JD Retail Launches its First Self-Developed Billion-Parameter Time Series Model, TimeHF, for Predicting Product Sales

JD Retail's technology team announced the successful launch of TimeHF, its first self-developed billion-parameter time series model for sales forecasting. This model leverages Reinforcement Learning from Human Feedback (RLHF), applying it for the first time to sales forecasting. The accuracy of predictions has been significantly improved by over 10%, substantially reducing uncertainty in demand forecasting. This achievement has demonstrated excellent performance in JD's internal automated replenishment scenarios for 20,000 products.