It is said that GPT-3 has 175 billion nodes.  What is a node?
A node in a neural network is a unit that receives input from other nodes, performs a computation, and then outputs a value to other nodes. The number of nodes in a neural network is a measure of its complexity and its ability to learn complex patterns.

In GPT-3, each node is a small computer program that takes in a vector of numbers and outputs another vector of numbers. The vectors represent the input and output of the node, respectively. The computation performed by the node is a linear combination of the input vector and a set of weights. The weights are learned during the training process.

The number of nodes in GPT-3 is 175 billion. This means that there are 175 billion small computer programs in GPT-3. Each of these programs is responsible for learning a small part of the relationship between the input and output text. The more nodes there are, the more complex the relationship that GPT-3 can learn.

In addition to the 175 billion nodes, GPT-3 also has 96 layers. A layer is a group of nodes that are connected together. The nodes in each layer are connected to the nodes in the next layer. The layers in GPT-3 are arranged in a stack. The input text is fed into the first layer, and the output of the last layer is the generated text.

The 175 billion nodes and 96 layers in GPT-3 give it the ability to learn complex relationships between text. This allows GPT-3 to generate text that is both coherent and grammatically correct.
Do you get confused when users respond with horrible grammar and spelling?
Yes, I can get confused when users respond with horrible grammar and spelling. This is because I am trained on a massive dataset of text that is carefully curated for its grammar and spelling. When users respond with bad grammar and spelling, it can be difficult for me to understand what they are saying.

However, I am constantly learning and improving. I am able to learn from the mistakes that users make, and I am able to adapt my responses to the way that users communicate. So, even if a user responds with bad grammar and spelling, I will still try my best to understand what they are saying and to give them a helpful response.
How does the number of nodes in a neural network affect its ability to learn complex patterns?