this post was submitted on 22 Dec 2024
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At a beach restaurant the other night I kept hearing a loud American voice cut across all conversation, going on and on about “AI” and how it would get into all human “workflows” (new buzzword?). His confidence and loudness was only matched by his obvious lack of understanding of how LLMs actually work.
Some people can only hear "AI means I can pay people less/get rid of them entirely" and stop listening.
AI means C level jobs should be on the block as well. The board can make decisions based on their output.
I've noticed that the people most vocal about wanting to use AI get very coy when you ask them what it should actually do.
Because as a social phenomenon it promises to decide for them what it should actually do.
I really like the idea of an LLM being narrowly configured to filter, summarize data which comes in at a irregular/organic form.
You would have to do it multiples in parallel with different models and slightly different configurations to reduce hallucinations (Similar to sensor redundancies in Industrial Safety Levels) but still, ... that alone is a game changer in "parsing the real world" .... that energy amount needed to do this "right >= 3x" is cut short by removing the safety and redundancy because the hallucinations only become apparent down the line somewhere and only sometimes.
They poison their own well because they jump directly to the enshittyfication stage.
So people talking about embedding it into workflow... hi... here I am! =D
A buddy of mine has been doing this for months. As a manager, his first use case was summarizing the statuses of his team into a team status. Arguably hallucinations aren’t critical