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Psychomadeye t1_ja6yjuy wrote

Reply to comment by just-a-dreamer- in Their future is AI, not ours. by [deleted]

As a person who works with these things, there's a lot of limitations to these technologies that are ignored by virtually everyone. These things are correlation engines. They're going to take jobs the same way the steam engine took jobs.

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just-a-dreamer- t1_ja72uj5 wrote

Looks like you have a narrow focus on a narrow field in tech.

Narrow AI is good enough to wipe out the white collar labor market within decades.

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Psychomadeye t1_ja74jrp wrote

Not exactly. There are many limits to this. For instance, this would require Moore's law to continue to hold true. It will not (failing somewhere in the next couple years). These models can't really work outside of their training space (space as a physical concept will need to change to fix this.) Information can only travel so fast and that's not going to be fixed either (because that's technically time travel). Some might say quantum computers can help, but as someone who is in this field I couldn't imagine how chemistry simulations would help my model run better. Finally, Models don't really understand things like true or false, or cause and effect and there's no clear path to fix that. There are more issues but you've probably got the idea.

These things are at best tools that can help people go faster. Those that are trying to replace workers may have some success in certain things like call centers. But in reality it's not going to make sense to replace people. Especially when you remember how really massive these models are. You can buy five data centers to run one instance or hire five employees to handle calls. And remember, you're going to need to provide a training space for each job you plan to replace. You might not even have the data for that.

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just-a-dreamer- t1_ja75iqv wrote

And?

The vast majority of humans also can't work outside their training data. The number of people that truly create something new in their field of choice is limited. The majority does not work in a managerial capacity.

It might feel different in tech for job description change like every 2 years. But even there most workers don't create something new and unique.

Narrow AI does not have to wipe out a profession completly, it is good enough to replace like 70% of the workforce to cause serious trouble.

Unpaid student loans, mortgages, car loans, child support, taxes, social security, insurances, health insurance...

Firing just 10% of white collar professionals in a short perioid of time would crash many layers of the financial pyramid.

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Psychomadeye t1_ja796kk wrote

You'd be surprised how small the training space is and how far outside a human reaches. We're talking a litter box to a football stadium in difference. And humans know the difference between true and false vectors, but an AI won't. If there's a chance to policy, you'll need years to retrain that model and will need to somehow find a dataset to use for that. You can't just ask it to use new cover pages on the TPS reports. You need to show it a million TPS reports with those cover pages and hope it generates them properly. Even when you don't create something new, the ability of these models to give you exactly what you want and actually have it work is extremely limited. And again, in order to address these limits, we need infinite space in a finite space, a time machine, or computers that fit inside an atom.

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just-a-dreamer- t1_ja79yrd wrote

Humans are screwed then, for their brains are fairly limited. Yet we manage somehow

I believe AI will optimize it's data over time and learn on the go. Besides, the workflow is designed for human hands and brains, not for AI.

It might be more reasonable to have no TPS reports at all as an example and come up with something that is better suited to AI capabilities.

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Psychomadeye t1_ja851np wrote

>Besides, the workflow is designed for human hands and brains, not for AI.

If we want non human workflow we will need a massive amount of data on that for it to learn the correlation. But I'm at a loss of where anyone would even get data on a non human workflow. These specifically aren't thinking machines. They just know how to generate a point on a graph to look like the rest of the points. They're a really really good dart player. This is why I call them correlation engines. They can't replace workers on their own because the rules of the game change slightly and it'll be months or years of training before it's ready again.

>Humans are screwed then, for their brains are fairly limited.

Our neurons don't suffer the same issues because the sheer size of a human brain expressed as a neural network is larger than we can currently hope to compute yet somehow, training time is seconds and not years, and we have transfer learning at a scale that artificial networks don't have.

>It might be more reasonable to have no TPS reports at all as an example and come up with something that is better suited to AI capabilities.

We need data to train the AI on this new system. This means it will need millions of examples. Then it can spend a few years learning that data. We haven't even gotten into costs yet. Those instances will be costly to run. Newer models might be faster but they are not likely to invent time machines or sub atomic computers without examples of those things.

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