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Exactly They are also going for the entirely wrong market. Everyone is arguing about replacing programming jobs, "AI can't replace my job". But it is really

Exactly They are also going for the entirely wrong market. Everyone is arguing about replacing programming jobs, "AI can't replace my job". But it is really just fractional. Lets say you have 5 marketing drones writing boring marketing material. AI allows them to do more, you still need humans to use the tools, and to edit, but now you only need 3. AI can't do the 'entire job' but it did enough to eliminate two positions. This is what is already happening. Do you think this stopped with the ESPN case? Companies didn't stop because they got caught, they just got better at it.

exe34 2y ago
I used to subscribe to this belief long before LLMs started confabulating, but I'm now starting to feel forced to concede that what will happen is that management will fire two marketing drones, the remaining three will use AI to write stuff, but then spend 5 drones worth of effort fixing the gish gallop. the overall quality will go down, the 3 drones will burn out, and the AI will be used to replace them entirely. the overall slop will be entirely useless.
- FrustratedMonky 2y ago
  I've waffled back on forth on that same line of reasoning. Maybe it just needs to reach point where the AI "confabulating" is equal or less than human "confabulating". Plenty of humans BS, make errors. So AI just needs to reach parity to allow replacing the humans.
  - AnimalMuppet 2y ago
    Some humans are capable of saying "I don't know" or, better, "I'll find out".
    - exe34 2y ago
      I think that information needs to be included in the input stream. instead of asking a model "what did I have for breakfast", you give it an api it can query to look at your food journal and if something is not available, it's marked explicitly as unknown. if you make the human stressed enough, they will in fact tell you an answer whether or not they know the answer.
- steveBK123 2y ago
  Yes the causality is reversed in a lot of peoples minds but this is more in-line with some other "innovations" were enforced. Big Boss reads Gartner. Gartners says do X. Big Boss mandates X, and gets the cost savings they want by firing or hiring freeze. The quality/quantity of the output was hard to measure compared to the concrete reduction on the spend side. 20 years ago it was offshoring. I recall a job where managers were all essentially given the offer at budget season - you can have 5 hires in Bangalore or 0 hires in US. Not a pot of money and managers deciding X vs Y, it was simply an ultimatum X or 0. Certainly it worked, however it was first forced in many areas where it didn't work, top-down. AI efficiencies will happen similarly.

exe34 2y ago

I used to subscribe to this belief long before LLMs started confabulating, but I'm now starting to feel forced to concede that what will happen is that management will fire two marketing drones, the remaining three will use AI to write stuff, but then spend 5 drones worth of effort fixing the gish gallop. the overall quality will go down, the 3 drones will burn out, and the AI will be used to replace them entirely. the overall slop will be entirely useless.

FrustratedMonky 2y ago
I've waffled back on forth on that same line of reasoning. Maybe it just needs to reach point where the AI "confabulating" is equal or less than human "confabulating". Plenty of humans BS, make errors. So AI just needs to reach parity to allow replacing the humans.
- AnimalMuppet 2y ago
  Some humans are capable of saying "I don't know" or, better, "I'll find out".
  - exe34 2y ago
    I think that information needs to be included in the input stream. instead of asking a model "what did I have for breakfast", you give it an api it can query to look at your food journal and if something is not available, it's marked explicitly as unknown. if you make the human stressed enough, they will in fact tell you an answer whether or not they know the answer.
steveBK123 2y ago
Yes the causality is reversed in a lot of peoples minds but this is more in-line with some other "innovations" were enforced. Big Boss reads Gartner. Gartners says do X. Big Boss mandates X, and gets the cost savings they want by firing or hiring freeze. The quality/quantity of the output was hard to measure compared to the concrete reduction on the spend side. 20 years ago it was offshoring. I recall a job where managers were all essentially given the offer at budget season - you can have 5 hires in Bangalore or 0 hires in US. Not a pot of money and managers deciding X vs Y, it was simply an ultimatum X or 0. Certainly it worked, however it was first forced in many areas where it didn't work, top-down. AI efficiencies will happen similarly.