how algorithms work

Content algorithms are complicated. It's time to break them down so everyone can understand them. Read these stories to learn how algorithms work.

41 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 facts of lore: What happens when the most reputable information on the internet is about fiction?

The facts of lore: What happens when the most reputable information on the internet is about fiction?

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 let Perplexity crawl my content? Pitting legacy media intellectual property standards against AI discoverability

Should I let Perplexity crawl my content? Pitting legacy media intellectual property standards against AI discoverability

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.

What is content distribution? Navigating the necessary evils of algorithms

What is content distribution? Navigating the necessary evils of algorithms

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.

Is all generative AI art terrible? A consideration of how changes in software transform artistic production

Is all generative AI art terrible? A consideration of how changes in software transform artistic production

Artists face increasingly thorny questions about if, how, and where AI-powered work belongs in their oeuvre. Perhaps the workaround is to use AI to express human eccentricity — not mimic it.

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