Updates from the intersection of history and artificial intelligence.
A domain lexicon turns OCR guessing into informed decisions — how to build one that boosts Hebrew handwriting recognition, and when it backfires.
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An accuracy number without calibration is a bluff. How confidence scoring and the right threshold lifted Hebrew handwriting OCR from 56% to 90% precision.
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Three-layer confidence framework for cataloging Holocaust-era photographs with AI: visual, objects, persons — explicit ✓ ~ ? markers and when to defer.
Read Article →Which engine wins on historical Hebrew documents — rabbinical script, Rashi, Yiddish, Ladino? Real accuracy benchmarks, the fine-tuning workflow, and the mistakes to avoid.
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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A structured database consolidating dozens of source types — press, diplomacy, diaries, minutes — from one decisive year into a searchable knowledge base.
Read Article →How archival research combined with AI turned a hundreds-of-pages memoir into a scholarly edition with hundreds of footnotes — in months, not years.
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How we used OCR and AI agents to turn thousands of pages of historical newspapers into a searchable database — and surfaced long-forgotten quotes.
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How we used LLMs and research agents to turn dozens of family memoirs into a unified historical narrative — verifying facts and revealing hidden links.
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How AI research agents working in parallel across dozens of sources reconstructed a historical event nearly erased from the record — a case study.
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How artificial intelligence is helping researchers uncover, cross-reference, and preserve Holocaust testimonies and documents at unprecedented scale.
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Traditional OCR cannot read handwritten documents. Modern HTR technology, powered by deep learning, is finally making centuries of handwritten records searchable.
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How AI is transforming archival work — from passive image scans to extracting meaning. Three layers of an AI-native archive, with a concrete worked example.
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Autonomous AI research agents can now conduct preliminary historical research across multiple archives simultaneously. Here's how they're changing academic work.
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Knowledge graphs connect isolated documents into networks of people, places and events — revealing patterns invisible to traditional research.
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How researchers query thousands of historical documents in plain English — with source-cited answers. Setup, costs, and where RAG still fails.
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Museums, archives, and libraries face an urgent race against time. AI-powered digital preservation offers new tools to protect cultural heritage for future generations.
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Discover how artificial intelligence is revolutionizing family history research, from deciphering old letters to connecting scattered records across continents.
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Off-the-shelf OCR fails on historical Hebrew. Here's the AI workflow archivists use to recover RTL manuscripts, Rashi script and worn pages.
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