E36 Untangling the Decision Making Process of Neural Networks - A Paper Deep Dive of Zoom In: An Introduction to Circuits

E36 Untangling the Decision Making Process of Neural Networks - A Paper Deep Dive of Zoom In: An Introduction to Circuits

Mechanistic interpretability refers to understanding a model by looking at how its internal components function and interact with each other. It's about breaking down the model into its smallest functional parts and explaining how these parts come together to produce the model's outputs.

Neural networks are complex, making it hard to make broad, factual statements about their behavior. However, focusing on small, specific parts of neural networks, known as "circuits", might offer a way to rigorously investigate them. These "circuits" can be edited and analyzed in a falsifiable manner, making them potential foundations for understanding interpretability.

Zoom In looks at neural networks from a biological perspective looking at features and circuits to untangle their behaviors.

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E45 Graphcast - How Google DeepMind is Changing Weather Forecasting

E45 Graphcast - How Google DeepMind is Changing Weather Forecasting

In this episode of the Artificially Unintelligent Podcast, William and Nicolay discuss the groundbreaking work of Google DeepMind on weather forecasting through their recent publication of the Graphca...

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E44 AI’s New Building Blocks: What are Foundation Models?

E44 AI’s New Building Blocks: What are Foundation Models?

In this episode of Artificially Unintelligent, hosts William and Nicolay delve into the intricate world of foundation models in AI. They discuss what these models are – large-scale, machine learning m...

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E43 Diving Deep into Code Llama: The AI Coding Specialist

E43 Diving Deep into Code Llama: The AI Coding Specialist

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