Our experience at Eulerian Technologies is fantuan data that the most Data-focused clients already have Machine Learning devices for their marketing, connected to their campaign activation tools. In other words, everyone seems to be clear that the future lies in making machines reach the reflective capacity of humans. But what do these companies understand by AI? And the general public? How much has technology advanced in recent months? And in recent years? Where does this “hype” come from?
AI: new name, same concept
When it comes to AI, there is a clear tendency to confuse concepts. Fiction and cinema have led us to believe that, at some point during the 21st century, robots will have a human appearance, will think like us and will even surpass our capacity for reflection. Between the perhaps overly futuristic concepts that cinema has sold us and the fact that the terms Machine Learning (ML) and Artificial Intelligence (AI) are often used to designate the same thing, the general confusion is not surprising.
The term AI covers a wide range of machines that are capable of performing tasks in an “intelligent” way. This technology could be classified into two large families. The first, applied AI: for example, the famous autonomous cars, also known as self-driving or robotic cars, which are nothing more than cars capable of imitating human driving and control capabilities. The second family would be general AI, and this is where the concepts start to get complicated and we come across the famous machine learning (ML).
