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Colah's Blog (Christopher Olah)
webcolah.github.io·colah.github.io/
Christopher Olah is a co-founder of Anthropic and a pioneer in mechanistic interpretability; his blog contains early foundational essays that influenced both deep learning pedagogy and the interpretability research agenda central to AI safety.
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Summary
Christopher Olah's personal blog featuring highly influential technical essays on neural networks, deep learning, and interpretability. Known for exceptionally clear visual explanations of complex ML concepts, including foundational work on LSTMs, neural network visualization, and mechanistic interpretability.
Key Points
- •Features landmark essays on LSTMs, neural network visualization, and representation learning that shaped modern deep learning understanding
- •Olah is a leading researcher in mechanistic interpretability, and early blog posts laid groundwork for that field
- •Known for unusually clear, intuition-building explanations with strong visual aids
- •Includes foundational pieces like 'Neural Networks, Manifolds, and Topology' and 'Understanding LSTM Networks'
- •Olah later co-founded Anthropic and leads interpretability research there; this blog reflects his intellectual trajectory
Cited by 1 page
| Page | Type | Quality |
|---|---|---|
| Chris Olah | Person | 27.0 |
1 FactBase fact citing this source
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Home - colah's blog
Recent Exciting Things!
Transformer Circuits
Multimodal Neurons
On Distill
Circuits
On Distill
Neural Networks (General)
Neural Networks, Manifolds, and Topology
Deep Learning, NLP, and Representations
Calculus on Computational Graphs: Backpropagation
Neural Networks, Types, and Functional Programming
Recurrent Neural Networks
Understanding LSTM Networks
Attention and Augmented Recurrent Neural Networks
On Distill
Convolutional Neural Networks
Conv Nets
A Modular Perspective
Understanding Convolutions
Groups & Group Convolutions
Deconvolution and Checkerboard Artifacts
On Distill
Visualizing Neural Networks
Visualizing MNIST
An Exploration of Dimensionality Reduction
Visualizing Representations
Deep Learning and Human Beings
Inceptionism
Going Deeper into Neural Networks
On the Google Research Blog
Four Experiments in Handwriting with a Neural Network
On Distill
Feature Visualization
How neural networks build up their understanding of images
On Distill
The Building Blocks of Interpretability
On Distill
Differentiable Image Parameterizations
On Distill
Activation Atlases
On Distill
Circuits
On Distill
Understanding RL Vision
On Distill
Multimodal Neurons
On Distill
Transformer Circuits
Individual Circuits Articles
Zoom In: An Introduction to Circuits
On Distill
An Overview of Early Vision in InceptionV1
On Distill
Curve Detectors
On Distill
Naturally Occurring Equivariance in Neural Networks
On Distill
High-Low Frequency Detectors
On Distill
Curve Circuits
On Distill
Visualizing Weights
On Distill
Miscellaneous
The Real 3D Mandelbrot Set
On my old blog
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Fanfiction, Graphs, and PageRank
Data.List Recursion Illustrated
Visual Information Theory
Research Debt
On Distill
The Paths Perspective on Value Learning
On Distill
Non-Technical Commentary
Research Debt
On Distill
Collaboration &
Credit Principles
Do I Need to Go
to University?
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Traditional Papers
Document embedding with paragraph vectors
On ArXiv [PDF]
TensorFlow: Large-scale machine learning on heterogeneous systems
On TensorFlow.org [PDF]
Concrete Problems in
AI Safety
On ArXiv [PDF]
Conditional Image Synthesis with Auxiliary Classifier GANs
On ArXiv [PDF]
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