Understanding Neural Networks: Mechanistic Interpretability Explained
Explore how researchers decode neural networks with mechanistic interpretability. Learn how AI models recognize images and the importance of understanding AI decisions.
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Research
Shaping the Future of AI with Transformer History
Hyung Won Chung discusses the history and future of Transformer architectures, emphasizing the role of cheaper compute in AI advancements. Learn about encoder-decoder, encoder-only, and decoder-only models.
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Grokking Transformers: Achieving Near-Perfect Causal Reasoning
Explore the groundbreaking concept of grokking transformers and learn how they achieve near-perfect causal reasoning by identifying hierarchical structures in human sentences.
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