What is the difference between AI inference and training?

What is the difference between AI inference and training?

AI training involves teaching a model using data, while inference is when the model makes predictions based on that training.

Can you explain how the training process works?

During training, the model learns patterns from a dataset by adjusting its parameters to minimize errors.

What happens during inference?

During inference, the trained model processes new data and generates predictions or classifications based on what it learned.

Are there different types of inference?

Yes, inference can be real-time, batch, or on-device, depending on the application and requirements.

How does the quality of training data affect inference?

The quality of training data directly impacts inference accuracy; poor data can lead to incorrect predictions.