Applications of Small Language Models in Finance

Ever wondered why a Large Language Model (LLM) is called ‘large’? It\'s all about the scale—these models are trained on massive datasets and contain billions of parameters, enabling them to perform a wide range of tasks with high accuracy. But this scale comes with significant computational costs and an increased margin of errors, including hallucinations where the model generates plausible but incorrect information. The latest article from the E42 Blog, ‘Application of Small Language Models (SLMs) in Finance: A Revolution in Invoice Processing’, delves into how SLMs are reshaping automation in finance. These compact, efficient models are designed for targeted applications, offering precision without the hefty computational costs of larger models. Discover how SLMs streamline operations, reduce latency, and enhance real-time decision-making, making them ideal for business-critical applications. Learn about the unique advantages of SLMs, from lower deployment costs to seamless integration with existing systems, and why they are more reliable than their larger counterparts.