Artificial Intelligence, Machine Learning, and Deep Learning are the three tech catch words right now and we often get to hear about it. So what actually these words mean and what’s the difference between them? Let’s take a deeper look into it.
Artificial intelligence is similar to adding a brain to the machine. In short, making a machine thinks and act upon the inputs which they get. Artificial intelligence doesn’t mean a magic. Artificial Intelligence works based on the sample input training given to the machine. For example, if you add a logic to the machine to respond “hi” when we send them a “hi” message then it becomes an Artificial Intelligence machine. Artificial Intelligence machine is fed with thousands of such sample datum.
Machine Learning is one of the forms of Artificial Intelligence but what’s the difference then? In artificial intelligence, the sample inputs are already fed into the machine but in the machine learning, we do not feed the sample data. Taking the same example of “hi”, when we say hi to the machine learning we need to tell the machine to output as “hi” so that when the next user says “hi” the machine will automatically respond “hi” based on the first user input. This makes the Machine Learning as one of the dangerous cause as well.
Suppose if the very first user trains the machine to respond “bye” to “hi” message then the machine will respond the same for next user as well. Why dangerous? The machine when trained to kill humans will become an unstoppable cause of danger.
Deep learning is part of a family of machine learning where the sample is not exactly fed into the machine. The data are predicted based on predictive analysis from huge amount of inputs also known as BIGDATA. Bigdata is basically huge terabytes of data. It can be an analysis of data from social media platforms such as Facebook, Twitter or any other such forms. This technology is derived from the concept of neural networks in the brain. It analyzed the huge data and form a big predictive neural network. These neural networks are used for analyzing the output.
These 3 buzzwords have evolved to form a greater part of technology at present Era. They have the power of making an completely automated machine world where everything would become luxuriously automated. From small things such as transporting goods from one place to another in a completely automated way to a huge task such as planning for launching rockets in space would get automated. They would take the world in a different objective space.
As rightly said everything has a good face and a bad face the same applies to this scenario. If these AI bots are trained to do bad things like destruction of a particular place then they can be a cause of danger. They will change the world objectives upon proper implementation.