4060 laptop @ 39 tok/s
DeepSeek-V4-Flash 284B → RTX 5090 desktop @ 22-25 tok/s
GLM-5.2 753B → RTX PRO 6000 workstation @ 15 tok/s
Run your claude code or codex now with frontier model for $0
Meet FreeToken 🧵
MF retweeted
TL;DR: This is one of the most important and exciting opportunities in AI on the planet - please read on.
The British Open-ended Learning & Discovery Lab is creating the perfect place for paradigm breaking AI research in the name of open-source and open-science. We have agency, we funding, we have unprecedented amounts of compute*, but WE NEED YOU!
..and we have created the dream job for you: The BOLD Fellow. This job combines a fast-moving, high agency, collaborative environment with full academic freedom and a salary that pays the bills.
Apply by noon UK time on the 15th of September for this once in a lifetime opportunity to shape the history of our field and of our planet:
my.corehr.com/pls/uoxrecruit…
*by academic standards
MF retweeted
Updated CS 8803 "Large Language Model" class at @GeorgiaTech this year for 2026!
The reading list spans pretraining, MoE, reasoning, RL & self-play, agents, long-context, test-time scaling, diffusion LMs, safety, interpretability, and more.
👉 cocoxu.github.io/CS8803-LLM-…
🔗 docs.google.com/spreadsheets…
How AI agents reproduced ICML 2026 papers xitter.cf/i/broadcasts/1yxBeeXBD…
MF retweeted
I accidentally discovered how to compress a semester of learning into 48 hours.
A grad student at MIT showed me his NotebookLM setup. I thought he was just organized. Then I watched him pass a qualifying exam on a subject he'd never studied before.
Here's exactly what he did:
First: he didn't upload a textbook.
He uploaded 6 textbooks, 15 research papers, and every lecture transcript he could find on the subject.
Then he asked NotebookLM one question:
"What are the 5 core mental models that every expert in this field shares?"
Not "summarize this." Not "explain this topic."
Mental models. The stuff that takes professors years to develop.
But the next part is what broke my brain.
He followed up with:
"Now show me the 3 places where experts in this field fundamentally disagree, and what each side's strongest argument is."
In 20 minutes he had a map of the entire intellectual landscape of the field:
the debates, the consensus, the open questions.
Most students spend a full semester just figuring out what those debates even are.
Then he did something I've never seen before.
He asked:
"Generate 10 questions that would expose whether someone deeply understands this subject versus someone who just memorized facts."
He spent the next 6 hours answering those questions using the source material. Every wrong answer triggered a follow-up:
"Explain why this is wrong and what I'm missing."
By hour 48, he could hold a conversation with his thesis advisor without getting destroyed.
The tool didn't change. The questions did.
Most people treat NotebookLM like a fancy highlighter.
These students are using it like a private tutor who has read everything ever written on the subject.
The difference between a semester and 48 hours isn't the amount of content.
It's knowing which questions to ask.
Looking forward for discovery models.
Announcing Discovery Loop!
I am very excited to announce that, along with my longtime friends and collaborators @Sanjay_Ghemawat, @OriolVinyalsML and @quocleix, we are founding Discovery Loop (@DiscoLoopAI), a Public Benefit Corporation whose mission is to automate machine learning, science, and engineering to accelerate discoveries and progress. The four of us have worked together for 14 to 30 years, and have helped build some of the world’s most used products, infrastructure and AI models, and we’re excited to turn our attention to this ambitious endeavor.
♾
Learn more at: discoveryloop.com
























