I gathered the best visuals to help you think better. Here’s what they are:

Perceptions of neural nets over the decades... A thread. [1/30]

so brave

📢 New course! Cats4AI🐱🤖 Learn category theory foundations from the lens of ML, grounded in concrete papers. Open to all! Sign up: cats.for.ai Andrew Dudzik @bgavran3 @_joaogui1 Pim de Haan + fantastic speakers Tai-Danae Bradley Pietro Vertechi David Spivak Taco Cohen

The mice staying dry in the old hollow log

NLP Roadmap 2022 with free resources. This is what you need to build real-world NLP Projects and a Good Foundation. A Thread 🧵👇

Excited to announce our Deep Learning Tuning Playbook, a writeup of tips & tricks we employ when designing DL experiments. We use these techniques to deploy numerous large-scale model improvements and hope formalizing them helps the community do the same! github.com/google-researc…

It was a pleasure working with our fellows Alexa Abbas ⛵️, Helyos and Nora on Apart Research work investigating Latent Adversarial Training (LAT) as a safety fine-tuning method. The study compares LAT to other methods and analyzes its impact on refusal behavior encoding.

We’re very pleased to release our latest study ‘Emergence of Language in the Developing Brain’ Paper: tinyurl.com/5h49xpjv Blog: tinyurl.com/mrtdk8p2 The first systematic investigation of how the neural representations of language evolve as the brain develops. A

Can AI help understand how the brain learns to see the world? Our latest study, led by Joséphine Raugel from FAIR at AI at Meta and École normale supérieure | PSL, is now out! 📄 arxiv.org/pdf/2508.18226 🧵 A thread:

My brain broke when I read this paper. A tiny 7 Million parameter model just beat DeepSeek-R1, Gemini 2.5 pro, and o3-mini at reasoning on both ARG-AGI 1 and ARC-AGI 2. It's called Tiny Recursive Model (TRM) from Samsung. How can a model 10,000x smaller be smarter? Here's how