Ways To Work With Me
Funded R&D: define the mechanism, build the first runnable artifact, expose the measurements, and separate the physical limit from the tooling problem.
Product and systems architecture: design the boundary between software, hardware, data, tests, deployment, and user-visible behavior so the system can change without becoming opaque.
Prototype implementation: turn a claim, circuit, renderer, FPGA fabric, signal path, or model run into a concrete artifact with source, reproduction steps, and a visible operating envelope.
Collaboration and institutional support: the larger Cartilage and active-device work needs fabrication access, lab discipline, funding, and partners who can help turn public mechanisms into stronger machines. The current Cartilage Core proof page and public source repository show the concrete starting point.
Technical review: useful when the first question is whether a claim, architecture, process boundary, or public evidence page holds up under engineering pressure.
What To Send First
The fastest useful message names the artifact, the boundary, and the opportunity shape.
Send a page, repo, diagram, paper draft, trace, screenshot, demo, measurement, prototype, process idea, or system failure. Then say whether you are asking about funded work, product architecture, a prototype, a collaboration, fabrication access, a role, investment, or a technical review.
I do not need polished pitch material. I need the strongest claim, the part that has to hold up, and what kind of work could happen next if the boundary is real.
Research Areas Behind The Work
Software systems: live data, durable state, user preferences, upgrades, migrations, production fixes, end-to-end tests, and page-shaped backend state.
Remote and parallel computation: NATs, real networks, control paths, worker boundaries, locality, causality, and failure behavior.
FPGA and reconfigurable computing: multiplexer fabrics, edge-visible runs, browser artifacts, and spatial computation models.
Semiconductor and active-device R&D: maker-scale fabrication boundaries, wafer-diced chiplets, OECTs, magnetic alternatives, packaging, and trust surfaces.
Machine learning: bounded Transformer training artifacts, local learning machinery, and technical notes that keep model shape, source, run, and result together.
Radio and RF front ends: stack-stripping experiments such as one-pin FPGA radio, sampling, mixing, filtering, demodulation, and audio output.
Contact
Email brian@solidstatepros.com.
Legal entity: Solid State Pros LLC.