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John Carmack explains how he applies Nassim Taleb's "anti-fragile" concept to his work, enjoying the thrill of new ideas while accepting that many won't succeed. Source: Deep Thoughts Engineering Speaker Series: John Carmack
As AWS continues aggressive load shedding as they limp their systems back into a healthy state, it'd be a good time to read the Metastable Failures in Distributed Systems paper. It's a quick read and I bet you'll find yourself nodding along:
Theory without practice is useless. Show me your code.
> Find a paper on arXiv. > Build a shitty version of it. > Open source it on GitHub. >Write a post explaining why it's shitty. That GitHub repo is 100x more valuable than any certificate.
Great example, why less people deliver bigger impact
Telegram founder Pavel Durov on what separates A Players from B Players “I can recall a few instances in my career where firing an engineer actually resulted in an increase in productivity,” Telegram founder Pavel Durov begins. He gives an example of two Android engineers…
Elon Musk's most inspiring speech that gives a clear understanding of his lifetime mission "There are a lot of negative things in the World, but life can't just be about solving one problem after another, they need to be things that inspire you, that make you glad to be alive"
BOOM! 💥 Today I added WebGPU support for @karpathy's nanochat models, meaning they can run 100% locally in your browser (no server)! The d32 version runs at over 50 tps on my M4 Max 🚀 Pretty wild that you can now deploy AI applications using just a single index.html file 😅
Excited to release new repo: nanochat! (it's among the most unhinged I've written). Unlike my earlier similar repo nanoGPT which only covered pretraining, nanochat is a minimal, from scratch, full-stack training/inference pipeline of a simple ChatGPT clone in a single,…
NVIDIA over USB4 on MacBook is ready to try! * ADT-UT3G dock + any 30/40/50 series GPU * Disable SIP * Install driver `extra/usbgpu/tbgpu` * Install NVK compiler `brew install tinymesa` * Test with: `DEBUG=2 NV_NAK=1 NV=1 python3 test/test_tiny.py TestTiny.test_plus`
My pleasure to come on Dwarkesh last week, I thought the questions and conversation were really good. I re-watched the pod just now too. First of all, yes I know, and I'm sorry that I speak so fast :). It's to my detriment because sometimes my speaking thread out-executes my…
The @karpathy interview 0:00:00 – AGI is still a decade away 0:30:33 – LLM cognitive deficits 0:40:53 – RL is terrible 0:50:26 – How do humans learn? 1:07:13 – AGI will blend into 2% GDP growth 1:18:24 – ASI 1:33:38 – Evolution of intelligence & culture 1:43:43 - Why self…
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new sitcom idea: 18 yo chinese ccp spy joining an SF defense startup and realizing no one has actually done any work because they are too busy going to parties and chasing social clout, so she has to create all of the tech herself before she can send it back home
>Augmented reality + generative AGI means people can suddenly do expert-level work they never trained it's already here
Two underdiscussed possibilities: Augmented reality + generative AGI means people can suddenly do expert-level work they never trained for. Real-time overlays guide you through any task - repairs, construction, technical assembly, complex procedures. Visual guides showing…
Starship vs A380 & 737-8 When stacked with the Super Heavy booster Starship is taller than an A380 and a Max-8 on top of each other, 123m vs 73m+40m
Starship vs 737-8 Easy to forget how massive Starship is, 52m long vs 40m for a Max-8
18 months ago, @karpathy set a challenge: "Can you take my 2h13m tokenizer video and translate [into] a book chapter". We've done it! It includes prose, code & key images. It's a great way to learn this key piece of how LLMs work. fast.ai/posts/2025-10-…
Video lectures, MIT 6.824 Distributed Systems spring 2020, by Robert Morris nil.csail.mit.edu/6.824/2020/gen… youtube.com/playlist?list=…
ML concepts every data scientist should know for interviews: Bookmark this. 1. Bias-Variance Tradeoff 2. Cross-Validation Strategies 3. Regularization (L1, L2, Elastic Net) 4. Class Imbalance & Sampling Techniques 5. Feature Engineering & Selection 6. Overfitting vs…
Training Andrej Karpathy’s Nanochat on 4x RTX 3090s at 225W each: Step 2,694/21,400 (12.59% done) Loss: 3.14 Runtime: 6.78 hours Throughput: 3,600 tok/sec Temps: 52-57°C VRAM: 19GB/24GB per card Total cost: 15$ at 55h Zero errors, perfectly stable
I don't like courses. Most were a waste of time. Yes, even at Stanford. If you're new to ML, take CS231N.
your honor i object, i dont know about harvard but stanford literally releases SOTA courses
My meeting budget: 5 min - meet someone new 10 min - solve a problem 15 min - identify + solve a problem Parkinson’s law: work expands so as to fill the time available for its completion.
MIT's 6.851: Advanced Data Structures (Spring'21) courses.csail.mit.edu/6.851/spring21/ This has been on my recommendation list for a while, and the Memory hierarchy discussions are great in the context of cache-oblivious algorithms.
"Cache‑Oblivious Algorithms and Data Structures" by Erik D. Demaine erikdemaine.org/papers/BRICS20… This is a foundational survey on designing cache‑oblivious algorithms and data structures that perform as well as cache‑aware approaches that require hardcoding cache size (M) and block…
50 LLM Projects with Source Code to Become a Pro 1. Beginner-Level LLM Projects → Text Summarizer using OpenAI API → Chatbot for Customer Support → Sentiment Analysis with GPT Models → Resume Optimizer using LLMs → Product Description Generator → AI-Powered Grammar…
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