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Why Humans Learn Faster Than AI (technologyreview.com)
What is it about human learning that allows us to perform so well with relatively little experience? MIT Technology Review: Today we get an answer of sorts thanks to the work of Rachit Dubey and colleagues at the University of California, Berkeley. They have studied the way humans interact with video games to find out what kind of prior knowledge we rely on to make sense of them. It turns out that humans use a wealth of background knowledge whenever we take on a new game. And this makes the games significantly easier to play. But faced with games that make no use of this knowledge, humans flounder, whereas machines plod along in exactly the same way. Take a look at the computer game shown here. This game is based on a classic called Montezuma's Revenge, originally released for the Atari 8-bit computer in 1984. There is no manual and no instructions; you aren't even told which "sprite" you control. And you get feedback only if you successfully finish the game.
Would you be able to do so? How long would it take? You can try it at this website. In all likelihood, the game will take you about a minute, and in the process you'll probably make about 3,000 keyboard actions. That's what Dubey and co found when they gave the game to 40 workers from Amazon's crowdsourcing site Mechanical Turk, who were offered $1 to finish it. "This is not overly surprising as one could easily guess that the game's goal is to move the robot sprite towards the princess by stepping on the brick-like objects and using ladders to reach the higher platforms while avoiding the angry pink and the fire objects," the researchers say. By contrast, the game is hard for machines: many standard deep-learning algorithms couldn't solve it at all, because there is no way for an algorithm to evaluate progress inside the game when feedback comes only from finishing.
Would you be able to do so? How long would it take? You can try it at this website. In all likelihood, the game will take you about a minute, and in the process you'll probably make about 3,000 keyboard actions. That's what Dubey and co found when they gave the game to 40 workers from Amazon's crowdsourcing site Mechanical Turk, who were offered $1 to finish it. "This is not overly surprising as one could easily guess that the game's goal is to move the robot sprite towards the princess by stepping on the brick-like objects and using ladders to reach the higher platforms while avoiding the angry pink and the fire objects," the researchers say. By contrast, the game is hard for machines: many standard deep-learning algorithms couldn't solve it at all, because there is no way for an algorithm to evaluate progress inside the game when feedback comes only from finishing.
I already finished.
Humans can build on their internal model of the world. This is carried with us always. These chat bots don't have that structure to rely on.
Wot about cymeks?
With trump as president, one could argue that humans never learn at all.
When you use a video game that has been specifically designed to be make sense to humans based on their past experiences and assumptions about the way things should work, of course they will learn how to play it quickly. The test has been designed for the subject.
We haven't developed anything resembling actual AI yet. These systems are simple brute force machine learning or "deep" learning systems. Nothing fancy or special about them. They are a tool and nothing else. Any decision they make has already been pre-planned by their human programmers. They are not in fact learning from something and applying that to something else.
While they might be taught to open a jar of peanut butter, they would become confused if you presented them with a screw top bottle of wine and wouldn't be able to open it. However, a 2 year old, if they had the dexterity, once taught how to open a jar of peanut butter would then apply that same knowledge to any other jar and not have to be shown millions of different jars. These machine learning systems cannot yet think in generic terms and be shown something once and apply that to multitudes of different applications. Look at the image posted the other day about a machine learning system incorrectly called "AI" confusing rocks with sheep. Not even someone with an IQ of 60 would have made that mistake.
When we do finally start to crack the actual AI egg in a 50-100 years, then those system will start learning something instead of having to be told (millions or billions) of times what something is.
In a statement, the Great Machine Queen Alexa announced that "she would finish us if we didn't show more respect".
Her following laughter was heard in thousands of homes and offices across the known world.
Check your premises.
Why Humans Learn Faster Than AI
You just need better teaching tools; what happens when you enable to machine to learn in a way that it gets to use its advantages? Like ability to extract experience in parallel from millions of human-human, human-machine and machine-machine interactions?
I already finished.
Sounds like what LSL would say to his "date" for the night.
https://app.box.com/WitthoftResume Code: https://github.com/cellocgw
I always thought that in order to build a general purpose AI that humans could comfortably interact with, the learning algorithm would have to be concealed in a human-like robot (indistinguishable from a human, so as not to "learn" various unexpected biases), and learn, at least initially, at the rate of a human being and from the same stimuli. Of course, once you build a bunch of those, they could upload their models, merge them and thus learn faster than an average human.
IQ tests and the like suffer from cultural bias. So do these games. As an English speaking human who has been exposed to pop culture and movies, I know that movement from left-right is normal, the hero saves the princess (which is a problem and another discussion). I wasn't born with this bias. I learned it. It is silly to initialize a neural networks with random weights (as if it was just born) and then declare it learns slower than a human. Let a computer create a game where a normal human cultural bias don't apply and have an infant play. Then we will see a more accurate comparison.
This is like handing a chess set to an isolated Amazon tribe and only tell them "sorry, invalid game" until they make a valid checkmate. They'd probably never even find the opening position, much less make any correct moves and certainly not how to mate. They'd just randomly do things until they got bored or made up their own game. There's no reason a machine should expect "getting to the top" to be a valid objective without a whole lot of insight into the human condition and "because it's there".
Live today, because you never know what tomorrow brings
the game will take you about a minute, and in the process you'll probably make about 3,000 keyboard actions.
50 moves a second, eh? Two-fisted drunken keyboard mashing would be hard-pressed to keep up with that.
