4D Vector fields are a newer feature implemented to efficiently work with AI tools. Vectors are similar to a multidimensional array of numbers. Vector fields do not have a simple nor a single calculation to compute the size of the field in 4D. This is because AI tools are based on representing data inputed as numbers and finding a mathematical function that takes the numbers as inputs and makes an output as a response.

For example, an AI tool used to predict housing prices may take in the following five inputs:

• Square footage
• Number of bedrooms
• Number of bathrooms
• Lot size
• Year built

A model (mathematical formula) is developed which can repesent those inputs into many numbers to expand the information and recognize more paterns. To humans some paterns might be "newer homes sell for more", "the number of bedrooms matter more than bathrooms", or "lot size matters more in rural areas". These patterns are something that humans can recognize, but computers cannot. Instead, by representing the input as something like 100 numbers, models can be developed that makes more accuract predictions based on these inputs. This means that the number of numbers used to represent the data can vary based on the model and the number of inputs.