Generative Adversarial Networks – or GAN – is powerful newcomer in the AI realm. GANs can be used to generate new data, that can help train new models as well as test and validate AI-based systems. Cristofer’s and Stefan’s guest this time is Edvin Listo Zec from RISE, who will discuss opportunities and risks with GANs.

Episode 06: Generative Adversarial Networks with Edvin Listo Zec

In this course we will explore the challenges presented when designing AI-powered services. In particular, we will take a look at Machine Learning (such as deep learning and generative adversarial networks), and how that can be used in human-centered design of digital services. This course is created for User Experience (UX) professionals, Service Designers, and Product Managers as a way to help take a human-centered approach to AI in their work. The course is also useful for developers and engineers who want to both learn more about different Machine Learning techniques, and at the same time get a deeper understanding of the importance of a human-centered approach to digital design. The podcast is developed by Pontus Wärnestål, Stefan Byttner, Cristofer Englund and Jeanette Sjöberg at Halmstad University in Sweden, and is financed by VINNOVA. Music by Lee Rosevere. Read more: dap.hh.se

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Episode 06: Generative Adversarial Networks with Edvin Listo Zec

Episode 06: Generative Adversarial Networks with Edvin Listo Zec