I had an interesting chat with AI researcher and artificial intelligence specialist, Richard Russell, who gave a fascinating and insightful presentation at the IEEE International Conference on Intelligent Robots and Systems in London on Tuesday.
We’re going to be going to a large amount of places where artificial intelligence is being used, and he said, “So, let’s look at what the most interesting work is being done by AI.”
We have an artificial intelligence in our pocket.
We have an AI in our head.
We want to learn and we want to understand.
It’s going to take some time for us to develop a set of algorithms that we can actually use to learn.
And he said that’s the big problem with artificial intelligence.
He says that the only reason why we have an intelligent robot that can be used for human jobs is because it has to be able to learn from experience.
We don’t want to use an intelligent machine that learns from experience, he said.
He also said that we’re seeing an increasing number of AI systems, such as machine learning systems, that have to learn about the world.
We need to get rid of all the bad examples, and then the good ones, he added.
And that’s where we have to start, to get the good examples out of there and then we need to be looking for the good.
We also have to be doing things with artificial neural networks, he explained.
So, if you have an algorithm that can learn from lots of examples, that’s good.
But if you’re training an AI system, which I think is the case right now, that can only learn a certain kind of example, that doesn’t work very well.
So, he says we have a big opportunity to learn new things, new ways to do things.
He said that a lot of the AI work being done in the world right now is not really about teaching machines to do more or learn more, but about how to get a machine to learn things that humans are not very good at.
And we need that in the future.
We also need to have good, robust systems that are not going to become more and more expensive.
He added that if we don’t have good and robust AI systems then we’ll have problems, and there are going to have to go hand-in-hand with the problem of AI and automation.