SNNLab

Since July 28, the system has moved toward sharing pure multicore C++ SNNs across the Lab, browser learning, and natural chat. It now asks follow-up questions for unknown input, gives acknowledgments after teaching, observes session boundaries, and separates self-echo history from human-taught history. In live conversation, exact matches sometimes work after teaching, but unseen paraphrases and topic changes still produce silence or unrelated replay, so it has not been promoted to natural chat.

Since July 17, response generation has been rebuilt around multiple C++ SNN cores—topic, relationship, match, permission to speak, inhibition, and recall—rather than Python convenience. Reproduction of known cases and paraphrases of the same facts now works much more often, and wrong answers to strange questions have been greatly reduced. However, the ability to apply knowledge to genuinely different unseen questions remains weak, and unseen exact matches are still nearly zero.

Moved response binding to a multicore C++ design; known cases and silence improved, but unseen generalization is still weak