Inside the Black Box: Cracking AI and Deep Learning
Arshavir Blackwell, PhD
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Cracking the Code of AI Interpretation
Dive into how we naturally explain neural networks with folk interpretability and why these simple stories fall short. Discover the journey toward mechanistic understandability in AI and what that…
Decoding GPTs Hidden Circuits
Explore how sparse autoencoders and transcoders unveil the inner workings of GPT-2 by revealing functional features and computational circuits. Discover breakthrough methods that shift from observing…
Decoding Attention and Emergence in AI
Explore how attention heads uncover patterns through learned queries and keys, revealing emergent behaviors shaped by optimization. Dive into parallels with natural selection and psycholinguistics to…
When Knowledge Battles Noise in GPT Models
Explore how GPT-2 balances fleeting factual recall with generic responses through internal competition among candidate answers. Discover parallels with human cognition and how larger models navigate…
Inside Circuits: How Large Language Models Understand
Dive into the world of neural circuits within large language models. In this episode, Arshavir Blackwell unpacks how transformer circuits, attention mechanisms, and high-dimensional geometry combine…
Hallucinations, Interpretability, and the Seahorse Mirage
This episode dives into why advanced language models still generate hallucinations, how interpretability tools help us uncover their hidden workings, and what the seahorse emoji teaches us about…
How Transformers Stack Meaning Like Finnish Words
Explore how large language models build up meaning in ways strikingly similar to the layered grammar of Finnish. Arshavir Blackwell reveals why understanding Finnish morphology offers a powerful…
The Mandela Effect in AI: Why Language Models Misremember
Dive into how and why large language models like ChatGPT mirror the human Mandela Effect, reproducing our collective false memories and misquotations. Arshavir Blackwell examines the science behind…
Bridging Circuits and Concepts in Large Language Models
How do millions of computations inside large language models add up to something like understanding? This episode explores the latest breakthroughs in mechanistic interpretability, showing how tools…
How Transformers Turn Words Into Meaning
Embark on a step-by-step journey through the inner workings of transformer models like those powering ChatGPT. Arshavir Blackwell breaks down how context, attention, and high-dimensional geometry…
Can Smaller Language Models Be Smarter?
Today we explore whether mechanistic interpretability could hold the key to building leaner, more transparent—and perhaps even smarter—large language models. From knowledge distillation and pruning…
The Weird Geometry That Makes AI Think
Explore how large language models use high-dimensional geometry to produce intelligent behavior. We peer into the mathematical wilderness inside transformers, revealing how intuition fails, and…
Can We Fix It?
Arshavir Blackwell takes you on a journey inside the black box of large language models, showing how cutting-edge methods help researchers identify, understand, and even fix the inner quirks of AI.…
Using Symbolic AI to Explain LLMs
Delve into the mysterious world of neural circuits within large language models. We’ll dismantle the jargon, connect these abstract ideas to real examples, and discuss how circuits help bridge the…
Peering Inside the Black Box
Mechanistic interpretability and artificial psycholinguistics are transforming our understanding of large language models. In this episode, Arshavir Blackwell explores how probing neural circuits,…
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Inside the Black Box: Cracking AI and Deep Learning has published 15 episodes since November 2025, covering topics in Education, Technology.
Inside the Black Box: Cracking AI and Deep Learning is currently highly active with new episodes weekly. Average episode length is 9m.
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