SoftMax @DataGod_v1
In God We trust all others must bring data and memes San Francisco, CA Joined June 2022-
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(1/N) How close are we to enabling robots to solve the long-horizon, complex tasks that matter in everyday life? 🚨 We are thrilled to invite you to join the 1st BEHAVIOR Challenge @NeurIPS 2025, submission deadline: 11/15. 🏆 Prizes: 🥇 $1,000 🥈 $500 🥉 $300
New in-depth blog post - "Inside vLLM: Anatomy of a High-Throughput LLM Inference System". Probably the most in depth explanation of how LLM inference engines and vLLM in particular work! Took me a while to get this level of understanding of the codebase and then to write up…
GPT-OSS bug fixes + Flex Attention support is here! 1. Fixed float16 infinite losses (>65504 overflows) 2. SWA=128 Flex default uses 129 tokens (extra 1) 3. Fixed MXFP4 inference swiglu_limit=7.0 not set 4. Sink token moved to index 0 5. FA3 doesn't have attn sink dX Details:…
GPT-OSS bug fixes + Flex Attention support is here! 1. Fixed float16 infinite losses (>65504 overflows) 2. SWA=128 Flex default uses 129 tokens (extra 1) 3. Fixed MXFP4 inference swiglu_limit=7.0 not set 4. Sink token moved to index 0 5. FA3 doesn't have attn sink dX Details:… https://t.co/rUbvvjGW7W
A brilliant essay that really captures the world view that all the players in the game are operating under. 'AGI by 2027 is strikingly plausible' - all it needs is for the trend lines to hold just a little bit longer. Buckle in for wild few years as we find out.
A brilliant essay that really captures the world view that all the players in the game are operating under. 'AGI by 2027 is strikingly plausible' - all it needs is for the trend lines to hold just a little bit longer. Buckle in for wild few years as we find out.
Router wasn't learning at first, we debugged it step-by-step and showed you how despite perfect load balancing, routing can be completely useless. We root caused it and fixed the problem. Papers skip the methodology, but you can find all details in our part 3 of MoE 101 series…
Router wasn't learning at first, we debugged it step-by-step and showed you how despite perfect load balancing, routing can be completely useless. We root caused it and fixed the problem. Papers skip the methodology, but you can find all details in our part 3 of MoE 101 series…
Just wrote a post on my understanding of the statistics behind block sparse attention. My take is that it works by using the "learned similarity gap," which creates a simple SNR formula connecting retrieval quality with model architecture. Read more: guangxuanx.com/blog/block-spa…
can't wrap my head around how cool this is
i remade tiny-tpu to support both inference and training! we successfully tested our architecture on the classic XOR problem. here's what i learned throughout the process:👇
i remade tiny-tpu to support both inference and training! we successfully tested our architecture on the classic XOR problem. here's what i learned throughout the process:👇 https://t.co/upJoqqH4I0
The Illustrated GPT-OSS New post! A visual tour of the architecture, message formatting, and reasoning of the latest GPT. Link in 🧵
Just published my new article, "Marketplace": my first attempt at efficient GPU training without backprop 😄🎉 I've been considering eliminating backprop for a while. I had an idea, experimented for two weeks, and it worked! Here's how it works:
@MaximeRivest You might find this interesting: arxiv.org/abs/2505.18350
Fastest inference engine for LLMs! LMCache is an LLM serving engine that reduce Time to First Token (TTFT) and increase throughput, especially under long-context scenarios. 100% Open Source
puzzles repo: github.com/srush/Triton-P… answers repo (i recommend understanding from the first few answers and then not looking at latter ones): github.com/SiriusNEO/Trit…
this repo is a good place to start learning about triton kernels, it will take you a day or two to complete these puzzles once you get the hang of it.
Google has released a new open source model... That runs on just 0.5 GB of RAM. Yes. You can fine-tune it for free to make it better than the giant models at your tasks. Quick steps to fine-tune Gemma 3 270M below
I think I found a based Substack on low-level GPU programming by accident. He has some extensive articles on CUDA programming, building LLM inference engines, looking inside GPUs and much more. even the name is cool: "From Scratch". bro.
The perfect weekend article just dropped by @rasbt on gpt-oss architectures. It’s wild to see how fast these architectures have leveled up since GPT-2 in 2019. abs positional emb → RoPE GELU MLP → Swish + SwiGLU one dense feed-forward → MoE Multi-head attention → GQA …
this is the most comprehensive resource i found so far which gathers all the key things to know about Context Engineering. Absolutely beautiful work.
Latest TRL release brings major upgrades for multimodal alignment! We dive into 3 new techniques to improve VLM post-training in our NEW BLOG: 🌋 GRPO 🎞️ GSPO 🐙 MPO ➕ Extra: vLLM integration for online training w/ transformers backend link in the next one
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Charly Wargnier @DataChaz
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93K Followers 962 Following AI and ML, ex-Hugging Face, World's First 4x GM @kaggle, YouTube 100k+: https://t.co/BHnem8fTu5
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