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50 sats \ 3 replies \ @freetx 19h \ parent \ on: Do you think AI will replace more jobs or create more new ones? AI
At a 32,000 ft level, what really is the value prop of LLMs? Essentially intellectual augmentation. It adds vast improvements to contextual and semantic recall...
Google existed for awhile, but it really only offered humans form recall, that is facts, dates, spellings...with a pretty limited enhancement to semantic recall (and no real contextual recall).
LLMs offer huge advances in semantic recall which is then paired with contextual coherence to offer a real augmentation of human ability. The value prop is not just to have facts+dates but to order those by semantic relations within the context of your conversation. It is the trifecta for intellectual augmentation.
But at that 32,000ft level, how different is it from any new tech? (All new tech is essentially a human multiplier).
If you went back to ancient Rome and explained that eventually there would be machines that could do the work of 1000s of men. Bulldozers, Cranes, Concrete trucks, etc...they would've assumed the future world would hardly need any workers. That would be a logical assumption from their employment perspective, but also totally wrong.
I'm just sitting back for the ride and seeing what plays out, but LLM-driven automation targets knowledge work, not physical labor (yet at least). Unlike past industrial shifts, this wave threatens entire job categories at once — journalism, translation, legal research, customer support, basic design jobs etc. It's a pretty big list. There will still be jobs in these fields, just way fewer.
Plus physical tools didn’t centralize power, but LLMs might - whoever controls the models controls knowledge access.
Also, these models are early days, they are going to get better and at some point be able to do all kinds of other things and admin tasks i think
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Fact, this era feels bigger than past ones. AI isn’t just changing jobs, it’s centralizing power too, which might be the bigger risk in the long run.
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It doesn't have to centralize power. We can use our own specific and fine-tuned LLMs, instead of using the commercial offerings.
Thanks to a very vibrant open source community, this is possible today. Of course there is more friction in setting up your own stuff, but it's not that hard. In the end, sovereign compute can enable you to do whatever you want, free of control.
I just stumbled upon a simple guide for running GPT-OSS (20b) #1140405 so I posted this for everyone to enjoy.
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