Mining the Vatican Secret Archives with TensorFlow w/ Elena Nieddu - TWiML Talk #243
Analysis
This article highlights a project using machine learning, specifically TensorFlow, to transcribe and annotate documents from the Vatican Secret Archives. The project, "In Codice Ratio," faces challenges like the high cost of data annotation due to the vastness and handwritten nature of the archive. The article's focus is on the application of AI in historical document analysis, showcasing the potential of machine learning to unlock and make accessible significant historical resources. The interview with Elena Nieddu provides insights into the project's goals and the hurdles encountered.
Key Takeaways
- •The project utilizes machine learning (TensorFlow) for historical document analysis.
- •The primary goal is to transcribe and annotate the Vatican Secret Archives.
- •A key challenge is the high cost associated with annotating handwritten documents.
“The article doesn't contain a direct quote, but it mentions the project "In Codice Ratio" aims to annotate and transcribe Vatican secret archive documents via machine learning.”