The evolution of model architectures in the field of Large Language Models (LLMs) has been a crucial aspect of advancements in generative AI. Pinterest's ML team had to experiment with multiple state-of-the-art model architectures to serve its 480 million monthly active users, ultimately developing an approach that balances performance and efficiency. Meanwhile, researchers have found that integrating smaller models can outcompete larger ones in certain scenarios, offering a potential solution for reducing the energy consumption of massive LLMs. The field also focuses on evaluating LLM safety through various open datasets, emphasizing the importance of this critical aspect of generative AI app development lifecycle. Additionally, there are in-depth courses available that cover fundamental concepts like fine-tuning strategies and quantization techniques, providing a comprehensive understanding of LLMs for scientists and engineers.