The Four Types of Artificial Intelligence
Reactive Machines – The Definition
Reactive machines have no memory so they cannot store any experience. They are limited in their ability to make decisions and must react to what is in front of them. They cannot rely on past experiences.
It is a cost cutting measure to narrow the view of a reactive machine. It does not make it more trustworthy or reliable.
Reactive machine is an artificial intelligence technique that is used to predict what will happen next, based on the current state of the system. A reactive machine is not concerned with the future of the system or its own future actions. Instead, it predicts based on the current state of the system. An example of a reactive machine is Deep Blue, which was designed by IBM in the 1990’s as a chess-playing supercomputer.
Google’s AlphaGo is an artificial intelligence that has beaten world champion Go player Lee Sedol. AlphaGo is a more complex form of the computer Go player Deep Blue, and is capable of playing the game at a higher level than the previous computer Go player.
Artificial intelligence is used to make computer programs that can work automatically.
What Is Memory?
Limited memory artificial intelligence is an artificial intelligence that is able to learn from past experiences to predict what may happen in the future. Limited memory artificial intelligence is more complex and presents greater possibilities than reactive machines.
An AI model can be trained when you provide a machine with data to analyse. A machine learning model is created when a machine processes the data it is given and creates a model. The model can make predictions, it can receive feedback and that feedback is stored as data. The data is then re-evaluated to improve the model.
There are three major machine learning algorithms:
Learning to make predictions through repeated trial and error
The neural network that is used in LSTM models can be a powerful tool for making predictions. It can utilize data from the past to make predictions about the future.
The E-GAN model, which is constantly evolving over time, is designed to predict the outcome of a given situation and utilize simulations and statistics to make predictions. It uses chance to help make predictions.
Artificial intelligence is a real possibility. We are not yet at the point where we can create it, but it is on the horizon.
The premise is that if machines can understand human emotions and make decisions, they will be able to learn and take over from humans in many different areas of life. In short, they will have a two-way relationship with humans.
Artificial intelligence is only at its infancy. It is currently at the human level of consciousness and understanding. In the future, it will become more than just a robot and may even have its own life. It could understand what other people need and what they are feeling and communicate this to the people it is communicating to. It may even be able to communicate to other people what it needs.