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Maybe I just lack imagination, but I don't really know how jobs are supposed to solidify around the role of giving prompts to agents and then looking at the res

Maybe I just lack imagination, but I don't really know how jobs are supposed to solidify around the role of giving prompts to agents and then looking at the results. I mean, engineers will be in the breadline because their role was simply to prompt the agents.. only to be superseded by managers or executives who no longer manage engineers but themselves prompt the agents? And, for this previously considered obsolete function which they do presumably by copy/pasting requirements from their email inbox, they will be paid by someone who doesn't know that they could just be talking to their own agents? Sorry if I misunderstand the point, just trying to understand.

RALaBarge 27d ago
Regardless of the imagination quandary, this second, RIGHT NOW is the worst these systems will ever be. They are only going to get better.
- hatefulmoron 27d ago
  For sure, and for that reason I mean to say that I wouldn't feel great as a manager/executive/etc either.
- greenowl 27d ago
  Maybe, maybe not. It's not unreasonable that these systems cap out at some point, or perhaps fizzle away entirely. The businesses that create these systems are not profitable and run at a massive historical and go-forward loss. New data centers required to operate these systems are facing increasing pushback at local levels. New construction is not guaranteed. Energy and power grid constraints exist as well. Government regulation is way behind. What happens when (if) mass layoffs due to AI occur? How does the population react? Theoretically AI can be regulated out of significant progress, or outright existence for many purposes. At the end of the day, US and other prominent governments make the calls, not corporations.
  - Calazon 27d ago
    For better or for worse, this technology isn't going away any more than search engines, smartphones, or social media have gone away.
    - flyinglizard 27d ago
      These inventions all stopped disrupting the world and just became a part of it. The question is whether LLMs are going to just take their quiet place, or profoundly change (or eliminate) humanity in a self-feeding frenzy towards singularity.
    - greenowl 26d ago
      Those technologies reached profitability relatively early, if not immediately.
      - scotty79 26d ago
        https://en.wikipedia.org/wiki/Productivity_paradox https://en.wikipedia.org/wiki/Productivity_paradox Computers never got profitable. They just made the alternative infeasible. Also, if you believe Amazon accounting, e-commerce only very recently got somewhat profitable.
  - scotty79 26d ago
    > It's not unreasonable that these systems cap out at some point, or perhaps fizzle away entirely. Yeah, like computers and mobile phones did. Things that have utility, even if not immediate or initially obvious, don't fizzle out.
    - krige 26d ago
      That's survivor bias to the extreme.
      - scotty79 26d ago
        What did fizzle away then and why do you believe AI is more similar to that thing than to computers?
- mooreds 27d ago
  I don't know if he's right, but Peter Zeihan thinks the breakdown in globalization will negatively affect the ability to continue to improve the chips that AI depends on[0]. Too many steps in the supply chain, too widespread, too vulnerable to deglobalization. 0: https://zeihan.com/the-ai-race-to-regression/ https://zeihan.com/the-ai-race-to-regression/
  - jiggawatts 27d ago
    An invasion of Taiwan would definitely slow progress but it wouldn’t stop it. We already have sufficient hardware that algorithmic (software) improvements alone should get us to GPT 7 / Greek Reference 6 even if not a single new chip is delivered to an AI data center ever again, starting today.
- goatlover 27d ago
  Those nuclear powered flying cars envisioned in the 50s were also inevitable progress of the automobile.
logicchains 27d ago
There are two things SOTA LLMs fundamentally cannot do. They cannot take financial or legal responsibility for mistakes, and they cannot learn new things without forgetting things (except to a limited degree by adding it to their context). This is clear to anyone who has used even the smartest models for tasks requiring domain knowledge outside of math and coding, for which it's not possible to generate an infinite amount of synthetic training data: they still make stupid mistakes, and have limited ability to learn from those mistakes. Humans also have a limit on the amount of domain knowledge they can acquire, albeit a much larger one. Executives hence cannot just replace all knowledge workers with LLMs, because executives have neither the domain knowledge to prompt and check the LLMs' work nor the bandwidth to keep on top of such a large volume of ongoing work.
- Calazon 27d ago
  For the moment that may be true. They are getting better and better at acquiring, retaining, and processing domain knowledge. I wonder what this will look like in a few more years. The responsibility side is a different matter of course.
- IAmGraydon 26d ago
  >There are two things SOTA LLMs fundamentally cannot do. I would say there’s a third thing. They seem to be very bad at being creative. Maybe they will eventually fix that, but if you ask it to come up with a list of business names or business ideas, for example, what you’ll get is the most generic, boring answer you could think of. They seem to be terrible at extrapolating outside of their training data. To me, this is the most significant difference.
- RALaBarge 26d ago
  In the US, Business' are treated like people with free speech rights. If it would be cheaper for them in the long run to use ai and robots instead of humans, they will figure out a way to make it so.
- scotty79 26d ago
  > they cannot learn new things without forgetting things Where did you get that idea from? Basically last few years was them constantly learning new things while improving their capability on the things they already knew.

