Scientists used deep learning to create a computer model that can predict harmful algal blooms in the ocean. They used special types of neural networks to simulate when and how these blooms happen. The model was very accurate, with a 96.8% success rate in predicting bloom initiation and a small error in estimating bloom density. The study found that factors like salinity, temperature, and ammonia levels play a role in the growth of these harmful algal blooms.