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.
BERT
A few things I've learned about Google
Don't use Quick Answers at the top of search results + other thoughts on Google from a search expert.
Google's MUM, the ideal search result, and the Esperanto SERP
What if you could have more control over the results of what an algorithm serves up for you? What does the ideal result look like?
The new darling of content intelligence tools: Frase review
Frase is attracting attention as the newest content intelligence tool on the market. Read The Content Technologist review.
The content intelligence conundrum: Why AI alone won't fix your content problem
These search results taste stale. TL;DR you can't optimize content without human originality.
How to diversify your algorithmic Spotify playlists
Do you want to listen to different kinds of artists on Spotify and simultaneously raise a middle finger to systemic racism? Here's how.
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