Exploring model architecture optimizations for Large Language Model (LLM) inference, focusing on Group Query Attention (GQA) and Mixture of Experts (MoE) techniques.

Scaling laws in AI offer a quantitative framework for understanding the relationship between model size, data, and compute resources. Learn about the Chinchilla scaling law, power laws, and the fut...

Exploration of AI accelerators and their impact on deploying Large Language Models (LLMs) at scale.

Overview of Large Language Model (LLM) inference, its importance, challenges, and key problem formulations.