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LLMs GPT-6 Sol and Opus 5.5 show promise in historical research, including alchemy and cryptography
Key points
- GPT-6 Sol and Opus 5.5 released this week.
- LLMs applied to historical problems like cryptography and text tracing.
- Models identified a Newton translation from a French alchemical text.
- Suggests collaboration between historians and AI labs.
- AI models perform best on 'tractable' problems with verifiable solutions.
New LLMs Applied to Historical Research
The recent releases of GPT-6 Sol and Opus 5.5 have enabled new applications of large language models (LLMs) in historical research. These models are being used to address existing historical problems, moving beyond basic research assistant functions like document transcription.
Solving Historical Puzzles
Early results indicate that these frontier models can tackle complex historical challenges. Examples include cryptographic tasks, such as decrypting historical communications, and tracing texts across different translations and adaptations. One instance involved identifying a passage Isaac Newton translated into Latin from a French alchemical text.
Criteria for AI-Tractable Problems
LLMs are most effective when applied to 'tractable' problems. These problems typically have identified needs, digitized and accessible data, align with AI capabilities like multilingual reasoning or autonomous research, and allow for clear verification or refutation of solutions. This last point is crucial for their success in fields like mathematics.
Potential for Collaboration
The observed capabilities suggest that collaborations between historians and current frontier models could lead to significant advancements in historical knowledge and interpretation. This potential was not as evident with previous AI models.
✨ This summary was generated by AI from the outlets' reporting listed below. It is not independently verified and may contain errors — check the original sources. How BrevFeed works →
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Primary sources
GitHub benjaminbreen/HumanitysFirstExamReporting from
New LLMs, GPT-6 Sol and Opus 5.5, are being used to solve historical problems beyond basic research assistance. These models demonstrate capabilities in areas like cryptography and tracing textual translations, potentially advancing historical knowledge.