This is a guest post. The views expressed here are solely those of the author and do not represent positions of IEEE Spectrum or the IEEE. We owe the success of numerous state-of-the-art artificial intelligence applications to artificial neural networks. First designed decades ago, they rocketed the AI field to success quite recently, when researchers were able to run them on much more powerful hardware and feed them with huge amounts of data. Since then, the field of deep learning has been flourishing.

Since my childhood, I have been working towards my goal of building human-level AI. But I had two main areas of interest – game programming and artificial intelligence. I spent my days and nights developing various real-time algorithms for computer graphics, aiming for a career in game development. This period deepened my understanding of programming and computer architectures. I learned how to invent new algorithms, to optimize the code on a machine level, to use math and physics to simulate the world, to develop game engines and to do art, game design, and sound design.