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Earlier quoted context omitted.
Attention models learn what to pay attention to. It's been found that data that begin with "Wikipedia:" are automatically weighted higher by language models during training, completely unsupervised.
But this is the same problem - Wikipedia is a secondary source and should always get overruled by the primary source.
Earlier quoted context omitted.
It is happening in insurance right now and it is an unmitigated disaster that nobody wants to address. There is real data used for insurance premiums and claims payouts but it's being swapped out for AI slop, and the sales folks are getting bonuses for selling hot garbage and the executives are getting bonuses for buying hot garbage.
Huh, if sales uses AI/LLMs and succeeds with it, as it seemed to me youve implied with their bonuses ... Isn't that actually positive for the company? Or do you mean they succeed by promising lies via AI?
I'd worry about things which:
1. "Succeed" in the short-term, but sets the company up for long-term failure.
2. Outperforms the competition with a pattern of activity which is actually illegal.
Looking towards the future, we will need to move away from "tokens are characters to print", We're kind of starting to consider this with "tool calls" but I believe an architectural shift will become necessary. We do have some kind of understanding of what kind of concept we want to emit next, e.g. ``` [The height:property name] of [Mount Bartle Frere:proper noun, describing an object to get a property out of], [in m…
Uh oh, that sounds suspiciously like querying structured data. You can't hype SQL or worse, SPARQL, to investors!
https://en.wikipedia.org/wiki/Resource_Description_Framework