Imagine having a crystal ball that could predict global events, political upheavals, or even economic shifts. While true clairvoyance remains elusive, researchers are exploring the potential of Large Language Models (LLMs) to forecast events based on historical data, raising the question – can AI actually predict the future? A new study delves into this fascinating area of temporal event forecasting, evaluating how LLMs can analyze past events and project potential future outcomes. Traditional methods often represent events as structured data points in a timeline, missing the rich context embedded in human language. This research explores how LLMs process not only structured event data, but also unstructured textual information extracted from news articles, to potentially generate more nuanced predictions. Researchers experimented with different approaches, including "rule-based history" – feeding the LLM carefully selected past events based on predefined rules, and "retrieved history" – where the LLM actively searches for relevant past events in a vast dataset. Interestingly, simply throwing raw text at the LLMs didn't improve prediction accuracy in initial tests. However, fine-tuning the models with specific instructions and integrating relevant text snippets showed significant improvement, suggesting LLMs can indeed learn complex patterns and relationships from text that enhance their predictive abilities. One of the most intriguing findings was related to "popularity bias." LLMs seem less susceptible to this bias, meaning they are better at predicting less frequent or "long-tail" events compared to traditional methods, which often prioritize frequent, well-documented occurrences. The study concludes that task-specific training and smarter ways of retrieving relevant historical data will be critical for advancing LLM-based event forecasting. While still in its early stages, this research opens exciting avenues for leveraging AI to better anticipate future events. Imagine the implications for political analysis, economic planning, and even disaster preparedness – a future where AI can provide not just hindsight, but also foresight, offering valuable insights into the potential unfolding of events.