“Artificial intelligence?” – “Sure, I’ve heard of it” is a common reaction. But companies are often at a loss as to how they can profitably use AI technologies. Our scientists give businesses a helping hand in a consortium project that offers numerous advantages.
Artificial intelligence (AI) is a key factor determining the success of companies today. When you put your ear to the ground, however, you quickly discover that only a small minority knows what it really is – in place of factual knowledge, there are a lot of misconceptions doing the rounds. And things get even trickier when it comes to the concrete question of how to use artificial intelligence to solve a company’s individual issues in a targeted and effective manner. As a result, businesses often end up choosing unsuitable or overly complicated applications when looking to use AI – leading to frustration rather than the success they were seeking. In many cases, this leaves the potential of AI unexploited.
Getting from an airy buzzword to specialist knowledge, methodological expertise and concrete implementation
Scientists at Fraunhofer IIS’s Engineering of Adaptive Systems division EAS have embraced the goal of changing this unfortunate situation and allowing companies to tap the benefits of artificial intelligence by means of a consortium project that was launched on September 16, 2020 and was founded in conjunction with KEX Knowledge Exchange AG. “Through the consortium project, we want to pull artificial intelligence down out of the buzzword clouds and make it tangible and usable for our partners – after all, the employees in the companies rarely come from an AI background,” says Anne Loos, Head of Business Development at the Engineering of Adaptive Systems division EAS. The project has attracted a lot of interest in the industrial sector, with 20 companies signing up to participate, ranging from small businesses and SMEs to large corporations. There is also a lot of diversity in terms of different sectors.
The project comprises three phases. To begin, there is foundational training: “There’s a tendency to think of artificial intelligence as something you turn to when you reach the limits of your own capabilities,” Loos says. “But that’s actually way off the mark: AI can’t always solve problems for which we ourselves don’t yet have a solution. But it does help us speed up complex procedures and relationships – provided we’ve described them first.” That is to say, the true core of artificial intelligence is the training phase, during which expert knowledge is represented in the AI. Only when the system has been trained in this way can AI take a step beyond and learn things independently.