What is AI? What is it used for?
Artificial Intelligence is a topic that has been getting a lot of attention, mostly because of the rapid improvement that this field has undertaken. Amazing innovations today, are setting foundations for amazing achievements such as medical Research and even Flying Cars. In this article I am going to focus on 3 specific topics:
- “What is Artificial Intelligence?”, on this topic, I am going to discuss and explain what is AI, what it is being used for and I am going to give some examples of it’s use in the future.
- Machine Learning, here I will explain what is this strange topic and what is the connection to AI. Moreover, I will give a small example o Machine Learning in action!
- Flying Cars(Easter EGG), just for fun, and to discuss a near possibility of AI implementation, I am going to discuss the future of flying cars and how are their development today.
What is AI?
Back in the 1950s, the fathers of the field Minsky and McCarthy described artificial intelligence to be any task performed by a program or a machine that, if a human carried out the same activity, we would say the human had to apply intelligence to accomplish the task.
As you can see, this is a fairly broad description so, nowadays, everything associated with human intelligence: planning, learning, reasoning, problem-solving, knowledge representation, perception, motion, and manipulation and, to a lesser extent, social intelligence and creativity is described as AI.
“Artificial intelligence is defined as the branch of science and technology that concerned with the study of software and hardware to provide machines the ability to learn insights from data and environment, and the ability to adapt in changing situation with high precision, accuracy and speed.”
What is AI used for?
Now that we realized what AI actually means, let’s find out what is it used for today!
While surfing the web, have you ever wondered how most ads are related to your interests? That’s a representation of AI, more specifically a representation of Machine learning in action, which we will talk about in the next topic. However, AI is being more popularly associated with robots, the capability to think by their own and the capability to have consciousness. These are astounding achievements if concluded, today, being a student specialized in AI, I can tell you this involves truly complex algorithms which we still can’t even try to imagine.
Machine learning is a big part of AI, it may be the only reason why this field has had such a meteoric rise, and it is based on the thought of trial and error. It is sure that every time we try to solve, for example, a maze, we are going to fail at least one time. However, in ML, to fail is a good thing, because you can gain knowledge, this information is stored as data, and each time a robot makes a decision on a specific path, he will search his data to see which one is the best for him.
I know, this might be strange to interpret, so I am going to teach you the mother of AI algorithms, especially to solve mazes, which is The A* algorithm.
In order to understand this algorithm, let’s visualize, our maze, has a chess board, that has nodes that can’t be accessed, just like in a maze.
- Now let’s define our beginning mode and final node to be the top left node and the bottom right one, respectively.
- From here, associate every node of the board with a value, determined by the sum of the distance from the beginning and the distance to the end node.
- Now, the PC is going to make his decision of the node to pick, based on this sum, which gives an arrow path to the end! If it reaches a node he can’t pass, it comes back to the last node that was picked before, just like the gift below.
English: Illustration of A* search algorithm. The graph is created by uniform square discretization of a 2-dimensional…en.wikipedia.org
If you want a more in-depth view of this Algorithm I can advise you to watch the video below, it explains the A* Algorithm in a much better way and with an actual example.
This is a sort of easter egg of this article and represents AI in action, in fact the base of flying cars has to be AI. In the future, scientists believe we are going to have autonomous cars that transport people to their desired destinations, this involves cars to some sort of Artificial Intelligence, more specifically, the implementation of Machine Learning, because they need to always find the best possible course to the destination, not crash on buildings and respect other users that are traveling as well, to avoid what we call traffic. A very basic implementation of this, but extremely ineffective and slow, could be the A* algorithm we talked about, were buildings represent unaccessible nodes. However, some good options that can be used, but were not talked about due to its complexity are:
- Neural networks- They are structures that can be “trained” to recognize patterns in inputs, and from them estimate a possible output.
- Genetic Programming-Treats programs as the parameters. For example, you would be breeding pathfinding algorithms instead of paths, and your fitness function would rate each algorithm based on how well it does.
This article was written to provide a fun introduction to AI, to show its numerous usabilities and the power position that it will assume in the future. More than ever, it is crucial to know the principles of Artificial Intelligence, being so important in the future, it is equally important to enter with the right foot in this new generation because it might be the only option to prepare for this uncertain future.
“We need to constantly be open to new ideas and approaches, such as artificial intelligence (AI), and be willing to challenge assumptions.”