LLM Quantization Project Part 1: What Even Is an LLM? (www.lttlabs.com)

The first installment of a new series on Large Language Models (LLMs) provides an accessible introduction to the foundational concepts underlying these powerful AI systems. From understanding neurons to exploring parameters and how they shape model performance, the article breaks down what makes LLMs function. With billions of parameters to tune during training, the article illustrates how models like GPT require immense computational resources, leading to significant memory requirements (VRAM) for storage and processing during inference. This publication is significant for the AI/ML community as it sets the stage for further discussions on LLM quantization, which is crucial for making these models more efficient and accessible. Future articles will delve into why LLMs consume substantial VRAM and how quantization techniques can compress these models without sacrificing performance. This foundational knowledge is essential for practitioners and enthusiasts who wish to grasp the intricacies of LLMs and keep up with advancements in optimizing and deploying them for various applications.