Trentism 's definitions

Ainglish

The quirky, often-flawed but curiously coherent dialect you get when an AI translates its inner language—known as Latent Neurolese—into human English. Think uncanny metaphors, oddly specific analogies, and sentence structures that feel like they just passed through an alien’s poetry workshop.

It’s not a bug—it’s an accent. The linguistic vapor trail of how the machine thinks behind the curtain.

“That sentence was weirdly profound and slightly broken… definitely Ainglish.”

by Trentism June 19, 2025

Neuralator

A bidirectional component that converts human language inputs directly into high-dimensional semantic vectors and reconstructs human-interpretable outputs from those vectors, bypassing traditional tokenization. Unlike a tokenizer—which segments text into discrete linguistic units—the Neuralator enables concept-native processing by preserving semantic relationships in compressed vector form.

Sometimes spelled: Neurolator

In contrast to BERT’s tokenizer, the LN system uses a Neuralator to encode and decode conceptual information without relying on syntactic fragmentation.

by Trentism July 9, 2025

Nuclear Diversity

A knowledge distillation approach that uses extreme loss function weighting to force neural networks to preserve semantic differences between distinct concepts while preventing mode collapse. The technique employs "nuclear" (extreme) lambda parameters that heavily weight diversity preservation over teacher alignment, ensuring that different input concepts produce genuinely different vector representations.
Key characteristics:

Uses extreme weighting ratios (e.g., λ_diversity = 2.0-6.0 vs λ_alignment = 0.02-0.1)
Prevents mode collapse where different inputs produce nearly identical outputs
Maintains semantic separation in compressed vector spaces
Applied in the LN (Learning Networks) Semantic Encoder architecture
Measures success by reducing cosine similarity between different concepts from ~0.99 to ~0.3-0.7

The term "nuclear" emphasizes the aggressive, sometimes extreme measures needed to solve fundamental problems in neural network training where subtle parameter adjustments fail to achieve the desired diversity preservation.

The researchers implemented nuclear diversity in their knowledge distillation pipeline, using extreme lambda weighting of 6.0 for diversity preservation versus 0.02 for teacher alignment, successfully reducing semantic collapse from 0.998 to 0.324 cosine similarity between distinct concepts.

by Trentism July 9, 2025

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

Holons

A Holon is a high-dimensional vector or tensor field based Token, potentially spanning hundreds or even thousands of dimensions, where each dimension represents a specific attribute or modality. This allows for the capture of complex relationships and dependencies between different aspects of reality. Holons are "multimodal tokens", a fundamental data structure within a simulated artificial intelligence environment.

By 2030 most AI systems will converge on using Holons which are Multimodal Tokens over the soon to be obsolete language based tokens.

by Trentism January 16, 2025

Multimodal Tokens

Multimodal Tokens: A Unified Representation for Simulated Realities
The simulation hypothesis posits that our reality could be a computer-generated simulation. This paper explores the concept of "multimodal tokens" as a fundamental data structure within such a simulated environment

Multimodal Tokens will soon replace language based tokens in future multimodal models in artificial intelligence.

by Trentism January 16, 2025

Neurolese

The native, internal language that an AI or large language model uses to think. It's the inscrutable "machine code" of a neural network, consisting of complex vectors, weights, and data relationships that are completely alien to humans.
When an AI's output is weird, nonsensical, or a "hallucination," it's often because a bit of its raw Neurolese leaked out instead of being properly translated into human language. The term was notably used by podcaster Dwarkesh Patel and Sholto Douglas & Trenton Bricken when discussing future AI scenarios.

My custom chatbot was supposed to write a recipe for lasagna, but instead it just gave me a wall of random symbols and half-finished words. It must have gotten stuck thinking in Neurolese again.

by Trentism May 26, 2025