How To Create A Self-Learning AI?

Artificial Intelligence is something that we see everywhere nowadays. Self-driven cars, automated factories, and Webpages controlled through algorithms are just a few examples of the many applications of AI. 

Traditional artificial intelligence (AI) uses computer algorithms to design computer programs that are supposed to make decisions or solve problems using the knowledge that is pre-programmed into them through code.

In contrast, self-learning AIs use machine learning techniques on top of advanced neural networks and deep learning frameworks like Google’s Tensorflow. At first look, AI seems to be the epitome of innovation, if it weren’t for a simple fact: Self-learning AIs still can’t learn all of it by themselves.

Self-learning AI programs, that have to identify objects or images, are fed large amounts of data, to create a neural network that matches the situation that needs to be identified. This means more photos of cats need to be uploaded for the AI system if it is supposed to recognize a cat in a picture. 

Self-learning programs need this advanced architecture because computers lack a natural way of identifying what an object is. The self-learning process is time-consuming and needs large amounts of data. Let’s move forward with an example. 

When you want to create an image recognition program using self-learning AI systems, you’ll have to upload 100 photos of the object you want to identify and 100 photos of an object that is opposite or different from the original object into the system; 

And that’s not it. It will take days for these objects to train upon the system. The system will require test data to check if the machine is trained enough to identify the correct object. Self-learning AIs can spend weeks on training the images and multiple attempts of tests before they start producing accurate results.

Even after producing accurate results, Self-learning AI’s have to maintain a continuous and ever-going learning process. Without that the self-learning AI will slowly get inaccurate and will often be confused about newly acquired photos.

All of this and so much more goes into making a self-learning AI. To know more about technology and Artificial intelligence, visit us at