The American Revolution created a lasting democracy while the French Revolution became blood-soaked tyranny. But today's armchair revolutionaries echo similar calls.

Breakthroughs, discoveries, and DIY tips sent every weekday. It's hard to contain misinformation once enough people believe it. A conspiracy theory spreads exponentially regardless of its accuracy, making it that much more likely to translate into real violence. According to a study published August 27 in the journal Nature, these situations can (and should) be geographically mapped with the same models that epidemiologists use to track diseases. And as an example, researchers turned to one of history's most famous moments of misinformation. The Great Fear of 1789 was a major chapter in the French Revolution and a defining moment in modern history.

The rapid proliferation of information in the digital era underscores the importance of accurate historical representation and interpretation. While artificial intelligence has shown promise in various fields, its potential for historical fact-checking and gap-filling remains largely untapped. This study evaluates the performance of three large language models LLMs GPT 3.5, GPT 4, and GoogleBARD in the context of predicting and verifying historical events based on given data. A novel metric, Distance to Reality (DTR), is introduced to assess the models' outputs against established historical facts. The results reveal a substantial potential for AI in historical studies, with GPT 4 demonstrating superior performance. This paper underscores the need for further research into AI's role in enriching our understanding of the past and bridging historical knowledge gaps.

Being a voracious reader is a prerequisite for academics in the humanities, but even the most dedicated bookworm needs to eat, sleep, and socialize. Not so for computers, which are known for being tireless, thorough, and very fast. And, when asked the right kinds of questions, these electronic speed-readers can grasp patterns that would otherwise lie beyond the reach of human scholars. That's exactly what happened when a team of researchers used machine-learning techniques to plow through transcripts of 40,000 speeches in a parliamentary assembly during the first two years of the French Revolution, according to a paper published in the Proceedings of the National Academy of Sciences last month. By quantifying the novelty of speech patterns and the extent to which those patterns were copied by subsequent speakers, the researchers illustrated how much of the important intellectual work of the revolution was initially carried out in committees, rather than in the whole assembly.

The French Revolution was one of the most important political transformations in history. Even today, more than 200 years later, it's held up as a model of democratic nation-building. But for years, historians and political scientists have wondered just how the democratic trailblazers of the French Revolution managed to pull off the creation of an entirely new kind of governance. New research from an interdisciplinary collaboration among historians, political scientists, and statisticians suggest that rhetorical innovations may have played a significant role in winning acceptance for the new principles of governance that built the French republic's foundation -- and inspired future democracies around the world. The study, published today in PNAS, used machine learning techniques to comb through transcripts of 40,000 speeches from the deliberations of the makeshift assembly formed during the revolution's early days to hash out the laws and institutions of the new government.