In this episode, hosts Mariana Menchero and Faranak Golestaneh explore the cutting-edge world of foundation models for time series forecasting with guests Azul Garza Ramírez, cofounder of Nixtla, and Mononito Goswami, one of the developers of MOMENT, a family of open-source foundation models for general-purpose time series analysis.

In this episode, we discuss the guests' transition into working with foundation models for time series forecasting. The guests describe the empirical approach they took, inspired by the success of Transformers in other domains like video, images, and text. Their experiments with adapting these models to time series data yielded exciting results, leading to the development of new products and tools.

The conversation sets the stage for a deep dive into the challenges and opportunities presented by foundation models in time series forecasting. The discussion highlights the need for massive, diverse datasets and the potential for these models to learn patterns and extrapolate to new data effectively.

This episode underscores the rapid advancements in time series forecasting and the growing importance of foundation models in pushing the boundaries of what's possible in this field. It offers listeners a glimpse into the minds of innovators who are shaping the future of time series analysis and its applications across various industries.

In this episode, guest hosts George Boretos and Arian Sultan Khan explore the intersection of Neuroscience with Forecasting & AI with guest Kai Markus Mueller, acclaimed neuroscientist and a pioneer in Neuropricing.

Kai, who began his journey in psychology with aspirations of becoming a child psychotherapist, eventually shifted his focus to cognitive psychology and neuroscience. His transition from academia to the industry led to the invention of Neuropricing that utilizes fMRI and EEG to understand consumer behavior and predict responses to advertising and pricing.

The podcast delves into Kai’s innovative work, highlighting how brain activity can often predict consumer behavior more accurately than traditional self-reported methods, with success stories such as Starbucks coffee pricing research and Pepsi’s strategy in Turkey.

Kai explains the practical applications of neuroscience in business, such as storyboard testing for advertising effectiveness. He discusses the integration of AI with neuroscience to enhance predictive models.

He also shares insights on balancing his various roles as an entrepreneur, professor, and industry practitioner, emphasizing the importance of a supportive team. Looking ahead, Kai sees immense potential for neuroscience and AI to transform business strategies, pricing, and drive marketing success.

The conversation underscores the growing mainstream acceptance and practical benefits of these advanced technologies.

In this episode, we had the privilege of hosting Mitchell O'Hara-Wild, data scientist and lead developer of the widely used and highly acclaimed forecasting packages, Fable and Feasts.

Mitchell is a PhD candidate at Monash University, Australia. He shared insights on a wide range of topics, including his journey into data science and forecasting, the reasons behind the development of the popular Fable package, and his views on AI in forecasting.

We also discussed Mitchell’s research on DAGs (Directed Acyclic Graphs) in the context of forecast reconciliation, as well as his consulting experience forecasting COVID-19 cases in Australia. Moreover, we had the opportunity to talk about his experience delivering workshops to researchers and practitioners through the IIF's Forecasting for Social Good community (F4SG) and at useR! conferences.

Listen to this podcast and learn more about Mitchell’s remarkable work in the realm of forecasting, software development, and the future of forecasting in the era of AI.