AI [probably referring to a LLM] is not trained by professionals or a single end user, because it requires such huge amounts of input training data...
You are correct and you are incorrect.
From scratch finding data for pattern matching is tough and requires high performance engines, trade-offs, and money. But we stand on the backs of giants.
There are trained ethical LLMs, certified to be so and deep pockets to back the assertion and the necessary curation. They are not necessarily free. From those seeds AIs can be built to do the things of which I speak.
If IBM can do it (and they do; having gone to the training and hard sell, I know), Apple Intelligence could be built and use Apple engines as infrastructure. Big Blue's giant Z mainframes, which are blades in pretty artwork boxed server racks, are performant due to their custom chips, virtual system management, tuned I/O structure, and multitasking software. Apple chips are performant, custom, and cheaper for the end user. Apple Intelligence is likely Apple's WatsonX App-Killer that'll make the difference, and most certainly runs on Apple hardware increasingly running on renewables.
My point isn't so much building LLMs from scratch, but applications built on a platform and then trained from private user data and via user curation. If I implied otherwise, I wasn't clear. Sorry.
I assume Apple's LLMs are ethical. I also assume that Apple is exposing AI APIs for use by developers.
#LLM #Ibmz #AI #genAI #ethics #watsonx #ibm #Apple #intelligence #Writer #Author #Fiction #WritingCommunity #WritersOfMastodon #Programmer #Program #Application #Code #Coding
Cc: @vextaur
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