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In addition to what others are saying I want to highlight that there's decent evidence that "all" we're doing is pattern finding and pattern matching. Definitel

In addition to what others are saying I want to highlight that there's decent evidence that "all" we're doing is pattern finding and pattern matching. Definitely ML isn't at a human level yet, but I see no reason to think that we're missing some secrete sauce that's needed to make a true AI. When someday we do achieve human level intelligences in computers, it will be at least in large part with ML.

Jensson 5y ago
> In addition to what others are saying I want to highlight that there's decent evidence that "all" we're doing is pattern finding and pattern matching. Is there? Link? It is possible, I just don't think there is enough evidence to say anything about it. What evidence would show that humans are just pattern finding and matching machines?
vanusa 5y ago
We're getting into the territory of some external debates -- that is to say, into areas that have already been debate by others, so there isn't much knew I could tell you here. But basically I'm in the camp of Gary Marcus and others, who would probably respond by saying something along the lines of the following: "No, there's not particularly good evidence that all we're doing is pattern matching, and a lot of evidence to the contrary. For one thing, a lot of these ML algorithms (touted as near- or superhuman) are easily fooled, especially when you jiggle the environmental context by even just a little bit." "For another, and on a higher level, what algorithms lack -- but which sentient mammals have in spades -- is an ability to 'catch' themselves, an ability to look at the whole situation and say 'Woah, something just isn't right here'. (This is referred to as the 'elephant in the room' problem with modern AI)." "And then there's the lack of a genuine survival drive -- not to mention the fact that we don't see any inkling of evidence of some capacity for self-awareness in any currently existing system." Just as a starting point. But these are some huge differences between currently existing AI systems (however you want to define "AI here) and actual sentient cognition. Huge, huge differences... such that I don't see one can get the idea that "all" we're doing is pattern recognition. Even if it may cover roughly 90 percent of what our neural tissues do - that other 10 percent is absolutely crucial, and completely elusive to any current, working technology as such. When someday we do achieve human level intelligences in computers, it will be at least in large part with ML. No doubt it will, but still there's that ... remaining 10 percent. Which you won't get to with accelerated pattern finding any more than a faster airplane will get you to the moon.
- gmadsen 5y ago
  All I will say is that these criticisms are outdated. they were formed with a bigger lack of understanding than we have now. read a Thousand brains: a new theory of intelligence
vlovich123 5y ago
We’re quite far from human-level intelligence and require drastically more power and data storage. It wouldn’t be surprising to see that the ML powering general AI would look the same as today’s AI to 90s ML. Still useful but qualitatively a meaningfully different approach.
DrNuke 5y ago
Some combination (sequential, parallel, meta, whatever convenient shape) of single tasks executed at super-human ability (computer vision + path learning are there already) would inevitably lead to some sort of singularity when coupled with just SoA motion, handling and decision making / optimization. Generalizing occasional singularities, though, still seems a long way ahead.

Jensson 5y ago

> In addition to what others are saying I want to highlight that there's decent evidence that "all" we're doing is pattern finding and pattern matching. Is there? Link? It is possible, I just don't think there is enough evidence to say anything about it. What evidence would show that humans are just pattern finding and matching machines?

vanusa 5y ago

We're getting into the territory of some external debates -- that is to say, into areas that have already been debate by others, so there isn't much knew I could tell you here. But basically I'm in the camp of Gary Marcus and others, who would probably respond by saying something along the lines of the following: "No, there's not particularly good evidence that all we're doing is pattern matching, and a lot of evidence to the contrary. For one thing, a lot of these ML algorithms (touted as near- or superhuman) are easily fooled, especially when you jiggle the environmental context by even just a little bit." "For another, and on a higher level, what algorithms lack -- but which sentient mammals have in spades -- is an ability to 'catch' themselves, an ability to look at the whole situation and say 'Woah, something just isn't right here'. (This is referred to as the 'elephant in the room' problem with modern AI)." "And then there's the lack of a genuine survival drive -- not to mention the fact that we don't see any inkling of evidence of some capacity for self-awareness in any currently existing system." Just as a starting point. But these are some huge differences between currently existing AI systems (however you want to define "AI here) and actual sentient cognition. Huge, huge differences... such that I don't see one can get the idea that "all" we're doing is pattern recognition. Even if it may cover roughly 90 percent of what our neural tissues do - that other 10 percent is absolutely crucial, and completely elusive to any current, working technology as such. When someday we do achieve human level intelligences in computers, it will be at least in large part with ML. No doubt it will, but still there's that ... remaining 10 percent. Which you won't get to with accelerated pattern finding any more than a faster airplane will get you to the moon.

gmadsen 5y ago
All I will say is that these criticisms are outdated. they were formed with a bigger lack of understanding than we have now. read a Thousand brains: a new theory of intelligence

vlovich123 5y ago

We’re quite far from human-level intelligence and require drastically more power and data storage. It wouldn’t be surprising to see that the ML powering general AI would look the same as today’s AI to 90s ML. Still useful but qualitatively a meaningfully different approach.

DrNuke 5y ago

Some combination (sequential, parallel, meta, whatever convenient shape) of single tasks executed at super-human ability (computer vision + path learning are there already) would inevitably lead to some sort of singularity when coupled with just SoA motion, handling and decision making / optimization. Generalizing occasional singularities, though, still seems a long way ahead.