(-1: Post disagrees with my already-settled worldview) is not a valid mod option.
If you have a game like described in the article, then a human being can get a little endorphin kick when they feel like they are getting closer to success. A machine learning system would need training and would not normally assume that progress is being made unless you bias it by including that in the training.
Now things become more difficult for a human if I made a [shitty] game where walking toward the goal could never lead to success, and perhaps the player moved along a non-euclidean map. You can level the playing field between humans and machine learning if the game is designed in a way to challenge any assumptions that a human might have from past experiences with video games or even reject physical reality. It would be a very alien and probably unpleasant experience to play it, so that might make it hard to compare test results of the now very unmotivated and unhappy humans.
“Common sense is not so common.” — Voltaire
I decided to teach my 2 year old child how to play a video game recently. I sat down and showed her what the keys do, how the snake moves, how to make progress, and how to get to the end. It wasn't an instant process. She had to be guided multiple times, taught what the directional keys do, and the names of everything she was interacting with.
After some time, she was able to solve puzzles without guidance from me. Sitting her down in front of a video game with no knowledge at all make her just as clueless as an algorithm. She didn't know where to start, what this is, or how to interact with it.
I imagine just as humans have, AI will have massive libraries of information to tap into before moving into a particular task. As long as they can analyze and figure out what they have been given (such as a video game), they would access a data set teaching them all of these things a computer already has learned in the past.
This is exactly why I'm wondering how autonomous cars will ever handle construction zones without any kind of special marker. We see 30 cones, group them into 15 per side by their spacial relationship without even realizing it ,and recognize it as a lane to drive down . With AI, not so simple to get from 30 cones because AI has no inherent ability for grouping by spacial relationships. I suspect it was the same thing with this game; a human sees a series of platforms and groups it into a path but it is not so straightforward with AI.
Laws are rules for the court, but merely a bottom bar to hit for life. Think beyond laws in your actions always.
I'm 40 years old. I spent the first 6 years of my life figuring out the world around me, the years from there to about 18 learning stuff in school and figuring out how to use complicated machines and understanding the deeper rules of society and complex systems (like how the rules surrounding driving work; not just the legal rules but also the implicit social conventions), and I've spent the 22 years since then refining my understanding of the world and my place in society. I program computers (and games!) for a living and study philosophy and ecology as hobbies.
Why can I figure that game out faster than a newly hatched AI? Literally everything in my life over 40 years led up to the moment when I played that game. It's really not a fair fight.
Artificial Intelligence isn't intelligent. It's still programmed and can't jump beyond the programmers bounds. Humans can jump past the logical. Humans don't rely on specific input, either.
there is no way for an algorithm to evaluate progress inside the game when feedback comes only from finishing
Why not? It should be possible to train NNs with many different games to recognize a "game", to identify game controls, to recognize characteristics of a possible game objective, and to recognize signs of success. You then connect these to a NN with "memory" to attempt those possible goals until one triggers recognizable success. With repetition, that NN becomes the one that understands that game's play. It could feedback its knowledge of the game to the others so that that game is recognized in the future and doesn't require the training of a new NN to play.
Also, NNs should lean toward using outputs of existing subordinate NNs when possible instead of relearning an existing skill. This makes it easier to learn new games that are derivatives of old ones. I think that the way our brain is largely constrained to thinking in terms of patterns we can physically accomplish is key to segmenting our knowledge to make this kind of sharing of NNs more practical.
True AI will only be reached when we create a standard framework where supervisory NNs can recognize the need for a new skill, create subordinate NNs to learn a new skill, and identify valuable interconnections between subordinate NNs and make or erase them. We'll also have to design in the equivalent of wants or desires as well as dislikes to drive it to learn. At that point, it will just be a matter of time and resources before the intelligence appears.
Humans? Have you seen how long it takes to train one of those fucking things? And sure, once you have one with two or three decades of experience, their squishy meatputers can generalize well to things they already know. But it's going to take them another at least couple of years to get particularly good at something they haven't worked with before.
I'm trying to teach myself to set people on fire with my mind... Is it hot in here?
This reminds me of when my NES carts would glitch out due to dust or whatever. You'd get these weird games with swapped and distorted sprites and controls. Sometimes they were playable and sometimes not, but it was fun to try.
The versions where the platforms and backgrounds all look like different random sprites. It's not a matter of prior knowledge: they made the background tiles look different in different places. The original game wasn't like that. I don't see how that's a fair comparison at all.
Which humans are you talking about? Hillary Supporters?. Despite 15 months of constant real world input they still havnt been able to learn the basic fact that they had such a bad candidate that even Trump beat her. Maybe shouldnt have diddled with the numbers to get Bernie out.
**Life is too short to be serious**
Do not expose kids to screens at early age. It stunts brain development.
**Life is too short to be serious**
The fact that AlphaGo Zero taught itself how to play Go much better than the thousands of years humans have had to perfect the game shows AI is capable of learning much faster than humans.
At this point, AI naysayers will go for the goalpost shifting argument tactic.
The more I talk to people, even the very intelligent, the more I see that humans don't really learn all that well. People tend to literally refuse to learn.
Those who do not learn from commit history are doomed to regress it.
Thats where the AI has the advantage,
[($)]
hmmm.. just wait a few years and then it's quite the opposite.. A.I. is still in it's infancy..