Nvidia's data center revenue saw a dramatic increase in the first quarter of fiscal year 2025, reaching $22.6 billion, which is a 427% rise from the previous year and a 23% increase from the previous quarter. I just read through their 10-Q filing for Q1 of 2025, and they wrote that 40% of data center revenue over the past four quarters was driven by inference, which involves using trained neural networks to make predictions and decisions. This indicates strong demand for Nvidia's products in applications where AI is used to analyze and interpret data.

Can any engineers or tech workers clarify why inference would lead to such huge increases? Is my understanding of inference correct?

My understanding is that in the context of artificial intelligence and machine learning, inference refers to the process of using a trained model to make predictions or decisions based on new input data. This contrasts with the training phase, where a model learns from a dataset by adjusting its parameters to minimize the error between its predictions and the actual outcomes.

Why would the company mention this as the reason they are now rolling in cash? Can someone please explain a clear reason why INFERENCE is their reasoning and not demand for AI chips to power data centers?