Table of Contents AI inference sits at the heart of transforming complex AI models into pragmatic, real-world applications and tangible insights. As a critical component in AI deployment, inference is fundamentally concerned with processing input data through trained models to provide predictions or classifications. In other words, inference is the operational phase of AI algorithms, where they are applied to new data to produce results, driving everything from recommendation systems to autonomous vehicles. Leading tech entities, like Nvidia, have spearheaded advancements in AI inference by leveraging their extensive experience in GPU manufacturing and innovation . Originally rooted in the gaming industry, Nvidia has repurposed its GPU technology for broader AI applications, emphasizing its utility in accelerating AI development and deployment. GPUs provide the required parallel computing power that drastically improves the efficiency and speed of AI inference tasks. This transition underscores Nvidia's strategy to foster the growth of AI markets by enhancing the capacity for real-time data processing and model implementation .