The first step in natural language processing is creating word-numbers, represented as points in space. If this confuses you, you're not alone. Keep reading.
Even in the face of "black box" algorithms, the history of artificial intelligence—natural language processing, more specifically—has left plenty of clues.
To put it another way: optimizing with GEO reverse engineering tactics is like entering a house through a small attic window. GEO ignores that the research frameworks literally embedded in the outputs of the model are the keys to the front door.
Sometimes, mid-planning, you'll hear something like, "We have to build out an entirely new content campaign that doesn't fit into our existing plan or budget because Wolverine is Canadian and his skeleton is infused with adamantine."
Should I, as a website publisher, be angry that an AI summary engine includes my content in its index? Or should I not be so precious about my intellectual property? Here's how I'm making that data-driven decision.
Instead of trucks and newsstands, in 2024 we have web- and social network-based aggregator systems that pipe content directly to consumers via software. Navigating algorithmic distribution is a necessary challenge. Here are some tips.
