The hard part of the problem is that we need to have a system that can build up a good world model on it’s own. There is too much stuff, such that it takes way way too long for a human to enter everything. Also I think that we need to be able to process basically arbitrary input streams with our algorithm. E.g. build a model of the world just by seeing a camera feed and the input of a microphone.
And then we want to figure out how to constrain the world model, such that if we use some planning algorithm we also designed on this world model we know that it won’t kill us because there is weird stuff in the world model, like there is weird stuff in solomonoff induction, because that are just arbitrary programs.
Also, a hard part is to make a world model that is that general, that it can represent the complexity of the real world interpretable.
If you have a database where you just enter facts about the world like X laptop has Y resolution, that seems to be not nearly powerful enough. Your world model only seems to be complex and talk about the real world, because you use natural language words as descriptors. So to a human brain these things have meaning, but not to a computer by default. That is how you can get a false sense of how good your world model is.
Cyc does not work. At least not yet. I haven’t really looked into it a lot, but I expect that it will also not work in the near future for anything like doing a pivotal act. And they got a lot of man-hours put into it. In principle, it could probably succeed with enough data input, but it is not practical. Also, it would not succeed if you don’t have the right inference algorithms, and I guess that would be hard to notice when you are distracted entering all the data. Because you can just never stop entering the data, as there is so much of it to enter.
> Cyc does not work. What if the group of users adding knowledge was significantly larger than the Cyc team?.
Edit: I ask because CyC is built by a group of its employees, it is not crowdsourced. Crowdsourcing often involves a much larger group of people, like in Wikipedia.
> In principle, it could probably succeed with enough data input, but it is not practical. Why is it not practical?
> that would be hard to notice What do you mean by “to notice” here?
Cyc does not seem like the things that I would expect to work very well compared to a system that can build the world model from scratch because even if it is crowd sourced it would take to much effort.
I mean notice that the inference algorithms are too bad, to make the system capable enough. You can still increase the capability of the system very slowly, by just adding more data. So it seems easy to instead of fixing the inference, to just focus on adding more data, which is the wrong move in that situation.
I haven’t read it in detail.
The hard part of the problem is that we need to have a system that can build up a good world model on it’s own. There is too much stuff, such that it takes way way too long for a human to enter everything. Also I think that we need to be able to process basically arbitrary input streams with our algorithm. E.g. build a model of the world just by seeing a camera feed and the input of a microphone.
And then we want to figure out how to constrain the world model, such that if we use some planning algorithm we also designed on this world model we know that it won’t kill us because there is weird stuff in the world model, like there is weird stuff in solomonoff induction, because that are just arbitrary programs.
Also, a hard part is to make a world model that is that general, that it can represent the complexity of the real world interpretable.
If you have a database where you just enter facts about the world like X laptop has Y resolution, that seems to be not nearly powerful enough. Your world model only seems to be complex and talk about the real world, because you use natural language words as descriptors. So to a human brain these things have meaning, but not to a computer by default. That is how you can get a false sense of how good your world model is.
Is it also true for a large group of people? If yes then why?
Cyc does not work. At least not yet. I haven’t really looked into it a lot, but I expect that it will also not work in the near future for anything like doing a pivotal act. And they got a lot of man-hours put into it. In principle, it could probably succeed with enough data input, but it is not practical. Also, it would not succeed if you don’t have the right inference algorithms, and I guess that would be hard to notice when you are distracted entering all the data. Because you can just never stop entering the data, as there is so much of it to enter.
> Cyc does not work.
What if the group of users adding knowledge was significantly larger than the Cyc team?.
Edit: I ask because CyC is built by a group of its employees, it is not crowdsourced. Crowdsourcing often involves a much larger group of people, like in Wikipedia.
> In principle, it could probably succeed with enough data input, but it is not practical.
Why is it not practical?
> that would be hard to notice
What do you mean by “to notice” here?
Cyc does not seem like the things that I would expect to work very well compared to a system that can build the world model from scratch because even if it is crowd sourced it would take to much effort.
I mean notice that the inference algorithms are too bad, to make the system capable enough. You can still increase the capability of the system very slowly, by just adding more data. So it seems easy to instead of fixing the inference, to just focus on adding more data, which is the wrong move in that situation.