Experts Predict LLMs to Shift from "One Model Fits All" to Specialized Models
ArcBjorn Blog
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Contributed by: Drex DeFord
Summary
By late 2025, the field of large language models (LLMs) is expected to transition from a generic "one model fits all" paradigm to a more tailored ecosystem featuring smaller, specialized models (SLMs). This change is spurred by rapid advancements in training compute and dataset expansion, but it also raises concerns around diminishing returns and high energy consumption. The technical foundation relies on critical factors such as architecture, diverse training data, and fine-tuning processes, which enhance models like GPT-5 and Claude for specific use cases. As healthcare professionals navigate this evolving landscape, the emphasis will shift towards selecting the most appropriate AI tools for targeted applications, optimizing care delivery and efficiency.