RALaBarge 27d ago

Regardless of the imagination quandary, this second, RIGHT NOW is the worst these systems will ever be. They are only going to get better.

hatefulmoron 27d ago
For sure, and for that reason I mean to say that I wouldn't feel great as a manager/executive/etc either.
greenowl 27d ago
Maybe, maybe not. It's not unreasonable that these systems cap out at some point, or perhaps fizzle away entirely. The businesses that create these systems are not profitable and run at a massive historical and go-forward loss. New data centers required to operate these systems are facing increasing pushback at local levels. New construction is not guaranteed. Energy and power grid constraints exist as well. Government regulation is way behind. What happens when (if) mass layoffs due to AI occur? How does the population react? Theoretically AI can be regulated out of significant progress, or outright existence for many purposes. At the end of the day, US and other prominent governments make the calls, not corporations.
- Calazon 27d ago
  For better or for worse, this technology isn't going away any more than search engines, smartphones, or social media have gone away.
  - flyinglizard 27d ago
    These inventions all stopped disrupting the world and just became a part of it. The question is whether LLMs are going to just take their quiet place, or profoundly change (or eliminate) humanity in a self-feeding frenzy towards singularity.
  - greenowl 26d ago
    Those technologies reached profitability relatively early, if not immediately.
    - scotty79 26d ago
      https://en.wikipedia.org/wiki/Productivity_paradox https://en.wikipedia.org/wiki/Productivity_paradox Computers never got profitable. They just made the alternative infeasible. Also, if you believe Amazon accounting, e-commerce only very recently got somewhat profitable.
- scotty79 26d ago
  > It's not unreasonable that these systems cap out at some point, or perhaps fizzle away entirely. Yeah, like computers and mobile phones did. Things that have utility, even if not immediate or initially obvious, don't fizzle out.
  - krige 26d ago
    That's survivor bias to the extreme.
    - scotty79 26d ago
      What did fizzle away then and why do you believe AI is more similar to that thing than to computers?
mooreds 27d ago
I don't know if he's right, but Peter Zeihan thinks the breakdown in globalization will negatively affect the ability to continue to improve the chips that AI depends on[0]. Too many steps in the supply chain, too widespread, too vulnerable to deglobalization. 0: https://zeihan.com/the-ai-race-to-regression/ https://zeihan.com/the-ai-race-to-regression/
- jiggawatts 27d ago
  An invasion of Taiwan would definitely slow progress but it wouldn’t stop it. We already have sufficient hardware that algorithmic (software) improvements alone should get us to GPT 7 / Greek Reference 6 even if not a single new chip is delivered to an AI data center ever again, starting today.
goatlover 27d ago
Those nuclear powered flying cars envisioned in the 50s were also inevitable progress of the automobile.

logicchains 27d ago

There are two things SOTA LLMs fundamentally cannot do. They cannot take financial or legal responsibility for mistakes, and they cannot learn new things without forgetting things (except to a limited degree by adding it to their context). This is clear to anyone who has used even the smartest models for tasks requiring domain knowledge outside of math and coding, for which it's not possible to generate an infinite amount of synthetic training data: they still make stupid mistakes, and have limited ability to learn from those mistakes. Humans also have a limit on the amount of domain knowledge they can acquire, albeit a much larger one. Executives hence cannot just replace all knowledge workers with LLMs, because executives have neither the domain knowledge to prompt and check the LLMs' work nor the bandwidth to keep on top of such a large volume of ongoing work.

Calazon 27d ago
For the moment that may be true. They are getting better and better at acquiring, retaining, and processing domain knowledge. I wonder what this will look like in a few more years. The responsibility side is a different matter of course.
IAmGraydon 26d ago
>There are two things SOTA LLMs fundamentally cannot do. I would say there’s a third thing. They seem to be very bad at being creative. Maybe they will eventually fix that, but if you ask it to come up with a list of business names or business ideas, for example, what you’ll get is the most generic, boring answer you could think of. They seem to be terrible at extrapolating outside of their training data. To me, this is the most significant difference.
RALaBarge 26d ago
In the US, Business' are treated like people with free speech rights. If it would be cheaper for them in the long run to use ai and robots instead of humans, they will figure out a way to make it so.
scotty79 26d ago
> they cannot learn new things without forgetting things Where did you get that idea from? Basically last few years was them constantly learning new things while improving their capability on the things they already knew.