A new study from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) demonstrates a method for training AI models to generate more realistic and coherent long-form text. The research focuses on improving the narrative flow and factual consistency of AI-generated stories and articles over extended passages. The team developed a technique called ‘progressive learning,’ where the model is trained to focus on maintaining context and logical connections between sentences and paragraphs, rather than just predicting the next word. Initial evaluations show the approach reduces contradictory statements and irrelevant tangents in generated text. The researchers suggest this could lead to more reliable AI assistants for drafting reports, creating educational content, and other applications requiring sustained coherence. Read the full article for detailed methodology and results.