Sterling Proffer

All modern machine-learning models are based on “neural networks”—programming which mimics the ways in which brain cells interact with each other. Their parameters describe the weights of the connections between these virtual neurons, weights the models develop through trial and error as they are “trained” to respond to specific inputs with the... See more

To understand your adjacent users, it is helpful to understand the attributes of who is successful today and why they are successful. The reason this is helpful is that your adjacent user is different on one or more of these attributes (but not all). These attributes create vectors of expansion.

This is the publishing paradox nowadays: opportunities come to you in direct proportion to your ability to operate without them.