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disagree. AI has not even begun to penetrate its potential in corporate America. you could enhance so much middleware stuff with a good unstructured data organi

disagree. AI has not even begun to penetrate its potential in corporate America. you could enhance so much middleware stuff with a good unstructured data organization AI and slap voice recog on top of it, you have massively multiplied the effectiveness of a whole bunch of mid level people from operations staff to sales reps, who are very good at their domain but continually stymied by computer syntax and lack of programmers to make the computer do stuff.

renegade-otter 2y ago
Most businesses do not even have their data game on properly. AI is an iteration of Big Data, and BOTH need proper source material, or the value will be zero AT BEST. https://hbr.org/2013/12/you-may-not-need-big-data-after-all https://hbr.org/2013/12/you-may-not-need-big-data-after-all
megadal 2y ago
The use case you described can be achieved with a subset of NLP, and has basically already been possible for years. Named-Entity Recognition (NER) and Text Classification will allow you to figure out what kind of text you're looking at and extract structured data. LLMs are not good at this because they're not specialized for it, but you can build a specialized NER model to extract custom entities from unstructured data today. That said, I don't really think this is some yet untapped potential of AI so much as an area of ML that just hasn't been applied enough. ETA: also, in general I think AI is going in the direction of basically just having an LLM route tasks to more specialized ML models (for corporate tasks at least). That's what Google's Vertex AI agents sort of do (and I am guessing the GPT 4 agents as well).
- KoolKat23 2y ago
  But this is the thing, that requires expertise and infrastructure. "AGI" LLM's can handle all the nuance, quite simply, they don't need specialist infrastructure or specialist programming, way cheaper, upfront cost. Way easier to scale. Individual employees can ask it for specific things that make their lives easier and it'll give it to them/or do it. No need to ask your manager, motivate for funding and hire an engineer/purchase new software/equipment.
  - megadal 2y ago
    If I'm not mistaken LLMs contain NER and text classification pipelines so you can leverage the exact same infrastructure. I can't see how AGI from that perspective _isnt_ just an LLM routing tasks to more specialized NLP models to be honest. Unless you're proposing that a bigger LLM (training data, neural network, etc..) will develop the emergent capability to accomplish this without the need for specialized agents. In which case, I can't see how that would perform more efficiently than an LLM routing requests appropriately amongst agents, as it necessarily requires processing much more data. But even if somehow it did perform more efficiently while needing much more data, I don't think the no-agent AGI approach will cover all use cases appropriately. It might be an easier drop in solution, but if I need it to behave a specific way in a specific context, I don't see how an AGI is going to consistently do that more accurately than fine tuning a model for the specific use case and having an LLM routing to it.
    - KoolKat23 2y ago
      I agree that's probably how they will work best.my point was that AGI allows everyone to leverage those tools without the steep learning curve or having to custom build each component for each specific use case themselves.
- deleted 2y ago
  [deleted]
LightFog 2y ago
You are assuming all stakeholders want the mid level people gone. We already have the technology to automate most of this stuff - bullshit jobs exist for a different reason.
- grob-gambit 2y ago
  I partially agree, there are huge delusions of Homo economicus. There is also this other process at work that is shaped by quarterly earnings reports in public markets. Maybe if we started over with a mirror economy that we rebuild from the ground up, most of these things could be automated. I think there are many inefficiencies in the system that Homo economicus wouldn't be able to deal with even if Homo economicus actually existed.
- doubloon 2y ago
  that is the exact opposite of what i said. i said it multiplies the effectiveness of people in the middle of a company. so they dont have to be stuck with middleware interfaces from dead software that hasnt been maintained in 10 years.
pesfandiar 2y ago
AI winter is more about the outlook of the research. Nobody can deny there are huge untapped opportunities in the applications.

renegade-otter 2y ago

Most businesses do not even have their data game on properly. AI is an iteration of Big Data, and BOTH need proper source material, or the value will be zero AT BEST. https://hbr.org/2013/12/you-may-not-need-big-data-after-all https://hbr.org/2013/12/you-may-not-need-big-data-after-all

megadal 2y ago

The use case you described can be achieved with a subset of NLP, and has basically already been possible for years. Named-Entity Recognition (NER) and Text Classification will allow you to figure out what kind of text you're looking at and extract structured data. LLMs are not good at this because they're not specialized for it, but you can build a specialized NER model to extract custom entities from unstructured data today. That said, I don't really think this is some yet untapped potential of AI so much as an area of ML that just hasn't been applied enough. ETA: also, in general I think AI is going in the direction of basically just having an LLM route tasks to more specialized ML models (for corporate tasks at least). That's what Google's Vertex AI agents sort of do (and I am guessing the GPT 4 agents as well).

KoolKat23 2y ago
But this is the thing, that requires expertise and infrastructure. "AGI" LLM's can handle all the nuance, quite simply, they don't need specialist infrastructure or specialist programming, way cheaper, upfront cost. Way easier to scale. Individual employees can ask it for specific things that make their lives easier and it'll give it to them/or do it. No need to ask your manager, motivate for funding and hire an engineer/purchase new software/equipment.
- megadal 2y ago
  If I'm not mistaken LLMs contain NER and text classification pipelines so you can leverage the exact same infrastructure. I can't see how AGI from that perspective _isnt_ just an LLM routing tasks to more specialized NLP models to be honest. Unless you're proposing that a bigger LLM (training data, neural network, etc..) will develop the emergent capability to accomplish this without the need for specialized agents. In which case, I can't see how that would perform more efficiently than an LLM routing requests appropriately amongst agents, as it necessarily requires processing much more data. But even if somehow it did perform more efficiently while needing much more data, I don't think the no-agent AGI approach will cover all use cases appropriately. It might be an easier drop in solution, but if I need it to behave a specific way in a specific context, I don't see how an AGI is going to consistently do that more accurately than fine tuning a model for the specific use case and having an LLM routing to it.
  - KoolKat23 2y ago
    I agree that's probably how they will work best.my point was that AGI allows everyone to leverage those tools without the steep learning curve or having to custom build each component for each specific use case themselves.
deleted 2y ago
[deleted]

LightFog 2y ago

You are assuming all stakeholders want the mid level people gone. We already have the technology to automate most of this stuff - bullshit jobs exist for a different reason.

grob-gambit 2y ago
I partially agree, there are huge delusions of Homo economicus. There is also this other process at work that is shaped by quarterly earnings reports in public markets. Maybe if we started over with a mirror economy that we rebuild from the ground up, most of these things could be automated. I think there are many inefficiencies in the system that Homo economicus wouldn't be able to deal with even if Homo economicus actually existed.
doubloon 2y ago
that is the exact opposite of what i said. i said it multiplies the effectiveness of people in the middle of a company. so they dont have to be stuck with middleware interfaces from dead software that hasnt been maintained in 10 years.

pesfandiar 2y ago

AI winter is more about the outlook of the research. Nobody can deny there are huge untapped opportunities in the applications.