Feedforward
Personal blogs from the AI community
- Understanding AIunderstandingai.org
Waymo is finally ready for freeway service
- Simon Willison's Weblogsimonwillison.net
Quoting Steve Krouse
- Interconnectsinterconnects.ai
Interview: Ant Group's open model ambitions
- One Useful Thingoneusefulthing.org
Giving your AI a Job Interview
- Sebastian Raschka, PhDsebastianraschka.com
Recommendations for Getting the Most Out of a Technical Book
- Lossfunk Lettersletters.lossfunk.com
Sequential scaling outperforms parallel scaling for LLMs
- Ponder on Franz Louis Cesistaleloykun.github.io
Steepest Descent on Finsler-Structured (Matrix) Geometries via Dual Ascent
- Posts on Max Woolf's Blogminimaxir.com
Claude Haiku 4.5 does not appreciate my attempts to jailbreak it
- AI: A Guide for Thinking Humansaiguide.substack.com
Do AI Reasoning Models Abstract and Reason Like Humans?
- Sam Altmanblog.samaltman.com
Sora update #1
- karpathykarpathy.bearblog.dev
Animals vs Ghosts
- Nick’s Substacknickjiang.substack.com
Teaching Algorithms in Ethiopia
- Adjacent Possibleadjacentpossible.substack.com
The Blank Page Revolution
- Shreya Shankarsh-reya.com
In Defense of AI Evals, for Everyone
- Neel Nandaneelnanda.io
MATS Applications Open (Due Aug 29)
- zhengdongwang.comzhengdongwang.com
Two recent updates
- antifragile systemsyongzx.substack.com
Can GPT-5 Pro win the gold medal on International Linguistics Olympiad (IOL)?
- Nicholas Carlininicholas.carlini.com
Gate-level emulation of an Intel 4004 in 4004 bytes of C
- Token for Tokenblog.jxmo.io
'AI' just means LLMs now
- Chris McCormickmccormickml.com
Output Latent Spaces in Multihead Attention
- Blog - Jason Weijasonwei.net
Life lessons from reinforcement learning
- Victoria Krakovnavkrakovna.wordpress.com
Retrospective on life tracking and effectiveness systems
- atharva's blogksagar.bearblog.dev
how we accidentally solved robotics by watching 1 million hours of YouTube
- flurries of latent creativityblog.singleton.io
Coding agents have crossed a chasm
- Lil'Loglilianweng.github.io
Why We Think
- Sander Dielemansander.ai
Generative modelling in latent space
- Exploring Language Modelsnewsletter.maartengrootendorst.com
A Visual Guide to LLM Agents
- 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