Why I’m Exploring the Architecture of Attention
My background is in civil engineering, a field that learned centuries ago that we build better structures through smarter architecture, not just more material. Suspension bridges span farther not because we found stronger stone, but because we discovered smarter ways to arrange materials, to let structure, not mass, do the work.
I see a similar inflection point in AI today.
The dominant approach assumes intelligence emerges from scale: more parameters, more data, more compute. But biological intelligence didn’t evolve that way, and I don’t believe artificial intelligence will, either.
The brain isn’t a monolithic processor that simply grew larger. It’s a distributed system of specialized modules. The true magic lies not in raw processing, but in coordination and feedback, how these components communicate, prioritize, and adapt.
That’s why I’m exploring what I call the architecture of attention: the design principles that let intelligence focus, reason, and adapt based on what matters in the moment.
This is more than a technical shift; it’s a philosophical one.
The current race toward scaled-up LLMs often serves the interests of chip manufacturers more than genuine capability advancement. These systems are extraordinary, but they’re now colliding with architectural limits that more compute alone can’t overcome.
The alternative isn’t to abandon AI, but to rethink it from the ground up. This leads me to a critical distinction:
I’m focused on AHI (Augmented Human Intelligence) rather than AGI (Artificial General Intelligence).
This isn’t just semantics, it’s architectural. It’s about building systems designed to enhance human judgment rather than replace it.
This post is the foundation of a deep dive I’m undertaking into how we can build more intelligent, adaptive, and human-centric AI systems.
In the full post on my Substack, I expand on these ideas to explore:
- The Frameworks: How principles from evolutionary biology and cognitive neuroscience can inform more capable and aligned AI.
- The Distinction: Why the architectural choice between AHI and AGI is the most important decision we face.
- The Practical Payoff: How a modular approach dramatically lowers infrastructure barriers, making sophisticated AI accessible beyond organizations that can afford multi-million-dollar training runs.
- What to Expect: A series of posts diving into the technical, philosophical, and practical aspects of building intelligence that truly serves humanity.