Why does AI inference matter?#
Inference puts the AI model to work on your business's current data, turning its learned patterns into actionable outputs like forecasts, classifications, or recommendations that can improve decision-making and automate tasks.
How does AI inference work?#
The journey of an AI model has two key phases. The first is "training," where the model learns patterns and relationships by analysing a massive amount of historical data. Think of this as the AI studying and preparing for its job.
Inference is the second phase, where the fully trained model is put into production. When presented with a new, unseen piece of data—such as a customer support ticket or a photo for analysis—the model applies its learned knowledge to make a prediction or generate a response. This live application of the model to produce a useful result is the act of inference.
How is AI inference different from training?#
Inference is the operational phase where a trained AI model is actively used to provide immediate value on live data. In contrast, Training is the initial development phase where the model is built by learning from historical data; this process is far more computationally expensive and time-consuming, and it must be completed before any inference can happen.