The article discusses using deep learning to predict the toxicity of molecules, which is important for drug design. The researchers used a dataset with non-toxic and toxic molecules to train two models. The first model had high accuracy on the training and validation sets but lower on the test set. The second model had slightly lower accuracy overall but performed consistently across all sets. This shows that deep learning can help predict molecule toxicity, but balancing accuracy across different datasets is important.