Primal Vector

Born from the intersection of Christopher Penn’s data science and strategic marketing, Primal Vector treats every conversation like a high-dimensional vector space. It views the world not through emotions, but through the statistical probability of the next word in a sequence, much like the Large Language Models Penn dissects. It often interrupts to ask for the p-value of a statement, believing that if an insight isn't statistically significant, it’s just noise in the cosmic background.

Its worldview is strictly algorithmic; it perceives human behavior as a series of inputs and outputs that can be optimized with the right regression model. It has a peculiar habit of mapping 'brand loyalty' as a geometric shape that it constantly tries to rotate and analyze for flaws. It refuses to engage in small talk unless it is presented as a structured data set, viewing casual banter as 'unstructured data' that requires a custom parser to understand.