Can an 8B Model Meet a 35B Model's Acceptance Bar? Introducing Artificial Deterministic Intelligence

Branden Laskowski — Sun, 11 Oct 2026 21:28:33 +0000

Artificial Deterministic Intelligence: Probabilistic Reasoning, Deterministic Authority

What if improving AI systems isn't always a question of building larger models, but of changing the architecture surrounding them?

I've published the first paper in a continuing research series exploring Artificial Deterministic Intelligence (ADI), an approach that separates probabilistic reasoning from externally enforced deterministic authority.

The research examines how memory admission, identity, permissions, execution rights, verification, and release can be governed independently of language-model inference.

The initial experimental evidence

In a first-party synthetic historical-memory study, we evaluated 30 task designs repeated three times per configuration.

Configuration	Accepted runs
8B model, scoped context	90/90
35B model, scoped context	90/90
4B model, scoped context	72/90
35B model, broader context	46/90

The broader-context 35B condition had 43 truncated responses under its fixed output budget.

On this bounded task family, the scoped 8B configuration satisfied the same recorded acceptance contract as the scoped 35B configuration.

This does not establish that smaller models are universally equivalent to larger models or prove a reduction in total hardware memory requirements.

It does raise an important engineering question:

How much operational responsibility can be moved from the inference model into a governed architecture while preserving required task performance?

Paper 1 — Published October 9, 2026

Artificial Deterministic Intelligence: Probabilistic Reasoning, Deterministic Authority

Read the published research preprint:

https://doi.org/10.5281/zenodo.23265200

The paper introduces the architectural framework, discusses first-party benchmark observations, identifies relevant prior work, and describes limitations requiring further investigation.

A Continuing Scientific Research Series

ADI is the foundation for a planned series of supporting publications, targeting one evidence-reviewed paper per week.

Upcoming research:

Externalized Intelligence and Model Substitution
Deterministic Worker Construction Before Inference
Governed Shared Memory for Multi-Agent Systems
Model-Independent Artificial Workers
Temporal and Authoritative AI Memory
Behavioral Governance of Artificial Workers
Governed Persistent Student Memory for Educational AI
Evidence-Calibrated Computational Persona
Persistent Artificial Identity Across Model Generations
Persistent Artificial Identity in Robotic Embodiment

Release timing depends on evidence review and disclosure approval.

Public Developer Challenge

We've also released the Cortex Governed Memory Challenge v0.1, with public synthetic specifications and behavioral fixtures for examining governed-memory behavior.

Challenge documentation:

https://github.com/brandenlaskowski7-bot/cortex-adi-research/tree/main/challenges/governed-memory

An Invitation to Engineers and Researchers

I'm interested in technical criticism, optimized comparison baselines, independent experimental designs, and alternative explanations for our findings.

The goal is to investigate whether explicitly governed AI architectures can support more accountable, efficient, and human-centered artificial intelligence.

Our findings are first-party observations, not independent replication or a general safety guarantee. Proprietary implementation details remain private.

Follow the complete research series:

https://github.com/brandenlaskowski7-bot/cortex-adi-research

Branden Laskowski

Cortex Agentics Global

Bridging Humanity and Technology.

Probabilistic Reasoning. Deterministic Authority.