In this video I would like to talk about artificial intelligence, the history, the uses and some concerns we may have regarding the techniques of AI. So let's start with the term 'artificial intelligence', perhaps to give us some insight it to what the term means we should consider two ways a system may be artificial intelligent. 

So the two ways are that the system may be weakly artificial intelligent or strong, or strongly artificial intelligent, of course we're talking about computers. As a side issue what do we mean by computer, well we may think such a thing is intuitive but it actually really isn't, it's actually very hard to define what a computer is. For our purposes let's just say any system of algorithms or system of rules, any system that follows any kind of rule or algorithm. 

Okay, so what is it to be weakly artificial intelligent? What is it for a computer to be that? Well that's the behave as if you are a human in some specific condition so we're talking about systems that follow algorithms and then the question for us now then is how are these systems intelligent and what does it mean to be intelligent? So let's talk a little bit about what our goal is. Replicate or reproduce human performance on tasks where we require, let's say creativity, problem solving and other faculties that we are-, that are typically regarded as being faculties of intelligence. We're trying to behave-, the machine should behave as if it's human in some sense. 

Now back to weak and strong so something is weakly artificial intelligent if it can solve a problem, if it can replicate human performance on a highly specific task. So weak AI is highly specialised to a specific problem, you ask-, you know, you-, the-, you change from-, you move from a system conveyor belt to a different system, you, you enter a different postcode that hasn't-, you know, or a different letter style that it hasn't seen before and the whole thing is unusable. What is the alternative,? What is the alternative? The alternative is to solve a problem generally. Solving-, I would actually quite like to use the word here 'skill' or 'skill acquisition'. 

So one way we could define strong AI is that it is where machines acquire skills and a more common way of defining it perhaps, is this general, sort of, problem solving. The word 'general' here which is where if I, you know, if I get the machine to solve the mailing problem what I would hope is that I can solve some other kind of problem, like, you know, where the human being if I get them to solve one highly specific problem it isn't that somehow they're only able to do that, you know. Exceptionally rare would that be the case because human beings acquire skills and then they can solve small variations to problems to.