In the context of GPT-3 or any neural network, a node refers to a __basic computational unit__ within the network. Think of it as a tiny, interconnected processing unit that performs calculations and data transformations.

Imagine a neural network as a vast web of interconnected nodes. Each node takes in input data, processes it using certain mathematical operations, and then passes the transformed data to other nodes in the network. These connections between nodes allow the network to learn and make predictions based on patterns it discovers in the data.

The number of nodes in a neural network, such as GPT-3, indicates the complexity and capacity of the network. With 175 billion nodes, GPT-3 has an immense number of these computational units, which enables it to learn from and generate text in a highly sophisticated manner.
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