Explore How Google’s Latest AI Model Delivers Zero-Shot Forecasting Accuracy Using Over 307 Billion Data Points
This post was co-authored with Rafael Guedes.
Forecasting is an essential aspect of decision-making in various industries, with retail being a prime example. Predictive capabilities play a crucial role in optimizing business operations, from financial planning to stock management. Developing an accurate forecasting model is key to improving processes and driving better decision-making across the board.
To build a reliable forecasting model, a deep understanding of state-of-the-art methodologies is necessary, along with domain-specific knowledge. The rise of pre-trained models has streamlined the process, eliminating the need for extensive customization. Leveraging the success of Large Language Models in the NLP community, researchers are now exploring the potential of pre-trained models in time series forecasting.
While there are similarities between language and time series tasks, there are also key differences that need to be taken into account…