To understand how AI accelerators work, let’s break down the process into simple steps:
4.1. Data Preparation
AI tasks require a significant amount of data, which is first prepared and fed into the accelerator. This data can include text, images, audio, or any other form of input relevant to the task at hand.
4.2. Model Training
AI models need to be trained before they can perform their intended tasks. This training involves adjusting the model’s parameters using the input data to minimize errors. AI accelerators excel in this phase, as they can handle the complex mathematical calculations quickly.
4.3. Model Inference
Once the model is trained, it can perform inference, which means making predictions or decisions based on new, unseen data. This is the phase where AI accelerators truly shine. They rapidly process the data and provide real-time responses.