AI Cataloging for Holocaust Archives
Three-layer confidence framework for cataloging Holocaust-era photographs with AI: visual, objects, persons — explicit ✓ ~ ? markers and when to defer.
Read Article →Updates from the intersection of history and artificial intelligence.
Three-layer confidence framework for cataloging Holocaust-era photographs with AI: visual, objects, persons — explicit ✓ ~ ? markers and when to defer.
Read Article →End-to-end guide to OCR and HTR for historical Hebrew, Yiddish, Ladino: engines that work, how to fine-tune, accuracy targets, and mistakes that kill projects.
Read Article →Plain-language glossary for AI-assisted historical research: OCR, HTR, RAG, embeddings, knowledge graphs, NER, pinkasim, yizkor books, and 25 more terms.
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Some years change everything. We built a structured database that consolidated dozens of source types — press, diplomacy, diaries, minutes — from one decisive year into a searchable, analyzable knowledge base.
Read Article →When personal memoirs need to become a proper scholarly edition. How combining archival research with AI turned a hundreds-of-pages manuscript into an academic book with hundreds of footnotes — in months instead of years.
Read Article →A real-world case study: how we used OCR and AI research agents to transform thousands of pages of historical newspapers into a searchable database — and uncovered forgotten quotes from key figures in early 20th century history.
Read Article →A life-story mapping project: how we used LLMs and research agents to turn dozens of family memoirs into a unified historical narrative, verify facts, and reveal hidden connections between different voices.
Read Article →A real case study in historical discovery: reconstructing the details of an event that was nearly erased from the record. How AI research agents working in parallel across dozens of sources surface information that human researchers had given up on.
Read Article →How artificial intelligence is helping researchers uncover, cross-reference, and preserve Holocaust testimonies and documents at unprecedented scale.
Read Article →Traditional OCR cannot read handwritten documents. Modern HTR technology, powered by deep learning, is finally making centuries of handwritten records searchable.
Read Article →How AI is transforming archival work — from scanning images to extracting meaning. Three layers of an AI-native archive, with a concrete example.
Read Article →Autonomous AI research agents can now conduct preliminary historical research across multiple archives simultaneously. Here's how they're changing academic work.
Read Article →Isolated documents tell fragments of stories. Knowledge graphs connect them into networks of people, places, and events — revealing patterns invisible to traditional research.
Read Article →Retrieval Augmented Generation (RAG) lets researchers ask natural language questions across thousands of historical documents and receive accurate, source-cited answers.
Read Article →Museums, archives, and libraries face an urgent race against time. AI-powered digital preservation offers new tools to protect cultural heritage for future generations.
Read Article →Discover how artificial intelligence is revolutionizing family history research, from deciphering old letters to connecting scattered records across continents.
Read Article →Historical Hebrew manuscripts present unique OCR challenges - right-to-left text, diverse scripts, and centuries of wear. Learn how AI is solving these problems.
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