Unverified50% confidenceOpinionExact time
Large language models show insight on cryptography problems often because they have encountered large amounts of public literature, code, and discussion during training, allowing them to quickly connect scattered clues.
1
Sources
50%
Confidence
Long-term
Relevance
10/18/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedLarge language models are trained on massive corpora that may already contain extensive mathematical literature, problem-solving processes, and even answers to similar problems.78% similarUnverifiedThe emergent capabilities of large language models are regarded by some researchers as signals of general intelligence, while others believe these capabilities may still represent efficient compression and retrieval of implicit patterns in training data.78% similarUnverifiedLarge language models possess powerful knowledge integration and reasoning capabilities that could be exploited by malicious actors to lower the barrier to accessing dangerous information.77% similarUnverifiedLarge language models can integrate scattered information from forums, tutorials, patents and engineering documents into step-by-step advice, and provide instant answers to questions through natural language interaction.77% similarUnverifiedMainstream large language models show significantly reduced accuracy when understanding obfuscated bundles with extremely long contexts (tens of thousands of lines) and may hallucinate on custom encryption variants.75% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1058977API
curl https://kongchang.com/api/v1/knowledge/claims/1058977MCP
get_claim(id=1058977)