I just published Awesome DevTools on GitHub!
A curated list of developer tools that make life easier — from debugging & testing to security, CI/CD, and productivity.
https://t.co/olqC24xjq6
I just published Best of AI as open source on https://t.co/zR7Risgyzd.
It's fully static and served on GitHub. Feel free to contribute and suggest any app you think should be there.
https://t.co/5jVqVr2pvF
Just applied to join @Cloudflare for Startups✌️ thanks to @kristianfreeman's tweet
> Free to apply and takes less than a minute
> You can get up to $350k in usage credits
highly recommend doing so if you haven't already
Exploring CUDA books? Check out the curated list of must-reads and community insights on CUDA learning. Deepen your GPU programming with top references and discussions. #CUDA#GPU#Programming#AI https://t.co/QynVTKfuIt
Master CUDA programming with this extensive book list! From beginner guides to advanced optimization & 2024-2026 releases. Essential for AI, HPC & GPU development.
https://t.co/iUqGlgkpoi
#CUDA#AI
THIS REPO HELPS BUILDERS STOP TREATING CUDA LIKE DARK MAGIC
awesome-cuda-books is a curated list of CUDA programming books.
That sounds simple, but it points at a bigger shift: more AI builders are running into the hardware layer whether they planned to or not.
This helps you find the learning path behind the buzzwords:
> GPU programming fundamentals
> memory and performance tradeoffs
> parallel computing concepts
> enough context to know when a model, kernel, or infra claim is real
For you, that means the next edge in AI tooling may come from people who understand both the product layer and the compute layer.
You do not need every founder writing kernels. But you do want enough literacy to know where the bottlenecks actually are.
https://t.co/NOCPynJAp0