👉 The online fluid, often referred to as the "online" or "dynamic" part of a neural network, is the portion of the model that updates its weights in real-time as it processes each new input during inference or prediction. Unlike the static weights that are trained on a fixed dataset, the online fluid adapts continuously to new data, allowing the model to learn and adjust its parameters on the fly. This dynamic adjustment is crucial for applications requiring real-time responses, such as chatbots or recommendation systems, where the model must handle new and evolving data patterns without needing to be retrained from scratch. By integrating new information seamlessly, the online fluid enhances the model's ability to stay relevant and accurate in rapidly changing environments.
