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From books and paintings to movies and musical theatre, artists have often drawn on the stories of the Bible for inspiration. Now, social media users are putting a distinctly modern twist on this trend by using AI to imagine biblical characters as influencers. In these videos, characters such as Adam and Eve, Samson, and David appear to'vlog' their way through the events of the Bible. In one viral video posted to X, a smiling Jesus declares from the cross: 'Yo fam, they don't know that G-O-D is about to BRB.' In another clip, an AI-generated character says: 'Your boy David here. About to yeet this little stone at Goliath and see what happens.' These short AI-generated clips have proven to be wildly popular online, with one TikTok account named theaibibleofficial racking up 26.7 million likes.

Uncovering evidence for historical theories and identifying patterns in past events has long been hindered by the labor-intensive process of inputting data from artifacts and handwritten records. Normally, epigraphers – scholars who study ancient texts written on durable materials such as stone, metal, or pottery – use their knowledge of repositories of information and digital databases to perform "string matching" searches to find textual and contextual parallels. However, differences in the digital-search query that can exclude or conceal relevant results and that the texts often are discovered not in their original context can complicate the work. Starting from Adam and Eve to the Greek gods there is so much to discover and researchers are using advanced technologies like Artificial Intelligence and Machine learning to get more accurate results. Most scientific research to date has focused on whether Adam and Eve could have passed on genetic material to everyone living; however, this doesn't seem to be the type of ancestry the Bible is concerned with.

In the year 2007, Adam and Eve discovered something that takes many years for others to discover. Eve researched an element named triclosan, a common component of toothpaste, and discovered that it is efficient in combating malaria-based parasites! Eve's friend Adam, researched the functions of yeast and turned over billions of data points available in the public databases to understand and predict the functioning of 19 genes of yeast. In the process, Adam discovered 9 new and accurate hypotheses. All this is done within an unbelievable time frame and with the highest precision and accuracy.

In the early 2000s, Mike Sellers was working on social AI agents for DARPA. During one simulation, two AI agents named Adam and Eve were given a few basic skills. They knew how to eat, but not what to eat. When they tried to eat apples from a tree, they felt happy. When they tried to eat wood from the same tree they didn't get any reward.

This story was told to us by Mike Sellers, who was working on some social AI for DARPA in the early 2000s. They were making agents that learned to interact socially together. "For one simulation, we had two agents, naturally enough named Adam and Eve. They started out knowing how to do things, but not knowing much else. They knew how to eat for example, but not what to eat. We'd given them an apple tree (the symbolism of that honestly didn't occur to us at the time), and they found that eating the apples made them happy. They had also tried eating the tree, the house, etc., but none of those worked. There was also another agent named Stan, who wanted to be social but wasn't very good at it, so was often hanging around and kind of lonely. "And of course, there were a few bugs in the system.