CT No.242: What's your vector, Victor?
How to understand tokens and vector embeddings, for word people.
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CT No.241: TF? ID(GA)F: The old faithfuls of language processing
Even in the face of "black box" algorithms, the history of artificial intelligence—natural language processing, more specifically—has left plenty of clues. While we can't understand the full equation, we can see how building blocks create common patterns in how current algorithms process language.
CT No.240: Mad inconvenient infrastructure
Infrastructure, no matter how solid or planned or continuously improved, gets messy. Observing humanity in July feels like the ultimate UX research experiment.
CT No.239: Please automate the tedious part for me
July is prime chart-making season. July 2025 is one more chartmaking season that will not be powered by artificial intelligence, and here's why.
CT No.238: Language is the technology
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.
CT No.237: Trust issues
Are attractive websites more likely to trick experienced content strategists?
CT No.240: Mad inconvenient infrastructure
Infrastructure, no matter how solid or planned or continuously improved, gets messy. Observing humanity in July feels like the ultimate UX research experiment.
CT No.239: Please automate the tedious part for me
July is prime chart-making season. July 2025 is one more chartmaking season that will not be powered by artificial intelligence, and here's why.
CT No.238: Language is the technology
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.
CT No.237: Trust issues
Are attractive websites more likely to trick experienced content strategists?
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