„Sobald Machine Learning ins Projekt kommt, verfallen alle in die wüsten 80er.“ Sind nun wieder Spaghetti-Code und Frickelbetrieb angesagt, nur weil auf einmal eine ML-Komponente unsere Architektur ergänzt? Larysa behauptet: nein! Wie machen wir es besser? Und wie hilft dabei MLOps? Darüber sprechen Robert und Larysa in dieser Folge.
Robert Glaser works as Head of Data and AI at INNOQ and boasts extensive experience from his previous role as a Senior Consultant. With a background in software engineering and expertise in developing ergonomic web applications, he advises companies on shaping sustainable IT strategies with a focus on Artificial Intelligence. He has a particular interest in the use cases for generative AI and the integration of AI into software products. In his podcast “AI und jetzt,” he discusses the opportunities of AI in diverse contexts. As a bridge-builder between technology and the business world, he is passionate about user-centered digitization. Beyond that, culinary delights are his major passion.
Larysa Visengeriyeva received her doctorate in Augmented Data Quality Management at the TU Berlin. At INNOQ she is working on the operationalization of Machine Learning (MLOps), data architectures such as Data Mesh and Domain-Driven Design.
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