Anyone know if JSON-LD is being used more in very recent years for AI? Saw a couple of comments elsewhere that many large companies are using it now. If so, how is is (and any knowledge graph / linked data) used in these situations?
Haven't come across this in the wild. My impression is that most of the semantic web people that were obsessing about ontologies twenty years ago have moved on.
As for AI, we now have deep learning approaches that don't require an investment in a lot of machine readable, disambiguated data but is as good or better than we are of making sense of unstructured data. That probably explains the low interest in semantic web type stuff at this point.
The ones that have moved on are being replaced by newcomers though - as evidenced by my multiplicity of my comments on this post, I'm one of them ;)
I would agree with your appraisal of AI - at the moment, there is a much greater return-on-investment for processing vast quantities of unstructured data than there is for meticulously curating knowledge graphs. However, I think that, in time, the balance will shift to vindicate the semantic web as people desire more trustworthiness from automated systems.
Why? What's changed to switch the balance from machine learned back in favor of painstakingly manually curated? Sounds a bit like wishful thinking to me. I don't think that cat will jump back into the bag and zip the bag up behind itself. Machines are only going to continue to outpace humans when it comes to pattern recognition, classifying things, or making sense of unstructured data. I don't see that turning around.
Maybe there will be a market for "artisanal ontologies". But I wouldn't get my hopes up for that one.
I was pondering the other day if someone could convince one of the proprietary LLMs to spit out something like json-ld of its internal knowledge base to train other AIs.
