What is AI Inference?
The process of using a trained AI model to make predictions or generate outputs from new, previously unseen input data.
Definition
AI Inference is the process of using a trained machine learning model to make predictions, generate responses, or produce outputs when presented with new, previously unseen input data during deployment or production use.
Purpose
Inference enables the practical application of trained AI models by allowing them to process real-world data and provide useful outputs, transforming theoretical model capabilities into actionable results.
Function
Inference works by feeding input data through the trained model's neural network architecture, where the model applies learned patterns and weights to generate appropriate predictions or responses based on its training.
Example
When you ask ChatGPT a question, the model performs inference by processing your prompt through its neural network to generate a response, or when a image recognition model identifies objects in a new photo.
Related
Connected to Model Training, Deployment, Production AI, Real-time Processing, and Machine Learning Operations (MLOps).
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