Imagine an AI that could not only read, but truly understand the complex language of proteins. This is the ambitious goal of EvoLlama, a groundbreaking new AI model that's pushing the boundaries of what's possible in the field of bioinformatics. Proteins are the microscopic workhorses of our bodies, responsible for countless essential functions. Understanding their intricate structures and interactions is crucial for developing new medicines, therapies, and a deeper understanding of life itself. However, deciphering this 'language of life' has been a monumental challenge. Traditional AI models have struggled to grasp the complex interplay between a protein's amino acid sequence (its 'letters') and its 3D structure (its 'shape'), both of which are essential for determining its function. EvoLlama tackles this challenge head-on by incorporating both sequence and structural information. Unlike previous models that treat amino acid sequences simply as text, EvoLlama utilizes advanced protein language models (PLMs) like ESM-2 to capture evolutionary knowledge encoded within these sequences. Simultaneously, it uses structure-based encoders like ProteinMPNN to understand the geometric features of a protein’s 3D form. These multimodal representations are then ingeniously fused and projected into a format that a large language model (LLM), similar to the technology powering ChatGPT, can understand. This enables the LLM to reason about proteins in a way never before possible. Researchers have demonstrated EvoLlama’s impressive capabilities by testing it on a variety of tasks, including predicting protein function, identifying catalytic activity, and even forecasting how proteins interact with each other. In many cases, EvoLlama outperforms existing state-of-the-art models, demonstrating the power of its multimodal approach. While EvoLlama utilizes predicted protein structures, which are not always perfectly accurate, it exhibits a remarkable ability to generalize its knowledge. This opens the door for future research using experimentally determined structures, potentially leading to even more accurate predictions. EvoLlama is more than just an incremental improvement; it represents a paradigm shift in how we apply AI to understand the building blocks of life. By bridging the gap between protein encoders and LLMs, it unlocks a new era of possibilities for drug discovery, disease research, and our understanding of the intricate machinery that makes life possible. The research team plans to release their code publicly, empowering scientists worldwide to build upon their work and accelerate progress in this vital field.