Michael
Andregg

I build the tools we need to understand and recreate intelligence. Somewhere in the last few years, emulating a mind stopped being science fiction and became an engineering problem.

I co-founded Eon, a public benefit corporation building reliable, scalable, and provably human emulation of intelligence from neurobiological detail — and aiming to make it a real option for humanity within the decade.

I believe this is a safer path than de novo AGI — whether the risk comes from bugs or bad actors — and one of the few that lets humanity actually participate in a world with superintelligence. Mapping the architecture of the human brain also makes AI more robust and more human, and along the way helps us understand the brain itself, including how to cure its diseases.

• 3deep-tech companies co-founded
• 15+ yrsbuilding the instruments this problem needs
• 1continuous problem: measure the brain, then run it

1. 01

   Eon Co-founder & CEO · now

   Provable whole-brain emulation from neurobiological detail. eon.systems

2. 02

   Atomos Co-founder · now advising

   Strategy, recruiting, fundraising, and building optical computers and massively parallel optical networking. I explored alternative computing — superconducting single-flux-quantum logic — and did hands-on Si and Nb microfabrication. My brother now runs it with a cracked team of electronics, optical engineers and physicists, focused on humanoid robotics. atomos.systems

3. 03

   Halcyon Molecular Co-founder

   Built the world's smallest electron microscope — high-speed and mass-producible, aimed at dramatically faster, cheaper DNA sequencing. The technology spun out as Voxa, which now sells these microscopes worldwide; one is aboard the International Space Station.

Emulating a brain has been out of reach mainly for one reason: the instruments to measure structure at the necessary scale and speed didn't exist. I've spent my career building exactly those kinds of instruments.

Electron microscopy taught me how to image matter at the smallest scales, mass-produced. Optical computing and massively parallel networking taught me how to move and process the resulting data at scale. Eon sits directly downstream of both. The arc that looks eccentric from the outside — microscopes, then optical computers, then brain emulation — is, from the inside, one continuous problem: measure the brain's architecture completely, then run it.

the future of life whole-brain emulation connectomics AI safety machine intelligence longtermism global priorities research transhumanism unconventional computing organ preservation self-identity population ethics kaizen archiving productivity

I'm working on an equation to help prioritize causes, and I'd like to see more experiments testing the simulation hypothesis.

I'm always glad to meet exceptional people in optical machine learning, data pipelines, image processing, and computational neuroscience — builders, systems engineers, and researchers.

Or just send me a note below. Anything at all — a question, an idea, a hello. No subject lines, no formalities; a sentence is plenty.

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