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AI Intelligence Architecture — A Research Series

Neural network abstract

Stabilarity Research Hub · Ongoing Series

AI Intelligence Architecture

An ongoing investigation into what AI really is — versus what we are building

Every major AI system built today shares a hidden architectural assumption: that intelligence should look, think, and plan like a human. This series systematically questions that assumption — not to dismiss what we’ve built, but to understand what we might be giving up by defaulting to the mirror.

From the anthropomorphic bias baked into training data, to the human planning frameworks imposed on AI agents, this series traces how our own cognitive architecture shapes — and potentially limits — what we build. Each installment stands alone but builds toward a larger argument about the civilizational choices embedded in our design decisions.

Published Articles


01

Part One · March 2026

AI is not like us?

The civilizational fork between anthropomorphic AI and the alien brain we could build instead. We systematically build AI in front of mirrors — shaped by human training data, human feedback, human interfaces. This essay asks: what are we giving up by choosing resemblance over capability? And is that choice being made consciously at all?

DOI: 10.5281/zenodo.18824472

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Discussion Card

02

Part Two · March 2026

The Planning Illusion

We’re teaching AI to plan like humans — and that might be the most expensive mistake in AI history. ReAct, Chain-of-Thought, Plan-and-Execute: every dominant agent framework mirrors human deliberate problem-solving. But AI doesn’t share our memory limits, our sequential processing constraints, or our cognitive bottlenecks. What looks like a feature is actually an unnecessary cage.

DOI: 10.5281/zenodo.18824558

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Coming Next

Upcoming in the Series

The investigation continues. Future installments will examine deeper layers of the anthropomorphic AI question.

Part 3 · The Evaluation Trap: Why Our AI Benchmarks Measure the Wrong Thing

How MMLU, HumanEval, and standard benchmarks encode human cognitive assumptions — and what non-anthropomorphic evaluation would actually look like.

Part 4 · The Memory Problem: Sequential vs. Structural Cognition

Human memory is episodic, lossy, sequential. AI memory doesn’t have to be. Why we keep building RAG systems that mirror human forgetting instead of architectural alternatives that exploit AI’s actual memory capabilities.

Part 5 · The Alignment Paradox: Whose Values Should Non-Human AI Optimize For?

If we successfully build an AI that doesn’t think like us, the alignment problem transforms. This article examines what alignment means for a genuinely alien intelligence.

About This Series

Written by Oleh Ivchenko, Innovation Tech Lead and ML researcher. All articles are peer-reviewed, DOI-registered on Zenodo, and freely available under open access.

Cite This Work

Ivchenko, O. (2026). AI Intelligence Architecture — A Research Series. Stabilarity Research Hub. Available at: https://hub.stabilarity.com

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