A Landn Research Proposal
Author: Alvin Adamtey Quashie
Organisation: Landn
Published: August 2026
Status: Open for academic engagement, citation, and collaborative research
Every computer ever built rests on the same foundation: the von Neumann architecture, a binary logic system in which all information is encoded as ones and zeros, processed sequentially, and stored in addressable memory. This architecture was designed in 1945 for electrical switches. It was not designed for human beings.
The result is a permanent translation problem. Humans must express their intentions in a language the machine understands, rather than the machine understanding the language the human already speaks. Eighty years of computing has been an attempt to bridge this gap without changing the foundation. GUIs, touchscreens, voice interfaces, and large language models have each narrowed the gap. None have closed it. None could, because the gap is not an interface problem. It is an architectural problem.
BRAIN proposes that the foundation should change.
BRAIN proposes four new hardware primitives to replace binary logic gates as the foundational unit of computation:
| Primitive | Definition |
|---|---|
| Intent | The expression of a desired outcome without specification of the mechanism |
| Navigation | The process of finding the most likely path from an expressed intent to an executable outcome |
| Context | The accumulated state of prior interactions that informs how an intent should be interpreted |
| Resolution | The selection of a specific action from a navigated set of possibilities |
A BRAIN processor does not ask: what is the binary state of this input?
It asks: what does this input intend, and what is the most navigable path to fulfilling it?
BRAIN is not a large language model. It is not a neural network. It is not an AI system layered on top of von Neumann hardware. It is an architectural proposal for the hardware layer itself.
Large language models operate at the software level on von Neumann hardware. They are extraordinarily capable translation machines. But they are still translating. The binary foundation remains. BRAIN proposes that the chain should not exist at the hardware level. The processor itself should operate on intent, navigate toward resolution, and maintain context as a hardware state.
Neuromorphic computing such as Intel Loihi and IBM TrueNorth moves in a related direction. BRAIN shares the spirit of this work but proposes a different primitive: not neural patterns, but intent and navigation. Quantum computing introduces superposition as a hardware primitive. BRAIN does not require quantum mechanics. It requires a rethinking of what a processor is designed to compute.
We publish this proposal not as a completed solution but as an invitation.
5.1 Physical substrate
What material or physical phenomenon could serve as the substrate for intent-native computation? Candidates include probabilistic computing substrates, biological or molecular computing, and photonic systems capable of representing continuous rather than discrete states.
5.2 Formal specification of intent
How is intent formally represented at the hardware level? Binary has a complete mathematical foundation in Boolean algebra. BRAIN requires an equivalent formal system.
5.3 Primitive instruction set
What is the equivalent instruction set for a BRAIN processor? How are intent, navigation, context, and resolution encoded as hardware instructions?
5.4 Interoperability
BRAIN does not propose the elimination of von Neumann architecture. It proposes an alternative. How do BRAIN and von Neumann systems communicate?
5.5 Energy model
Can BRAIN be implemented in a way that is competitive with binary systems on energy consumption?
The people who cannot use technology today are not failing because the interface is bad. They are failing because the gap still exists. A child in rural Ghana who cannot read cannot navigate a graphical interface. An elderly person unfamiliar with software conventions cannot use a touchscreen application without assistance.
BRAIN is built on the belief that the gap should not exist. That technology designed for human beings should begin with human beings, not with transistors.
This is not a small ambition. It is the right one.
The full BRAIN research paper is available at:
- Landn Research: landn.io/research/brain-base-reasoning-architecture-for-intelligent-navigation
- Academia.edu: academia.edu/172139325
- SSRN: submitted
- OSF: submitted
This is an open research proposal. We welcome:
- Academic citations and references
- Formal responses, counterarguments, and extensions
- Collaboration from researchers working on neuromorphic computing, probabilistic computing, photonic computing, or hardware architecture
- Questions, challenges, and discussion via GitHub Issues
We do not know what BRAIN looks like in silicon. We know why it should exist. And we know that the work of imagining it, specifying it, and eventually building it is the most important work in computing that nobody is currently doing.
We are starting it here.
Landn is a technology company founded in Accra, Ghana. We build operational intelligence infrastructure and conduct original research into the future of computing.
Website: landn.io
Research: landn.io/research
X: @landnhq
Published by Landn, Accra, Ghana. Written by Alvin Adamtey Quashie, Founder.
Open for academic engagement, citation, and collaborative research.
© 2026 Landn Intelligence Limited. All rights reserved.