Understanding Continuous Batching in AI Tools from First Principles
Introduction to Continuous Batching Continuous batching is a method used in AI tools to process data efficiently. It involves grouping data inputs in a way that balances speed and resource use. This approach helps AI models work faster without losing accuracy. Why Continuous Batching Matters in AI AI models often need to handle many requests at once. Continuous batching allows these models to manage incoming data smoothly. This is important for tools that must respond quickly while using computing power wisely. Basic Principles Behind Continuous Batching At its core, continuous batching works by collecting data inputs over time before processing them together. This process reduces waiting times and avoids overload. The key is to find the right batch size and timing to keep the system efficient. How Continuous Batching Works in Practice When a request comes in, the system does not process it immediately. Instead, it waits briefly to gather more requests. Once enough requests ...