True artificial intelligence should also have a consciousness.

Artificial intelligence is an issue that has gained much popularity in the past few years. This is also evident in the number of technologies referring to artificial intelligence (AI).

Autonomous cars and personal assistants like Apple's Siri are often spoken about, while machine learning, deep learning and neural networks are frequently featured in written text. What do these terms mean, and what is the difference between them? How far has technology based on elements of AI progressed? We discussed these topics in a series of interviews with Juraj Janosik, an expert on artificial intelligence of the ESET company.

In the interview, you will learn: class="ul What artificial intelligence is and which AI approaches are currently being developed Why we owe the development of AI partially to games Why we don't always understand the decisions of AI How the human brain and reproduction of cells inspire the development of AI How old AI technologies, which many perceive as brand new, actually are Let's start right from the beginning. How can I grasp the notion Artificial Intelligence?f we can simulate human intelligence, consciousness and thinking with some technology, we achieve artificial intelligence.

There is a term for it - artificial general intelligence - but there is also a concept called super intelligence. While artificial general intelligence (AGI) is meant to imitate human thinking, including its faults, super intelligence (SI) should go even further and exceed the limits of human consciousness and thinking, and considerably surpass them.

However, there are more philosophical discourses involved, and we have to admit that currently, we are still far behind, even in the development of AGI.The issue of AI often brings up the terms machine learning (ML) and deep learning (DL).

What is the difference between them?These terms are frequently confused, even by professionals. Simply put, artificial intelligence is an umbrella notion.

It includes a wide range of topics that also cover the issues of robotics, machine learning and so on. Thus, machine learning is just one sphere of AI, and currently, it is probably gaining the most attention.

Deep learning, on the other hand, is just one part of machine learning. This sphere is inspired by how the brain functions and tries to simulate the connection between neurons in the brain.

Well, let's start from the beginning. How does ML function?The idea of machine learning is quite simple.

We have a lot of data available, and through ML, we want to make a compact representation of it. This means that if I have a huge amount of data, I do not have to sort through it all on my own.

It is enough for me to take a smaller sample, assort it and use an algorithm on it to in order to assign it the basic sorting/classification. Then, I let the learned algorithm work on another, smaller sample, and watch if it sorts it out according to my wish.

If not, I adjust its behaviour, for example by specifying criteria. If I am satisfied with the algorithm's performance, I use it for the whole database, and the algorithm sorts it on its own in a much shorter time than any human would manage.

Can you give a more specific example?For example, if we want to teach a computer how to distinguish a cup, we load thousands or millions of photos of cups and glasses. Of these pictures, the algorithm tries to create some sort of generalisation on its own.

Then, when I show it a new photo of a cup, it will be able to tell what is the probability that this is a cup. If I am not content with the results, I can adjust the criteria, for example, by telling it the object is a cup and so on.

Currently, when AI is mentioned, it is machine learning that is talked about the most. It already functions on a regular basis by, for example, recommending users programmes on Netflix based on the programmes they have already seen.

Mobile phones that categorise photographs, autonomous cars and cyber-security are also examples of machine learning we engage in. Right now, the biggest discussion in AI revolves around machine learning global companies like Google and Apple are investing massively in these technologies.

What is the difference between deep learning and machine learning?Deep learning also interprets bulks of data, of which we need to make a compact representation. This is called a model, which will then make predictions.

However, we will not use tree algorithms but rather neural networks.Neural networks are inspired by how the human brain works, by the functioning of neurons.

The brain is basically a huge network of neurons, which is entered through...

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