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Levels of Intelligence

Has AI reached human intelligence?
Hey, welcome back in this session, we want to speak about levels of AI, we have already an idea of what AI actually can be, but what kind of aspects of AI exists because it is a rather broad field and sometimes we are really interested in those intelligent, self-learning systems. So on a very, very high level, there are two major directions of AI. One is the strong AI and the other one is the weak AI. The strong AI is quite commonly assumed to be the definition of AI as really an AI which is able to imitate and maybe even replicate human intelligence should learn by itself.
It should be self conscious and maybe even when we interact with it, we at some point don’t even realize that there is an AI inside, but we might even assume it’s a human being that is actually the goal of some AI researchers. But most of the researches focuses on weak AI, and that is actually the applied air. And we are also interested in that is we have an imitation of intelligence and a more closer defined world, maybe for a very specific task. And then we can have just rules or also self-learning systems which make the best of the hardware in a given environment. And then we have an AI which supports humans to solve specific tasks.
So these two different definitions exist, and there are many others, maybe you have also heard about GOFAI (Good Old-Fashioned Artificial Intelligence) which is again towards the idea of a strong AI But it is not so important if we now focus on strong or weak AI, it’s more interesting to look into what kind of AIs exist. So there are several levels, and these levels are either we have a very simple agent, so it’s just has reflects. And so as a smart rule, if the temperature is higher than 50 degrees, then switch on the water or turn on the air conditioning or whatever. So that can be very simple rules, and that’s already a basic AI.
And then we can have a state full AI that one remembers the state of the environment. So we we don’t always have to give an input it also produces an output based on the current state, which is in very simple example, could be a clock or a traffic light. There is a state inside and after a while, it produces a different output. So all of these systems, even though they are a just rule-based systems, are included in a very broad definition of AI However, in most of the AI applications, we are interested in systems which go beyond that. They, for example, are able to pursue a given goal. So these are goal based agents.
You give a problem and it wants to solve it, like in search, you put in a search term in your search engine and then it tells you this and this and this are the most interesting documents for you. And then finally, this utility based agent, that one does not only fulfill the goal, but also tries to optimize the way to reach that goal. So if you want to travel from A to B., there are many, many ways you could even walk, maybe, but that’s not what we typically are interested in. So it’s tries to optimize either for time for cost or a combined optimization time, cost, and the energy use So the effects of the environment.
So these levels of intelligence exists. And the idea is that an AI, especially a learning AI, should be able to generalize beyond the distribution of what it has seen already while we were programming it or training it.

It is not an easy task to know whether the provided AI is strong or weak. This video will furnish you with more details about the differences between the two types. Levels of intelligence will be discussed as well in this material.


  • Can you differentiate between strong and weak AI?
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An Introduction to Artificial Intelligence in the Tourism Industry

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