AI is everywhere. Would you agree? The computer, smartphone, tablet, and voice assistant that are built into our phones all include AI technology. It is also the driving force behind most searches conducted online and in self-driving automobiles. It’s possible that you’re not familiar with the numerous kinds of AI out there. Therefore, we decided to introduce you to the various types of AI.
Table of Contents
1. Reactive Machines
The first robot on the job for the first time was extremely basic in its functionality. You could tell that impulses from the outside were driving it. The first production robot that we saw, referred to as a “stop and go”, was a humanoid-like figure that was completely reactive. It didn’t even have a central brain.
These robots, like the KrioRus Alba 6 and the DaVinci “iFlex,” were available at a very reasonable price. However, despite their lack of complexity, they performed exceptionally well. After encountering computers with limited memory, our next encounter was with extremely advanced machines with artificial intelligence.
2. Limited Memory Machines
The similarities between reactive machines, self-aware machines, and software are far greater than between reactive and mechanical machines. They are extremely iterative, meaning that the developers can build new features on top of them whenever they are required. They were developed to have a reactive nature. As a tool for matching patterns, we make use of them.
Let’s imagine you have a list of one hundred objects that you want to be able to identify. However, your memory is not infinite. Due to the sheer volume of information, you will need to compile an accurate catalogue to locate certain items. Consequently, we will construct a computer or compile a catalogue to hold the first one hundred items in a list. Then, if it comes across a new object, it will inquire whether you are familiar with the item in question.
3. Mind Machine Theory
This refers to developing computer programs that can sense their surroundings and remember them using machine learning. They can pick up on what is happening around them and learn from their experiences. Machine learning is used in the creation of reactive machines, which are machines that carry out tasks based on commands.
The systems adapt their modes of interaction with the surrounding environment in response to our commands. Discussions within customer service chatbots are automated using self-awareness, which enables them to resemble human conversations. Both machine learning and big data are “data-driven” in their approach.
4. Self-awareness Machines
As mentioned above, these machines are also capable of reasoning for themselves, even though they are still in their very initial phase. In other words, they are mindful of themselves, their feelings, and their surroundings and aware of the world around them.
Conclusion
Many distinct areas of research have immensely benefited from artificial intelligence. The study of human intelligence is an example of one of these fields. Researchers have started developing artificial minds that function similarly to natural minds as we learn more about how the mind functions and what factors contribute to forming our identities. AI software is also collaborating with other industries, including robotics, cybernetics, and computer software design.
