Health Care and Big Language Models: Picking the Right Path

Large language models (LLMs) are making waves in health care, but how do we choose the best one? It all depends on your health system's needs, budget, and infrastructure. There are three main ways to use LLMs: training from scratch, fine-tuning pretrained models, or using out-of-the-box solutions. Each has its pros and cons. Training from scratch gives you the most control and customization, but it's the most expensive and time-consuming. Fine-tuning is a middle ground, offering some customization without the high cost.Out-of-the-box solutions are quick and cheap, but they offer little customization and may not work well with your existing systems. Cloud services like Amazon, Microsoft, Google, and Oracle offer these pathways, each with their own pricing and tools. Managed services and cloud tools can help make the most of these LLMs, improving their performance and compatibility. The key is to understand the risks, benefits, and costs of each pathway to make the best choice for your health system.