Introduction to AI #2: the explosion
Artificial Intelligence (AI) raises many questions. And for a good reason: it is an extremely broad area for which there are many definitions and which disrupts many aspects of society.
If we hear a lot about AI today, it is because it has an increasingly more significant place in our lives: indeed, we use tools based on AI every day. For instance, it helps us with automatic word completion on mobile phones, it allows the recommendation of press articles or information in a newsfeed or it is used to optimize the price of airplane tickets.
In the previous article, we gave an accelerated biography of AI. Drawing its roots from a distant imagination, it was first named in 1955 and has known since then moments of elation with high expectations and less dynamic moments. In this article, we will look at why AI is increasingly being used.
The launching ramp
But why does AI seem to be such a new concept? In the past, there were fewer possibilities due to the lack of computing power and data (in 2012, Google’s AI needed a huge amount – several million – of cat pictures to be able to learn the concept of cat!). It developed particularly in the 2000s thanks to a combination of two factors. First of all, the availability of data: the storage cost has decreased, the physical volume has increased and we are generating more and more data (it is the “Big Data” era). In addition to this, the power of processors makes it increasingly easy and fast to process large amounts of data.
Therefore, AI left the laboratories and entered our lives. While the scientific community was initially too optimistic about the possibilities offered by AI with the development of computing power, it is now more realistic and unable to predict how far they will expand. We did not expect a machine to be able to beat a human to Go, the famous board game. This new development of AI, related to the possibilities of applying it on a large scale, allows to disrupt every conceivable field, from translation to health. This technical success partly explains why this old concept is now in the spotlights.
There is also an economic success. The use of data is a factor in value creation. Again, Big Data plays a role: it is often crucial to have a large amount of data so that AI algorithms can recognize a pattern. But on the other hand, having this data alone (without processing it) does not create any value. When AI began to produce results, more funding was attracted which allowed the development of applications and led us to even more results.
AI has a logical place in task automation: it frees up human time to dedicate us to new things. For example, search engines can help us find information among a large amount of other information. This helps us in both our professional lives (finding a document using the search engine integrated into Windows’ file explorer) and our private lives (finding information about a show using Google). It is easy to understand why AI was adopted very quickly, contributing to its economic and social success.
After a stormy start (sometimes referred to as the “winter of Artificial Intelligence”), AI now seems to have established itself in a stable and sustainable way in our daily landscape. This success was driven by three waves: a technological progress, which led to an economic success, to end up with its adoption by society.
In the next article of our series, we will dive into the technical world of AI to better understand why it is difficult to define it and why the uses are so varied.
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