Nicolas Garfinkel (Interviewdroid.com)

Friends, who should I follow on BlueSky for AI, SEO, And Data Science trends & topics? My feed is looking pretty bare right now...

#AI #SEO #DataScience

DeepMind Calls Out Embedding Limits: Why Single-Vector Retrieval Falls Short — An Attention… Finally a major lab openly admitting the limits of embedding models and representing everything as single vector.

Are you really seeing SEOs out there that aren't considering semantic relevance when optimizing site content? That would be pretty wild at this point and time.

Related - have you seen the DeepMind study on the limits of embeddings? Super interesting read that I think you'll enjoy!

[3/3]
"Semantic search" has mathematical blind spots. If you abandon exact keywords for pure vector search, you lose visibility on logic-based queries.

arxiv.org/pdf/2508.21038

[2/n] The results were wild:
❌ SOTA Embedding Models (Google, OpenAI) failed hard, scoring <20% recall.
✅ Old-school BM25 (Keyword matching) scored nearly 100%.

Embeddings are great at concepts, but bad at precise boolean logic.

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.
[1/n]

#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.

Welp... Now I know what I'm doing for the next 37 minutes. Thanks Lily for sharing.

OpenAI Burned An Estimated $19 Billion In Cash Between 2023 and 1H 2025 - Where Did It Go? OpenAI had $9.6 billion in cash at the end of June. So, Microsoft’s funding in 2023 was $2 billion in cash (and $8 billion in credits, but I’m not counting those), add in the $6.6 billion of cash from 2024 (i’m not including the line of credit, as that would be a “cash equivalent), $10 billion from SoftBank and other investors in June 2025, and we assume $2 billion in revenue in 2023, $3.7 billion in revenue in 2024, and $4.3 billion in revenue in the first half of 2025 (for a total of $28.6 billion in cash), this means that OpenAI burned $19 billion in cash from the beginning of 2023 through the end of June 2025. Yet the reported losses are much, much smaller. For the sake of argument, I’m also going to leave OpenAI’s $4 billion line of credit out of the calculation. In 2024, OpenAI allegedly burned $5 billion. Through 1H 2025, it had a “net loss” of $13.5 billion but an “operating loss” of $6.7 billion, and the painfully-worded accounting leaked to The Information is done in such a way as to make it unclear how much of that is cash, with the hopes that you believe it’s not cash burn. $19 billion in burned cash doesn’t make sense based on any reported numbers. Even if we assume OpenAI burned $2 billion in cash in 2023, $5 billion in cash in 2024 and $6.7 billion in cash in 1H 2025, that’s $14.9 billion in missing burn to get us to the $28.6 billion total. I guess there could be prepayments as part of its deals with Broadcom or CoreWeave, but even then, The Information had another tidbit: OpenAI also recorded around $670 million of equity it gave to unnamed entities for providing the company with servers in the first half of 2025, compared to $1 billion in such equity compensation last year. While it’s not clear which cloud provider or providers received the equity, the decision could help OpenAI minimize its cash burn as it projected it would spend $16 billion to ren…

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.

Here's $10 off annual.

edzitronswheresyouredatghostio.outpost.pub/public/promo...

#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

@wilreynolds.bsky.social I saw you liked my message 👀

Would be awesome to chat when you feel the timing’s right. Here's my calendar link if and when you feel up to it! meetnicolas.com.

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.

Hey Wil. Big fan of yours. I built something similar. Maybe an opportunity to collab and build a single, stronger solution instead of chasing the same goal from two sides? I have few killer features in dev that could make it worth a chat.

Forbes Marketplace: The Parasite SEO Company Trying to Devour Its Host Are you sick of Forbes appearing in search results? For topics that Forbes doesn’t have any expertise in? Here’s the organic rankings for “best pet insurance”: Forbes ranks #2. Not sure a business web...

The Forbes Advisors story is maybe the most unethical case of Search Engine Manipulation and they finally got burned after who knows how much money they made from it
larslofgren.com/forbes-marke...

Long read but a good one.
written by: @larslofgren.bsky.social

#SEO #SEOTools

🧵 (4 of ?)
3: The breakdown is for a single industry and results may vary for other industries (though I doubt it).

4: Similarity scores on page title aren't the *BEST* way to determine content relevance. But it's not a bad way either. More factors at play around content quality, etc...

🧵 (3 of ?)
Limitation 2: The analysis was done on a mix of non-branded head and tail terms more geared towards information queries.

* PS - I hate this character count limit!

🧵 (2 of ?)

Limitation 1: based on one of the "big 3" SEO tools provider so it could very well the other tools KW Difficulty Scores are more accurate. I will not name the company because the purpose of this is not to "throw any shade". The assumption is they all are equally as problematic.

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...

🧵 (1 of ?)

Really enjoyed your talk! Great idea recording it.

Hi!

Hello World