New research proves that single-vector embedding models (like those powering modern semantic search) have a hard "capacity limit." They physically run out of dimensions to encode complex relevance relationships.
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#TechSEO #SearchEngineering

#buildinpublic #day13 - This is going to be RAD!

Monitor breaking news, and triggers AI-led interviews with your SMEs instantly.

#InterviewDroid

#BuildInPublic ...Day 2: Improved design & layout of the outputs.
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#ContentMarketing #ContentInterviews
#LegalMarketing
InterviewDroid lets your experts talk to our adaptive AI on their own time, turning a quick 15-minute chat into weeks worth of marketing content.

Tomorrow's Premium: Based on analysis of years of reporting, OpenAI has burned $23 billion since 2023, ending 1H 2025 with $9.6bn cash. OpenAI appears to have $9bn+ more in burn than has previously been reported.

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#SEO - I think we missed something big here re:Vector Embeddings.

Check out DeepMind's research around limitations of vector embeddings and ex-Google’s Deedy's quote about them.

I'll share more next week once I get time to really flush out this article over the weekend.

#VectorEmbeddings

If you want authoritative content, you need SMEs to be involved with your content process. Here's one way to get them to want to be part of it.

PS - Check out interviewdroid.com, a similar product to what Wil is talking about in his blog post below.

Keyword Difficulty Scores do not work & I brought some data to prove it... You have to check this out!

Link: www.youtube.com/watch?v=M1MN...

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Hello World