Thanks for all this, most of which flew right over my head!!
I wonder, can you recommend a resource where one could get "quickly" up to speed on how this stuff conceptually works, something one could ingest in a weekend or so to get a decent handle on it (but not necessarily be capable of doing anything)?
Like, I think I have a decent understanding of the probabilistic "next word" aspect of LLM text generation, but I'm assuming there's an initial "vector query" that happens prior to this part of it?
Also, could you offer any advice on the notion of how AI/ML is able to extract various meanings from text? For example, let's say I wanted to be able to scrape this thread and then for each comment extract various ideas/topics mentioned in each comment (ideally with influence from a custom ontology), detect emotions, claims of fact, etc etc etc - is that sort of thing possible?
I wonder, can you recommend a resource where one could get "quickly" up to speed on how this stuff conceptually works, something one could ingest in a weekend or so to get a decent handle on it (but not necessarily be capable of doing anything)?
Like, I think I have a decent understanding of the probabilistic "next word" aspect of LLM text generation, but I'm assuming there's an initial "vector query" that happens prior to this part of it?
Also, could you offer any advice on the notion of how AI/ML is able to extract various meanings from text? For example, let's say I wanted to be able to scrape this thread and then for each comment extract various ideas/topics mentioned in each comment (ideally with influence from a custom ontology), detect emotions, claims of fact, etc etc etc - is that sort of thing possible?