How does data quantity affect the accuracy of AI prediction models?

The accuracy of AI prediction models directly correlates with the quantity and quality of data provided. As Johnny Harris explains, 'The more data you give it or train it on, the more accurate its results are.' This principle applies across various predictive scenarios, particularly in forecasting natural phenomena like hurricanes. For hurricane prediction specifically, incorporating extensive data on sea surface temperature, air pressure, wind speed, humidity levels, ocean heat content, and historical storm patterns significantly enhances predictive accuracy. These comprehensive data inputs enable AI systems to make more precise forecasts about a hurricane's path and characteristics, demonstrating how data-rich environments produce more reliable predictive outcomes.