A resource for content professionals working in the age of algorithms

Baby's umpteenth tradeshow: How the news publishing industry is surfing the AI tide

What I heard and did not hear at ONA

Downtown Chicago, featuring the Chicago Tribune.
286 posts

Tokens and vector embeddings: The first steps in calculating semantics for LLMs

Tokens and vector embeddings: The first steps in calculating semantics for LLMs

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.

When words and math collide: Old-school tried and true language processing algorithms

When words and math collide: Old-school tried and true language processing algorithms

Even in the face of "black box" algorithms, the history of artificial intelligence—natural language processing, more specifically—has left plenty of clues.

The front door to discovery: How natural language processing is the key to visibility in LLMs

a house with a white picket fence with a leafy fall lawn

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.

A digression on trust: Slop blogs and the accomplished UX strategist who doesn't exist

A digression on trust: Slop blogs and the accomplished UX strategist who doesn't exist

Are attractive websites more likely to trick experienced content strategists?

How SEO ends

How SEO ends

Perpetuated primarily by startups hungry for users and the entrepreneurial agencies and thought leaders who serve them, bad data begets worse expectations. Rapid rocketship visibility graphs imply that business results will follow—almost never the case long-term.

CT No.235: Placing bets

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