Even if skipping completely the discussion about what is “intelligence”, the expression “artificial intelligence” has been used as a label for so many different technologies that it has become practically useless. It includes things like decision trees in games (even if a lot of them boil down to simple if/then statements), generative models, even theoretical systems that would reason in a human-like way. And evolutionary models like the one in the OP and the one in my link.
So it’s basically the 20s version of what “smart” was in the 90s/00s. Like this:
OK, I’m being cheeky and exaggerating it in the image macro, but it should give you an idea.
AI has been a field within computer science since at least the 1950s. It encompasses algorithms for making decisions, which is why so many technologies are labeled this way. “Intelligence” may seem like an odd choice of terminology (some people conflate it with sentience or similar), but general machine intelligence is one goal of this study, and the applications of AI are putative steps to that end.
Back when those guys started talking about what methods could get us there, things like decision trees, symbolic manipulation, neural nets, were all potential pathways that were on the table. So these get included in the field because that’s where and to what end they were produced.
Another thing is that intelligence can be narrow in its domain. A character in a video game that needs to move from point A to point B can do so following something like the A* pathfinding algorithm. In the domain of graph traversal/pathfinding, it’s hard to imagine something much more intelligent (or fit to solve the problem) than A* despite being a simple algorithm.
But yeah, as a marketing term it is kind of silly since most people don’t know what it means. It remains a useful categorization for a broad field of study/research in CS though.
I’m fine with the usage of the acronym and expression in CS; specially because scientists are damn stubborn when it comes to “This is not [word1]! This is [word2]! Don’t screw with the terminology, you muppet!”. (As they should.)
So the bone that I have to pick against it is mostly against its marketing usage. Specially when it masks the underlying tech, just to make it look fancier. (Like here.)
It may be over-used but in my mind it’s still the correct term. AI is quite a broad category so you can fit many kinds of software algorithms under it. Perhaps it’s misleading as many people probably imagine AI to imply AGI when it could just be narrow AI aswell which even though not generally intelligent may still be superhuman at this one specific task like in this example playing the labyrith.
Not really. Can you write this specific simpele algorithm out in a few lines? Its Computer Vision (which I admit uses probably quite a simple algorithm to find the ball) and a reinforcement learning algorithm with one goal; get the ball from start to finish, these are your only 2 inputs. They didn’t write the algorithm. Time and the neural network did the rest on its own. That’s were the artificial ‘intelligence’ is referring to, humans didn’t put any algorithm there.
I don’t get what the issue is calling it AI?
Even if skipping completely the discussion about what is “intelligence”, the expression “artificial intelligence” has been used as a label for so many different technologies that it has become practically useless. It includes things like decision trees in games (even if a lot of them boil down to simple if/then statements), generative models, even theoretical systems that would reason in a human-like way. And evolutionary models like the one in the OP and the one in my link.
So it’s basically the 20s version of what “smart” was in the 90s/00s. Like this:
OK, I’m being cheeky and exaggerating it in the image macro, but it should give you an idea.
AI has been a field within computer science since at least the 1950s. It encompasses algorithms for making decisions, which is why so many technologies are labeled this way. “Intelligence” may seem like an odd choice of terminology (some people conflate it with sentience or similar), but general machine intelligence is one goal of this study, and the applications of AI are putative steps to that end.
Back when those guys started talking about what methods could get us there, things like decision trees, symbolic manipulation, neural nets, were all potential pathways that were on the table. So these get included in the field because that’s where and to what end they were produced.
Another thing is that intelligence can be narrow in its domain. A character in a video game that needs to move from point A to point B can do so following something like the A* pathfinding algorithm. In the domain of graph traversal/pathfinding, it’s hard to imagine something much more intelligent (or fit to solve the problem) than A* despite being a simple algorithm.
But yeah, as a marketing term it is kind of silly since most people don’t know what it means. It remains a useful categorization for a broad field of study/research in CS though.
I’m fine with the usage of the acronym and expression in CS; specially because scientists are damn stubborn when it comes to “This is not [word1]! This is [word2]! Don’t screw with the terminology, you muppet!”. (As they should.)
So the bone that I have to pick against it is mostly against its marketing usage. Specially when it masks the underlying tech, just to make it look fancier. (Like here.)
It may be over-used but in my mind it’s still the correct term. AI is quite a broad category so you can fit many kinds of software algorithms under it. Perhaps it’s misleading as many people probably imagine AI to imply AGI when it could just be narrow AI aswell which even though not generally intelligent may still be superhuman at this one specific task like in this example playing the labyrith.
AI implies intelligence. This is just a simple algorithm
Not really. Can you write this specific simpele algorithm out in a few lines? Its Computer Vision (which I admit uses probably quite a simple algorithm to find the ball) and a reinforcement learning algorithm with one goal; get the ball from start to finish, these are your only 2 inputs. They didn’t write the algorithm. Time and the neural network did the rest on its own. That’s were the artificial ‘intelligence’ is referring to, humans didn’t put any algorithm there.