Unpacking the multilayer perceptrons in a transformer, and how they may store facts. Grant explores the inner workings of large language models, specifically focusing on how they predict and encode information. Understanding the storage and retrieval of facts in AI relies on complex neural architectures and high-dimensional spaces.

Demystifying attention, the key mechanism inside transformers and LLMs. Grant delves into the inner workings of transformers in large language models, focusing on the attention mechanism and its data processing capabilities.

Grant provides an in-depth visual explanation of transformers in AI, discussing their structure, function, and the process of generating text using GPT models. Transformers use attention mechanisms and vast data to revolutionize text generation in AI.

A gentle introduction to the Transformer architecture and its various applications. Understanding and utilizing transformer models are crucial as they increasingly underpin advanced AI applications.

Annotated version of a transformer with comments adds explanation to the model architecture.