AI inference is the process where a trained AI model makes predictions or generates outputs in response to new data, playing a crucial role in the functionality of AI applications like ChatGPT and Google Translate. This stage must balance speed, reliability, and cost-efficiency, often involving complex optimizations across multiple layers of the technology stack, including model servers, frameworks, and infrastructure. The Baseten Inference Stack offers a comprehensive solution by integrating open-source technologies and proprietary enhancements to optimize performance. Key metrics for measuring inference success include latency, throughput, and cost, each requiring careful consideration to ensure efficient and reliable AI applications. Despite the challenges in balancing these metrics, advanced inference systems enable AI to deliver real-time, reliable, and cost-effective services to millions of users worldwide.