A late 2025 series aiming to break down the technologies that underpin generative AI, Large Language Models, Natural Language Understanding, and Information Retrieval. Featuring absolutely no math, minimal technical jargon, and lots of pop culture.
A late 2025 series aiming to break down the technologies that underpin generative AI, Large Language Models, Natural Language Understanding, and Information Retrieval. Featuring absolutely no math, minimal technical jargon, and lots of pop culture.
Transformers take static vector embeddings, which assign single values to every token, and expand their context, nearly simultaneously as they process the context of every other word in the sentence. But who cares, let's listen to a pop song!
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.
Are attractive websites more likely to trick experienced content strategists?