Artificial Intelligence and Deep Learning

Artificial Intelligence and Deep Learning

Most people always think artificial intelligence, machine learning, and deep learning mean the same thing. We have written this article to clear all the misconceptions you might have about these words. Although they are related to each other, the words do not mean the same thing.

Machine learning

Before defining machine learning, we should first talk about data mining. Data mining is the process of going through a pre-existing database with the aim of extracting new information from it. Machine learning works the same way. In fact, it is a technique employed in data mining. In a simple definition, machine learning is a method or technique that is used to parse data, learn from the data, and apply what you have learned to make data-driven decisions.

Several companies use machine learning to give their clients a better experience. For example, Netflix uses machine learning to give users better suggestions to movies that they would like to watch. Also, Amazon uses machine learning to give product recommendations to its customers based on their preferences or past purchases.

Deep Learning

Deep learning is considered a subset of machine learning. Technically, it has the same functions like machine learning but has different capabilities. Although machine learning models become better progressively, they still need some guidance. In other words, if a machine learning model gives an inaccurate prediction, it is up to the programmer to explicitly fix that problem. This is not the case in deep learning where the model does the correction by itself. An excellent example of deep learning is an automatic car driving system.

For example, suppose we want to have a system that turns the light on whenever it is dark. If we use machine learning to teach the model, we can probably program it to turn on the light when the user says dark. This means that the model will look for the word “dark” in people’s phrases before it can turn on the light. But suppose someone says “the light is very dim, I cannot see anything”. In this situation, the user wants the light on but the sentence does not have the word “dark”. So the light will not be turned on. With deep learning, the model learns from its own method of computing.

Deep learning is inspired by how the brain cells called neurons work. This has led to the concept of artificial neuron networks, which are modeled using layers of artificial neurons. These artificial neurons receive input and apply an activation function within a human set threshold.

We know that this concept may sound like rocket science and too Sci-Fi to newbies. However, Deep learning is already in our daily lives. There are five components of artificial neurons. They are:

  • Input nodes – Each of these is associated with a numerical value. The value can be any number.
  • Connections – Every connection departing from the input node has a weight associated with it. The weight can be any real number.
  • Weighted sum – Brings together all the values of the input nodes and weights of the connection
  • Activation or transfer function – Only comes into the picture when a certain threshold is exceeded.
  • Output node – It is associated with the function of the input nodes.

Artificial Intelligence

Artificial intelligence (AI) is completely different from the two concepts discussed above. Both machine learning and deep learning are subsets of artificial intelligence. They are a way of achieving AI. There are no standard or specific definitions of AI. Here is a simple definition coined by our online artificial intelligence and deep learning experts to give you an idea of what AI is all about.

Artificial intelligence is the ability of a computer program or system to function like a human brain. AI experts try to replicate the human brain. This includes how a man thinks works and functions. Until now, there are no perfect systems that have been established to work as a human being. However, Technology Experts have come close with Sophia, which is the most advanced AI model present today.

It is quite complex to replicate the human brain. AI professionals still don’t know several experts about the human brain like how do we dream? This is the main reason why they have not been able to come up with a perfect AI system until now.

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