Imagine sifting through mountains of research papers just to understand a single gene's function. It's a daunting task, even for seasoned scientists. The sheer volume of biomedical literature grows exponentially, making it nearly impossible to keep up. But what if an AI could do the heavy lifting? Researchers have developed GENESUM, an AI system that uses large language models (LLMs) to automatically extract and summarize key information about genes. It works in two stages: First, it intelligently retrieves and filters research papers related to a specific gene, discarding redundant information. This ensures the AI focuses on the most relevant findings. Second, GENESUM uses a fine-tuned LLM to synthesize the information from these selected papers into a concise and coherent summary. This isn't just about summarizing text; it's about connecting complex gene functions with scattered insights from various research studies. Experiments show GENESUM significantly outperforms other methods, producing summaries that closely resemble those written by human experts. The secret to its success lies in the combination of intelligent filtering and the power of LLMs. By leveraging the structure of Gene Ontology (GO) annotations, which describe gene characteristics, GENESUM identifies the most crucial sentences in the research papers. This strategic approach allows the LLM to focus on the most pertinent information, leading to accurate and comprehensive summaries. This breakthrough has significant implications for biomedical research. By accelerating the process of knowledge extraction, GENESUM can empower scientists to make faster discoveries and ultimately develop new treatments and therapies. However, the journey doesn't end here. Challenges remain in ensuring the AI understands the nuances of scientific language and avoids potential biases in the literature. Future research will focus on refining these aspects, ultimately pushing the boundaries of AI-driven scientific discovery. As AI continues to evolve, we can expect even more powerful tools that will transform the way we understand and interact with the vast world of scientific information.