Feedforward
Personal blogs from the AI community
- Simon Willison's Weblogsimonwillison.net
Textual v4.0.0: The Streaming Release
- Interconnectsinterconnects.ai
Latest open artifacts (#12): Chinese models continue to dominate throughout the summer 🦦
- Nick’s Substacknickjiang.substack.com
A World Beyond Want
- Sebastian Raschka, PhDsebastianraschka.com
The Big LLM Architecture Comparison
- Understanding AIunderstandingai.org
Why Google dismembered a promising AI coding startup
- Ponder on Franz Louis Cesistaleloykun.github.io
A Simple Heuristic Solution for Steepest Descent on Stiefel Manifold
- Token for Tokenblog.jxmo.io
All AI Models Might Be The Same
- Blog - Jason Weijasonwei.net
Life lessons from reinforcement learning
- Lossfunk Lettersletters.lossfunk.com
How to approach research in AI
- antifragile systemsyongzx.substack.com
RL vs next-token-prediction: why should it be a dichotomy?
- Chris McCormickmccormickml.com
Reading and Writing with Projections
- zhengdongwang.comzhengdongwang.com
Superhuman AI in a Normal Age
- One Useful Thingoneusefulthing.org
Against "Brain Damage"
- Victoria Krakovnavkrakovna.wordpress.com
Retrospective on life tracking and effectiveness systems
- Posts on Max Woolf's Blogminimaxir.com
Predicting Average IMDb Movie Ratings Using Text Embeddings of Movie Metadata
- atharva's blogksagar.bearblog.dev
how we accidentally solved robotics by watching 1 million hours of YouTube
- Adjacent Possibleadjacentpossible.substack.com
Machine Readable
- flurries of latent creativityblog.singleton.io
Coding agents have crossed a chasm
- Sam Altmanblog.samaltman.com
The Gentle Singularity
- Neel Nandaneelnanda.io
Post 51: Socratic Persuasion: Giving Opinionated Yet Truth-Seeking Advice
- AI: A Guide for Thinking Humansaiguide.substack.com
David Cope: Composer, computer scientist, and pioneer of computer generated music
- Lil'Loglilianweng.github.io
Why We Think
- karpathykarpathy.bearblog.dev
Vibe coding MenuGen
- Sander Dielemansander.ai
Generative modelling in latent space
- Exploring Language Modelsnewsletter.maartengrootendorst.com
A Visual Guide to LLM Agents
- Nicholas Carlininicholas.carlini.com
Machines of Ruthless Efficiency
- jeremybernste.injeremybernste.in
Deriving Muon
- Thonk From First Principlesthonking.ai
Why PyTorch is an amazing place to work... and Why I'm Joining Thinking Machines
- Jeremy Jordanjeremyjordan.me
Training extremely large neural networks across thousands of GPUs.
- Maharshi's blogmaharshi.bearblog.dev
Learning CUDA by optimizing matrix-vector multiplication (SGEMV) for cuBLAS-like performance - A worklog
- Chip Huyenhuyenchip.com
Common pitfalls when building generative AI applications
- Yi Tayyitay.net
Returning to Google DeepMind
- FOR OUR POSTERITYforourposterity.com
SITUATIONAL AWARENESS: The Decade Ahead
- ruder.ioruder.io
The Evolving Landscape of LLM Evaluation
- Jascha’s blogsohl-dickstein.github.io
Neural network training makes beautiful fractals
- Kemal Erdem Blog RSS Feederdem.pl
Step by Step visual introduction to Diffusion Models.
- Brian Kitanoblog.briankitano.com
Llama from scratch (or how to implement a paper without crying)
- siboehmsiboehm.com
Can Function Inlining Affect Floating Point Outputs? Exploring FMA and Other Consistency Issues
- peterbloem.nlpeterbloem.nl
What design can teach us
- Greg Brockmanblog.gregbrockman.com
It's time to become an ML engineer