According to Google DeepMind, a new dataset of table tennis ball throws and a MuJoCo simulation environment replicating real-world trajectories have been released on GitHub. This dataset includes detailed data on specific serves and rallies, enabling quantitative analysis and algorithmic backtesting for AI-powered trading strategies that leverage sports analytics signals. Traders focusing on AI development and data-driven modeling can now access high-fidelity, real-world motion data to enhance predictive machine learning models and test automated trading systems using trajectory-based features (Source: Google DeepMind Twitter, April 30, 2025).