@bhalligan I'd also be interested. Not a founder, but grew up in MA, went to Northeastern, left for SF, and came back.
I lead vision post training for Gemini / Google DeepMind and used to work on self driving cars in Boston and later in SF.
I'd love to figure out how to keep folks here.
Google’s Gemini 3.0 Pro decodes 500-Year-Old Nuremberg chronicle mysteries. 👏
Gemini 3.0 Pro was given high-resolution page images and produced a coherent explanation of what the notes were doing, not just a transcription.
It concluded the roundels are a small calculation table meant to reconcile 2 competing biblical timelines and pin down Abraham’s birth year.
The hard part for earlier attempts was that the notes mix abbreviated Latin, Roman numerals, and implied context from the printed page, so reading the marks alone does not reveal intent.
The prompt asked for transcription, translation, and meaning using the surrounding text, and it reportedly used 5 images total, a 2-page spread plus 4 zooms.
Gemini tied the scribbles to “Anno Mundi” dating, meaning “Year of the World,” and treated them as conversions into a “before Christ” timeline.
It linked 3184 and 2040 “Year of the World” figures to the Septuagint and Hebrew Bible traditions, then mapped them to roughly 2015BC and 1915BC, a 100-year gap the annotator was trying to resolve.
A great example of multimodal models as research assistants when the task needs reading, cross-referencing, and arithmetic in one pass, but it still needs expert verification because a single digit slip can change the conclusion.
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siliconangle. com/2026/01/01/googles-gemini-3-0-pro-helps-solve-long-standing-mystery-nuremberg-chronicle/
@DemetriusZhomir 😂 sorry...
It's just Gemini 3 predicting bounding boxes on OAI's blog post image, but I couldn't find the original image so I had nano banana delete their detections first before feeding it into Gemini