EVERYTHING A SENIOR ENGINEER NEEDS TO KNOW ABOUT WHAT'S INSIDE AN LLM
LLMs are made of Transformers, which use self-attention mechanisms to improve processing efficiency and address issues associated with traditional RNNs, such as sequential bottleneck and long-range decay of information. This post goes over various components of Transformers, including positional encoding, attention mechanisms, and the importance of architecture design in enhancing AI model performance.