Law of Diminishing Returns for Running AI Proof-of-Concepts
Speakers

Oguzhan (Ouz) Gencoglu is the Co-founder and Head of AI at Top Data Science, a Helsinki-based AI consultancy. With his team, he delivered more than 70 machine learning solutions in numerous industries for the past 5 years. Before that, he used to conduct machine learning research in several countries including USA, Czech Republic, Turkey, Denmark, and Finland. Oguzhan has given more than 40 talks on machine learning to audiences of various backgrounds.

At the moment Demetrios is immersing himself in Machine Learning by interviewing experts from around the world in the weekly MLOps.community meetups. Demetrios is constantly learning and engaging in new activities to get uncomfortable and learn from his mistakes. He tries to bring creativity into every aspect of his life, whether that be analyzing the best paths forward, overcoming obstacles, or building lego houses with his daughter.
SUMMARY
Starting the AI adoption with AI Proof-of-Concepts (PoCs) is the most common choice for most companies. Yet, a significant percentage of AI PoCs do not make it into production whether they were successful or not. Furthermore, running yet another AI PoC follows the law of diminishing returns in various aspects. This talk revolves around this theme.

