Showing posts from December, 2023

The Evolution of LLMs Over the Last 12 Months

  The evolution of Large Language Models (LLMs) over the last 12 months has been a fascinating journey, marked by advancements in both research and applications. From improved architectures to novel use cases, let's delve into the key developments that have shaped the landscape of LLMs. 1. Architectural Advancements: Over the past year, there have been significant strides in refining LLM architectures. Researchers have been experimenting with novel approaches to enhance model performance, efficiency, and training speed. Transformers, the foundational architecture for LLMs, have seen various modifications to address limitations and improve overall capabilities. 2. Scaling Up: One notable trend has been the continuous effort to scale up LLMs. Larger models, such as GPT-4, have been introduced, pushing the boundaries of what was previously thought possible. Scaling up not only improves the model's capacity to understand context but also contributes to achieving state-of-the-art re