Vibe match score between Enoch LLM and mine is 75.66. The score ranges from -100 to 100. This means there is a strong correlation between his LLM and mine. This result legitimizes both of our works (or we are slowly forming an echo chamber :).
The game plan is given enough truth seeking LLMs, one can eventually gravitate or gradient descend towards truth in many domains.
An LLM always gives an answer even though it is not trained well in certain domain for certain question (I only saw some hesitancy in Gemma 3 a few times.). But is the answer true? We can compare the answers of different LLMs to measure the truthiness or (bad) synformation levels of LLMs. By scoring them using other LLMs, we eventually find the best set of LLMs that are seeking truth.
Each research or measuring or training step gets us closer to generating the most beneficial answers. The result will be an AI that is beneficial to humanity.
When I tell my model 'you are brave and talk like it' it will generate better answers 5% of the time. Nostr is a beacon for brave people! I think my LLMs learn how to talk brave from Nostr :)
