Senior Generative AI Specialist at @awscloud | Helping startups & enterprises train large-scale models & optimize inferencing. Founders—DM to connect!
Washington, DC
Joined March 2009
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Anton retweeted
BREAKING: NVIDIA just dropped an open 30B model that beats GPT-OSS and Qwen3-30B — and runs 2.2–3.3× faster
Nemotron 3 Nano:
• Up to 1M-token context
• MoE: 31.6B total params, 3.6B active
• Best-in-class performance for SWE-Bench
• Open weights + training recipe + redistributable datasets
You can run the model locally with 24GB RAM.
🚀 New blog: Building custom LLMs for public sector on AWS
Learn how governments can develop national & domain-specific language models that meet sovereignty, compliance & cultural requirements.
Full 6-stage development guide 👇
aws.amazon.com/blogs/publics…
#AWS #AI #PublicSector #LLM#MachineLearning
Anton retweeted
this 17 year old homeschooled girl refuted a conjecture that was unsolved for 40 years, and which professional mathematicians worked on for years without solving
she was rejected from most graduate programs she applied to, because she did not have a degree
Anton retweeted
Learn how @nvidia Dynamo can be quickly setup & seamlessly deployed using Amazon EKS for automated scaling & simplified Kubernetes management ⚡💡🔧
NVIDIA Dynamo supports #AWS services such as Amazon S3, Amazon EFA & Amazon EKS.
👉 go.aws/3IK98YH
Grateful to be featured on AWS for AI Podcast (Ep. 8)! 🎙️ I shared insights on training foundation models at scale + my journey from 🇹🇹 to AWS.
Would love if you could watch, like & comment to support! 🙌 youtu.be/i95xUdpy0qQ?si=3wum…
Anton retweeted
First ever thermodynamic computer was put online internally today.
Soon to be accessed by our first customers.
So excited for things to come.
Anton retweeted
Today, we are releasing 4 hybrid reasoning models of sizes 70B, 109B MoE, 405B, 671B MoE under open license.
These are some of the strongest LLMs in the world, and serve as a proof of concept for a novel AI paradigm - iterative self-improvement (AI systems improving themselves).
The largest 671B MoE model is amongst the strongest open models in the world. It matches/exceeds the performance of the latest DeepSeek v3 and DeepSeek R1 models both, and approaches closed frontier models like o3 and Claude 4 Opus.
Anton retweeted
Verification and Validation in Computational Science and Engineering by Patrick J. Roache.
Anton retweeted
I solved every single problem in the CUDA mode book. A quick thread summarizing this experience and what I learned 1/x
Anton retweeted
“The Coatue team mapped out cloud revenue market share, Oracle at 5%, Amazon at 44% with AWS, Google 19%, Microsoft 30%.
Next to that, they showed NVIDIA GPU allocation: Microsoft and Google match their cloud share. Amazon is 44% cloud revenue but only 20% GPUs. Oracle jumps from 5% to 19%.
Cori comes out of nowhere at 11%.”
“One obvious takeaway is that Amazon has half the share of GPUs than their share of AWS.
So that could mean one of two things, either AWS is behind in AI, that could be one, or they're pursuing a different hardware strategy than its competitors.”
— Bill Gurley @bgurley and Thomas Laffont @thomas_coatue
Anton retweeted
C++23 is not for toy-language coders. If you're playing with PHP, JS, Python, or Rust , stay in your lane. This is for real engineers with academic background.
Anton retweeted
The single most undervalued fact of linear algebra: matrices are graphs, and graphs are matrices.
Encoding matrices as graphs is a cheat code, making complex behavior simple to study.
Let me show you how!
AI is getting out of hand. The USA and China comp is serious and I think it’s good for AI because the gap between us and other countries is huge
