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> I found a lot of factually incorrect statements in that article. Such as: "If a human can’t perform the task, then neither can an AI." Don't we create AI syst

> I found a lot of factually incorrect statements in that article. Such as: "If a human can’t perform the task, then neither can an AI." Don't we create AI systems to solve problems human cannot all the time? Not really, I think we create AI systems to solve problems humans take way too long to solve. But I can't think of anything AI does, that a human couldn't, given sufficient time and resources. Regarding the rest, I fully agree with you. Things like this are nothing but scary to me

ACow_Adonis 9y ago
Ah, but certain problems are not just limited by the amount of time and resources that may be apportioned to them, but are bounded by needing to be completed with specific time and resource constraints. And that's a spot where computers and programming show that they are capable of implementing systems that biological humans literally cannot under any circumstance. Our hardware/meat-ware is not capable of it. If we maintain a willing suspension of disbelief, for sure a human being may be able to add up a million numbers correctly if they had infinite time and infinite resources (although in reality they would not be provisioned with those resources or time), but what no individual human can do is be presented with those numbers and add them up in under a second. Or to be more realistic and to draw away from our simple notion of individual problems and individual resource constraints, there are fields of knowledge resulting from coordinated-compound-tasks that require locally doing 20 disparate but coordinated operations in parallel in under a second. The application of our modern day technology literally involves the creation and implementation of systems that no biological human or human-centric system can accomplish. edit: of course, that might be a way of saying the problems that you said human beings take way to long to solve, but i think there's an important need to distinguish between those problems that we can't do because of algorithmic complexity, and those problems that we cannot do because we are not made/manufactured of the same stuff and able to be programmable with the same ease. Without blurring the definition of what it means to be human/computer, there are fundamentally problems that computer/AI can solve that we cannot.
TheSpiceIsLife 9y ago
Given sufficient time and resources a human will likely recruit other humans to design and built AI to solve those problems.
aesthetics1 9y ago
I feel like the statement is fundamentally contradictory, seeing as how humans have invented and trained the AI systems. By definition, that is something that humans are doing. On the other hand, it may be more insightful to say that if humans cannot perform the task (time is not a factor), than neither can AI. For example, assessing non-tangibles, or something abstract like identifying sarcasm in text without context.
- TeMPOraL 9y ago
  I think this is dancing around a tautology - if humans can't do something "in theory", it means they can't describe it, which means they can't program it in AI. Obviously.
tinymollusk 9y ago
ML can handle things at scale (not just speed, number of data points) that humans can't. Imagine a classification problem with 1000 dimensions -- humans can't keep in working memory that many entries. Granted, many of these are trivially solvable if you can scale them (e.g. human with a computer but no AI/ML), but scale is an important component. It's kind of like how metadata isn't that big of a deal until you have enough of it.

ACow_Adonis 9y ago

Ah, but certain problems are not just limited by the amount of time and resources that may be apportioned to them, but are bounded by needing to be completed with specific time and resource constraints. And that's a spot where computers and programming show that they are capable of implementing systems that biological humans literally cannot under any circumstance. Our hardware/meat-ware is not capable of it. If we maintain a willing suspension of disbelief, for sure a human being may be able to add up a million numbers correctly if they had infinite time and infinite resources (although in reality they would not be provisioned with those resources or time), but what no individual human can do is be presented with those numbers and add them up in under a second. Or to be more realistic and to draw away from our simple notion of individual problems and individual resource constraints, there are fields of knowledge resulting from coordinated-compound-tasks that require locally doing 20 disparate but coordinated operations in parallel in under a second. The application of our modern day technology literally involves the creation and implementation of systems that no biological human or human-centric system can accomplish. edit: of course, that might be a way of saying the problems that you said human beings take way to long to solve, but i think there's an important need to distinguish between those problems that we can't do because of algorithmic complexity, and those problems that we cannot do because we are not made/manufactured of the same stuff and able to be programmable with the same ease. Without blurring the definition of what it means to be human/computer, there are fundamentally problems that computer/AI can solve that we cannot.

TheSpiceIsLife 9y ago

Given sufficient time and resources a human will likely recruit other humans to design and built AI to solve those problems.

aesthetics1 9y ago

I feel like the statement is fundamentally contradictory, seeing as how humans have invented and trained the AI systems. By definition, that is something that humans are doing. On the other hand, it may be more insightful to say that if humans cannot perform the task (time is not a factor), than neither can AI. For example, assessing non-tangibles, or something abstract like identifying sarcasm in text without context.

TeMPOraL 9y ago
I think this is dancing around a tautology - if humans can't do something "in theory", it means they can't describe it, which means they can't program it in AI. Obviously.

tinymollusk 9y ago

ML can handle things at scale (not just speed, number of data points) that humans can't. Imagine a classification problem with 1000 dimensions -- humans can't keep in working memory that many entries. Granted, many of these are trivially solvable if you can scale them (e.g. human with a computer but no AI/ML), but scale is an important component. It's kind of like how metadata isn't that big of a deal until you have enough of it.