About
Hi. I'm Alex Nugent, inventor, co-founder, and CEO of Knowm Inc. I started building physical neural networks in 2002, before I — or most of the world — knew the word memristor, and I've spent most of my adult life on the problem of memristor machine intelligence.
The first patents — and KnowmTech LLC, the company we formed to hold them — came out of that early undergraduate work. I carried those ideas into a year at Los Alamos National Laboratory, where they turned into plasticity rules that could repair a neural network while it kept running: AHaH plasticity. That led me to DARPA, where I helped get SyNAPSE — Systems of Neuromorphic Adaptive Plastic Scalable Electronics — off the ground and spent four years as a science and engineering advisor on it, watching HP, IBM, and HRL throw serious money at neuromorphic hardware, then advised the Physical Intelligence program that grew out of it. Afterward I won SBIR and STTR research contracts from the Air Force Research Laboratory and the Office of Naval Research, published the AHaH Computing theory in PLOS One in 2014, and licensed the self-directed-channel memristor Knowm still ships today. The longer version is Chapter 2.
Knowm has been early for a long time. In 2002, machine learning couldn't reliably tell a dog from a cat and Intel had just shipped its first dual-core chip. Memristor synaptic accelerators sounded like a solution in search of a problem, and they were. That has changed. Models now cost more to train than a custom chip costs to build, inference demand is exploding, and the energy wall has been hit. The question is whether we keep hauling learned weights through memory hierarchies forever, or build hardware that holds adaptive physical state where the computation actually happens.
Knowm became the first company — and as far as I know still the only one — commercially providing memristors to researchers, educators, and students around the world. Those devices catalyzed the largest body of independent academic work of any commercial memristor: as of May 2026, a Google Scholar search for "Knowm memristor" returns roughly 589 papers and citations across chaotic circuits, memristor logic, neuromorphic signal processing, reservoir computing, threshold logic, and more. I personally packaged and shipped every single chip. They left the slide deck, hit real labs, and got tested, abused, modeled, and built into things I never would have thought to build myself.
The remaining supply of Knowm SDC memristors is finite, and the path from research device to broad manufacturing needs resources far beyond what a small company in Santa Fe can carry.
Knowm's IP is for sale. I want it to find a home with an organization that can carry it faster and farther than I can — people who can span the stack from materials and fabrication to architecture, ML systems, and product. I'm not raising money and I'm not looking for direct investment. I want a buyer for the technology, not another round of the VC-and-government funding hustle I've mostly lost patience for.
Until the right home appears, I'm developing in the open, one article at a time. knowm.ai is the untold story of Knowm — the theory, the patents, the lab results, the fab, the politics, the breakthroughs I've kept private since our 2014 PLOS One paper on AHaH Computing, and a few stories I've never told.
I'm going to build the thing I came here to build: a neural processor that assimilates neural networks into a thermodynamic synapse substrate — memory, adaptation, and computation collapsed into the same physical material. Subscribe to follow along. New articles drop as I write them, and I'll spec and build in public.
If you want a polished corporate narrative and the stamp of name-brand approval, you'll hate this. If you suspect the next phase of AI needs a different relationship between memory, computation, and physical adaptation — and you can still read and think for yourself — you're in the right place.
The short version: I'm going to build the damn thing and tell you how I got here. I hope you follow along.
Blue Skies,
Alex