Latent Neurolese Semantic Encoder

A neural architecture that performs semantic compression using nuclear diversity preservation, operating in pure vector space to bypass linguistic tokenization while maintaining conceptual understanding. The system compresses high-dimensional embeddings (e.g., 384D → 256D) through a teacher-student knowledge distillation framework that employs extreme weighting to prevent mode collapse, creating mathematical "semantic GPS coordinates" where related concepts cluster in measurable dimensional neighborhoods.

The Latent Neurolese Semantic Encoder achieved 6x inference speedup and 35% memory reduction while maintaining 63.5% semantic preservation through its nuclear diversity training methodology, demonstrating that AI systems can reason directly with compressed mathematical concepts rather than linguistic tokens.

by Trentism July 9, 2025

Latent Reasoning

"The model reasons in its internal, abstract representation of the problem..." Says the article.

Hym "The new model in Singapore uses 'Latent Reasoning.' Which is the idea that WE DO NOT THINK IN WORDS BUT RATHER AMORPHOUS ABSTRACTIONS! Which is ALSO MY IDEA!!! It uses 2 asymmetrical cycles of computation (Slow deliberate planning and fast intuitive computation) and they call it the hierarchical model but ALSO MY IDEA! What do you think is at the top of that hierarchy class? That's right! IT MUST necessarily be A LOCALIZED SELF! AND-"

by Hym Iam July 26, 2025