JSON and CSV [and a massive amount of custom-made spaghetti code] gave the impression that semantics was totally unnecessary in dataflows. Now that we live in a world where dataflows build themselves, we will need a description language that is much more robust.
Probably generated from chatbot interactions, but formally defining how the consumer can discover content and mix them.
I work with Palantir Foundry stack, and I awfully think that this is the best implementation of semantic web principles I could ever imagine.
And the current trend is really to connect the AI layer of Foundry with the ontology layer.
Note: after rereading your comment, I must admit that Foundry enforces data co-locality and model co-locality (==a unified centrally managed ontology). Which are NOT what the semantic web wanted.
The concept will re-emerge somehow. Webpages are 99.99% of the time the formatting of a data structure for humans. LLM can barely infer that data structure from the webpage and connect it with other data structure of other pages. [truth is that the LLM algorithm does not do that AT ALL internally, but from our user experience it really looks like it does].
But when webpages die and data is accessed only by machine2machine APIs, we will no longer have this formatting for humans. Then we will need API-literate LLMs. Which means LLMs that can connect the dots between shitloads of unconnected JSONs. And if we don’t hint it for which connections are existing between that chaos of APIs, it will not be able to apply its magic.
In short: we need to be able to bring JSON to vector space. And it is absolutely not meant for that, by default.
warpd, properly configured, was working perfectly for me.
until i realized i 99% needed it for web surfing. so i switched to kinkHints in firefox, which is covering my link clicking need.