Why is the process of transforming research into a “real-world” product so full of question marks? We often know where the research journey starts but have uncertainty about how and when it ends.

In this talk, I will share my own experience leading algorithmic teams through the cycle of research into production of live-streaming AI products. I will also share how to mitigate between agile incremental delivery and giant leaps forward that require longer research. The talk will outline test-driven machine learning development, how understanding the minimum viable product (MVP) way of thinking can help not only managers but every developer. Learn to outline MVP for new AI capabilities and move forward with production in mind while always raising quality standards. At the end of this session, you will get the boost you need to take the data-driven experimental mindset to the next level, along with methodologies you can adapt for development as well as research.