Google Colab

⚡️The Future of Notebooks - with Akshay Agrawal of Marimo

Jul 18, 2025 · 28:14

Akshay Agrawal introduces Marimo, an open-source reactive Python notebook built from scratch for AI and data work, emphasizing its lack of Jupyter dependencies and features like reactive execution, built-in UI elements, and pure Python storage for Git versioning. Marimo has surpassed 300k monthly PyPI downloads and more GitHub stars than Jupyter Notebook, used at OpenAI, Hugging Face, and Cloudflare. Agrawal demos interactive data exploration, including a PS5 controller for data annotation, and AI-native code generation with context-aware cell completion. He explains Marimo's UV package integration for inline dependency management and the upcoming MoLab cloud-hosted service on Modal, free for community use, addressing demand for a Colab-like experience. Marimo notebooks can be run as scripts or deployed as data apps, with a fork exploring agent cells for generative analysis.

The Utility of Interpretability — Emmanuel Amiesen

Jun 6, 2025 · 1:53:02

Emmanuel Amiesen, lead author of Anthropic's Circuit Tracing paper, presents the newly open-sourced tools that let anyone inspect how language models compute, revealing that models like Gemma 2-2B engage in genuine multi-step reasoning rather than mere pattern matching. Amiesen demonstrates that the model's internal features causally drive outputs—for instance, suppressing the 'Texas' feature in a capital-of-state query changes the answer from Austin to Sacramento. He explains how sparse autoencoders uncover features shared across languages and modalities, and how attribution graphs map feature interactions. The episode covers practical insights: why jailbreaks succeed (the model prioritizes grammatical completion over refusal) and how planning in poetry generation involves deciding a rhyme before the line begins. Amiesen calls for more researchers to explore interpretability, citing the low barrier to entry with open models and tools.