Profile avatar
dpetrini.bsky.social
PhD in computer vision/AI - medical imagens. Electronics projects, astronomy, and the history of science. Father, husband, electrical engineer and engineering manager.
15 posts 133 followers 492 following
Regular Contributor

Kkkkkk Lol

Great achievements of chip design.

Excellent, going to the point.

Riccioli's Almagestum Novum (1651) wasn't just the most comprehensive Astronomy Textbook ever. It also linked House Grimaldi to French Royal ancestors, pushing the diplomacy that would ally Monaco with France and protect them from Italian Unification. www.amazon.com/Almagestum-N...

That's a lot of parameters for a large language model. The human brain has ~100 trillion. About 60X GPT-4.

How to Accurately Time CUDA Kernels in Pytorch In a world of increasingly costly machine learning model deployments, ensuring accurate GPU operation timing is key to resource optimization. In this blog post, we explore best practices to achieve this in PyTorch. www.speechmatics.com/company/arti...

The best

Slides for "Table Foundation Models" I explain why these models can strongly outperform tree-based models, what are the intuitions, hopefully pointing to ways forward for more improvement speakerdeck.com/gaelvaroquau...

Ilya Sutskever NeurIPS talk [video] Discussion

I love Mad Magazine

Just put together a starter pack for Deep Learning Theory. Let me know if you'd like to be included or suggest someone to add to the list! go.bsky.app/2qnppia

Are you Sirius?

Stochastic Gradient Descent - AI Flashcards

I was deeply honored to receive the 2024 VinFuture Prize from the VinFuture Foundation in Hanoi, alongside Geoff Hinton, Jensen Huang, @ylecun.bsky.social and @drfeifei.bsky.social, for our contributions to the advancement of deeplearning. vinfutureprize.org/laureates/pr...

I’m on the academic job market this year! I’m completing my @uwcse.bsky.social @uwnlp.bsky.social Ph.D. (2025), focusing on overcoming LLM limitations like hallucinations, by building new LMs. My Ph.D. work focuses on Retrieval-Augmented LMs to create more reliable AI systems 🧵

PDF understanding is key issue for RAG.

Anthropic released an interesting thing today: an attempt at a standard protocol for LLM tools to talk to services that provide tools and extra context to be used other the models modelcontextprotocol.io

Reposting our work here: ieeexplore.ieee.org/document/983...

Evaluating LLM output is hard. For many teams, it's the bottleneck to scaling AI-powered product. A key mistake is defining eval criteria w/o actually LOOKING AT THE DATA. This leads to irrelevant / unrealistic criteria + lots of wasted effort. Thus I built AlignEval.com

Motivation For Deep Learning