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// 52d agoOPENSOURCE RELEASE
GPT-1900 intuits modern physics from pre-1900 data
Michael Hla's 3.3B parameter LLM was trained exclusively on text published before 1900 to test "out-of-distribution" reasoning and scientific discovery. The model showed provocative glimpses of intuition, suggesting light consists of discrete energy packets and the local equivalence of gravity and acceleration when prompted with period-contradictory observations.
// ANALYSIS
A fascinating experiment in "scientific time travel" that challenges current assumptions about LLM reasoning versus data memorization.
- –Aggressive decontamination (22B tokens filtered for "future leaks") represents the project's most significant technical hurdle and achievement.
- –While exhibiting "glimpses" of intuition, the model remains a small-scale prototype prone to period-appropriate "bullshitting" using 19th-century prose.
- –The results suggest LLMs can synthesize breakthroughs from contradictory data, though they remain heavily tethered to historical biases.
- –Open-sourcing the dataset and weights provides a unique benchmark for testing "true" reasoning in larger, modern models.
// TAGS
llmreasoningopen-sourcephysicsmachina-mirabilis
DISCOVERED
52d ago
2026-04-05
PUBLISHED
52d ago
2026-04-05
RELEVANCE
8/ 10
AUTHOR
Primary-Track8298