Artificial intelligence promises mountains of gold. As smart algorithms are spreading like wildfire in the high tech industry, engineers are facing all kinds of obstacles. AI specialist Albert van Breemen tells us what tech companies have to take into account if they want to master the technology.
Artificial intelligence is a technology that, due to its versatile applicability, enables radical changes in many industries. AI has developed rapidly over the last eight years – even faster than experts predicted. This is mainly due to deep learning, an AI technology requiring a huge amount of data to work properly. The first wave of commercial AI applications has emerged at companies that already have lots of data, like Amazon, Facebook, Google and Uber. Currently, we’re seeing a second wave in which AI algorithms are being trained with sensor data. AI is entering the engineering world and traditional machine builders are faced with the question of whether and how to invest in artificial intelligence.
Designing advanced systems is getting ever more challenging. Each generation, their complexity grows. There’s an increasing demand for performance, intelligence and interoperability. Engineers regularly reach the limitations of their current toolbox, in which modeling and analysis from so-called “first principles” are standard. Adding AI gives them technologies to work with larger datasets (big data) and smart AI algorithms. Both elements form the basis for finding new solutions to the aforementioned challenges.
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