I've seen a few of this type of thing pop up in search results ("DeepWiki" by Cognition.) I'm not a fan. It is just LLM contentslop, basically. Actual wikis written by humans are made of actual insight from developers and consumers. "We intend you use it in X way", "If you encounter Y issue, do Z." etc. Look at arch wiki. Peak wiki-style documentation, LLMs could never recreate. Well, maybe with a future iteration of the technology they can be useful. But for now, you do not gain much by essentially restating code, API interfaces, and tests in prose. They take up space from legitimate documentation and developer instruction in search results.

I've had 23andme since ~2012. Haven't received a single email from/about 23andmedatasettlement.com

It depends on how you test it. I recently found that the way devs test it differs radically from how users actually use it. When we first built our RAG, it showed promising results (around 90% recall on large knowledge bases). However, when the first actual users tried it, it could barely answer anything (closer to 30%). It turned out we relied on exact keywords too much when testing it: we knew the test knowledge base, so we formulated our questions in a way that helped the RAG find what we expected it to find. Real users don't know the exact terminology used in the articles. We had to rethink the whole thing. Lexical search is certainly not enough. Sure, you can run an agent on top of it, but that blows up latency - users aren't happy when they have to wait more than a couple of seconds.

This is an advertisement. And it would be a better advertisement if it started by actually explaining what the products are, instead of diving immediately into a woe is me pitch and then abruptly pivoting to black friday deals.

I think they are referring to the fact that Google has shimmied AI into every one of their products, thus demand surge is the byproduct of decisions made internally. They are themselves electing to send billions of calls daily to their models.

As opposed to external demand, where vastly more compute is needed just to keep up with users torching through Gemini tokens.

Here is the relevant part of the article:

"It’s unclear how much of this “demand” Google mentioned represents organic user interest in AI capabilities versus the company integrating AI features into existing services like Search, Gmail, and Workspace."