Welcome to the world of artificial intelligence: AI. This article is neither a technical puzzle nor a weapons register, but an invitation to a world full of inventions and innovations. But to explore this world, we need a map and a guide to lead us. This article aims to provide just that.

There is widespread misunderstanding about what AI actually is. Some think it’s an alien force threatening our lives, others say it’s just a marketing technique, and some try to offer a scientific explanation, hoping to be understood. In order to really understand it, you have to get to the root of the issue and investigate further. Likely, the word “artificial” is the easiest part to explain. Please take a minute and give it a try. Very simple, right? We can point to all kinds of things around us that are artificial in the truest sense of the word. The really difficult part of the expression is the second part: "intelligence". If we do the same exercise again, explaining the word might be a little harder. When putting these two parts together, it's easy to get to the real meaning of AI, which is, strictly speaking, intelligence. Human intelligence invested in enough computing power, speed, and memory building up to the powerful techniques and solutions we observe today. Every AI solution needs human intelligence behind it first and then uses advanced technologies and innovations to deliver results.

This brings us to the next question: What actually is an AI solution? Is it a robot? A drone? A chess player? AI as a domain is composed of solutions that express intelligence through machines, such as speech processing, image and video recognition, language and text understanding, knowledge extraction, and machine learning in the field of various topics - predictive and descriptive analytics. On the other hand, machine learning is a subset of AI. Figure 1 shows the main topics of cognitive services that the technology currently offers.

Fig. 1: Cognitive Services [1]

In theory, this all sounds amazing, if a bit general, we'll dive deeper to really understand AI’s use cases. The real world has something even more interesting to offer us: the many great AI use cases we see in our daily lives. For example, we could go into the industry and talk about advanced techniques that are being applied in healthcare to collect patient data and use it to predict disease, prescribe in areas that need improvement, or wearable technology. Or we can switch to the banking sector and discuss the anomaly detection algorithms developed to ensure customer account security. Or we can even dive into production lines and their optimization. There are so many applications that it’s difficult to make a selection. However, I would like to come to your daily life, so that you not only get to know these applications, but can actually experience them, or rather, experience AI.

Our morning routines are usually AI-centric. Now, think about your morning routine: Do you usually wake up next to your phone, or does your home assistant set the alarm for you? Adjusting our phone brightness, the good morning message from our virtual assistants (for instance: Alexa or Siri), the best route to work, all these normal activities are AI-driven. When you open your browser to check the train schedule, an advertisement will most likely appear. This process consists of a rather complex AI algorithm that’s calculated your interest in an ad and if you will perform a certain action. If you aren’t interested in the ad, you know the algorithm isn’t accurate, but it still exists.

Let’s leave the house and explore what’s going on outside. On the street, it’s a whole new world of AI: we can see edge devices, innovations, and algorithms in the air, on the sidewalk, and in front of businesses. Air quality sensors, traffic sensors and cameras, video surveillance, waste management systems, and smart lighting are only a few examples of AI solutions applied in outdoor environments. To sum it up, we are often on a road of computation, mathematics, analytics, and ultimately AI. One of the most interesting cases in the concept of smart streets and smart cities is applying AI to trash bins. Actually, there’s an interesting algorithm sequence that tracks sensor data about how full the bin is and optimizes trash collection routes so that we don’t have full trash bins...