In this episode, we spoke to Joannes Vermorel, founder and CEO at Lokad, a quantitative supply chain software company.

Joannes discussed how supply chain theory is broken down, and that we need to think in terms of paradigms and modules rather than models for solving supply chain problems. He talked about issues in time series forecasting and judgmental forecasting. He emphasized how critical it is to have a holistic view of the problem, to aim for optimization of the entire system. and to acknowledge that we often don’t know the metric to be optimized and it requires some experimentation. We also discussed how Lokad is deploying AI pilots to address some of the important problems in supply chain.

To learn more about Lokad, visit https://www.lokad.com/ or check them out on YouTube.

In this episode, we spoke to Laurent Ferrara, Professor of International Economics at SKEMA Business School. Laurent discussed the role of nowcasting, particularly in the realm of macroeconomic nowcasting. He delved into the details of the models and methods that have been proven effective in this domain. Laurent also talked about GDP nowcasting using Google data and shared some intriguing results from his recent research.

Laurent is the program chair of the 44th International Symposium on Forecasting, which will be held in Dijon, France. He provided an overview of the conference program and explained why we should attend!

In this episode of our podcast, we delve into the intricate world of machine learning (ML) deployment with Dr. Eric Siegel, author of the book AI Playbook, Mastering the Rare Art of Machine Learning Deployment.

Dr. Siegel, once an avid advocate of ML, now approaches the field with a disciplined yet optimistic perspective. He shares invaluable insights on how businesses can effectively implement ML strategies. Our discussion revolves around a range of compelling topics, from the inspiring story of Jack from UPS, who leveraged his psychology background to revolutionize parcel delivery, to the common pitfalls that cause many ML projects to fail.

Eric elucidates the six crucial steps for ML deployment, emphasizing the importance of ethical considerations in this rapidly evolving field. Whether you're a student, a business leader, or just an AI enthusiast, this episode offers a treasure trove of knowledge and strategies to navigate the complex landscape of machine learning deployment.