It's now me vs me

I spent last week at Neurips (the big ML/AI conference) and had hundreds of amazing technical conversations with old friends and new. Beyond the technical, I'm deeply grateful for the love from all the folks who stopped me in the hallways and in the street to say kind words and

Andrej Karpathy, Eureka Labs founder & former Director of AI at Tesla, breaks down how LLMs like ChatGPT "download the Internet." Watch the full beginner-friendly breakdown here: https://t.co/doph3alGnE

never think before spending money on books. also, if you want one and dont want to buy, drop the link below and i will gift it to you

😋😋😋🙂🤌

I am feeling sick 🤧🤢

Turned 22 today. AMA !! Quick look at the past year: > landed an ML internship at @Apple, then joined @MSFTResearch to work on agentic memory > secured a six figure USD research grant from @Meta to build SoTA AI models at @cognitivelab_ai > crossed 10k GitHub stars across my

No worries 🤣 @rrishabk please try to learn AI from scratch Data analytics-> ML, DL ,CV,NLP, THEN MOVE TO LEARNING ADV LLMs -> gen ai ( how it works exactly) the move to fine tuning and other adv concepts Kid !! 🤌🤌

tldr: 2 guys with a laptop removed ~70% of the world’s compute bill for free, cuz why not

A new era will begin now

We have just used the @Nvidia H100 onboard Starcloud-1 to train the first LLM in space! We trained the nano-GPT model from Andrej @Karpathy on the complete works of Shakespeare and successfully ran inference on it. We have also run inference on a preloaded Gemma model, and we

Build this Markdown render website where you can share the preview via url ( i am not finding any so i created this ) https://t.co/ZtjgYzOwdL

i won the @xai hackathon by making ads for X Videos introducing Halftime. targeted ad generation using AI that feels like a part of your movies and shows built with @yuviecodes @lohanipravin

I have been fine-tuning LLMs for over 2 years now! Here are the top 5 LLM fine-tuning techniques, explained with visuals: First of all, what's so different about LLM finetuning? Traditional fine‑tuning is impractical for LLMs (billions of params; 100s GB). Since this kind of

Someone please write AWS @awscloud docs again using @mintlify please I am tired of reading boring docs

Also so many are down again Obviously if we are dependent on a product which is that much big This is possible Kind a monopoly

Again @Cloudflare 😭🙏

> my top 8 local LLMs > to run at home > for December 2025 > MiniMax-M2 at #1 > great for agentic workflows thanks to interleaved thinking > very solid at coding & good at UI/design as well > fits on 2x RTX PRO 6000 > or 8x RTX 3090s w/ full context > (specifically

In this article, I have tried to cover the breadth of distributed GPU training, which includes: > arithmetic intensity via shared memory data reuse > BF16 precision for memory and training stability > CUDA kernel programming for GPU execution > data, pipeline, and Tensor