Large language models have significant potential in the life sciences and pharmaceuticals industries, particularly in the analysis and labeling of imagery data. These models can detect and classify cells, aiding in the identification of diseases like cancer, and assist in microscopy tasks such as cell segmentation. With self-supervised learning, models can learn from diverse sources and derive labels without external help. In the field of surgery, co-pilots powered by large language models can provide real-time suggestions and guidance to improve surgical procedures. Moreover, the convergence of different industries, such as manufacturing and healthcare or retail and warehousing, brings new opportunities for AI applications. The use of AI in retail and warehousing spans areas like inventory management, personalized product suggestions, and infrastructure inspections. The crossover between manufacturing and healthcare sectors allows for the transferability of skills and knowledge. However, it's crucial to ensure data quality and avoid bias in large language models, as human expertise remains essential, particularly in critical areas like radiology and laboratory microscopy.
