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Artificial intelligence will be the technology sensation of the next few years, with the AI market predicted to grow by 40 percent a year.
The European Union is also spending a staggering amount of its budget up to 2027 on the field.
But what will it take to make related corporate development truly effective?
And how far is AI currently embedded in our everyday lives?Listen to the full broadcast here.
First of all, it's worth clarifying what we even call artificial intelligence.
"The concept itself is not new, having been around in the US for over 60 years. In practice, however, it only became widespread in the 2010s. This is because it was only then that the computing power and the amount of data needed to teach an AI became widely available," says INSPYRE Informatics's CEO.
According to Péter Borzák, AI is capable of interpreting the data in order to draw conclusions to meet a specific goal.
"Imagine, for example, a large automotive assembly plant where there is a lot of concern about where certain parts are located, what pre-order products they have been set aside for, or which work phase they are involved in.
This is where machine vision and image recognition algorithms come to the rescue. Thanks to these, a worker can simply take a picture of a part and the associated mobile or web app identifies it in a few seconds, displaying all the associated data," he explains.
By using algorithms, companies can gain a competitive advantage
However, many are still concerned about AI.
It's a bit like the advent of fax machines or the internet, where many people initially thought they didn't need this innovation or that it was too expensive to implement.
Yet, as Péter Borzák pointed out, today, AI-related technologies can be implemented at affordable prices.
"Moreover, those who start using them sooner can gain a significant competitive advantage. Although it is now possible to license existing algorithms, it is not always advisable to use so-called "boxed" solutions.
Of course, they are cheaper, but the design and application of algorithms always depend on the specific use case.
- The first step is therefore to formulate the business problem itself so that the business can see what they want to use the algorithms for.
- Then, the data set used to train the AI must be prepared.
- The final step is to make the development live.
"If the development is done in-house, it is also recommended to work with external experts," he added.
The topicality of the subject is illustrated by the fact that digitalization, including artificial intelligence, is a priority in the EU budget.
According to the CEO, it is hard to imagine a business sector where the introduction of a fourth-generation technology could not bring immediate efficiency gains.
However, the business application of these technologies is still in its infancy in Hungary.
The reason for this is usually the fear of high costs, as already mentioned, although the introduction of innovative solutions does not necessarily involve unrealistically high costs nowadays.
Listen to the interview for more details!