We're seeking computationally de‑risked inventions that can be patented and licensed across NMK Capital's innovation challenge and the 10 focus areas we discussed:
1. Telecom / RAN & Core
2. Satellite / Ground Segment
3. IoT / Edge / Embedded
4. Semiconductors / EDA / Packaging
5. Energy Storage / Batteries
6. Electric Power / Grid Operations
7. Robotics / Autonomy / Facilities (Open‑RMF/ROS)
8. CFD / Thermofluids / Aero
9. Materials & Chemistry (non‑biomedical)
10. Quantum / SDR / Physics
We're looking for systems, methods, devices, compositions, processes, and diagnostics/monitoring inventions that can be proven computationally, replicated from your repo/zip, and claimed cleanly—analogous to the way you'd build and validate an AI‑scientist project, but outside life sciences. Examples include:
Control and orchestration methods (e.g., RIC xApps/rApps, grid controllers, multi‑robot facility orchestration, flight autonomy supervisors).
Design flows & tool‑calling agents (EDA flows, packaging/assembly planning, CFD/thermal topology optimization, grid planning toolchains).
Compositions & materials/structures (battery electrodes/electrolytes/interlayers, surface treatments/coatings, composites, metamaterials), where the performance uplift can be demonstrated in simulation/digital twins.
Form‑factor, deployment‑route & device innovations (edge vs. cloud split, packaging/thermal designs, radio front‑end/antenna structures, device‑level integration).
Combination systems with measured "synergy" (coordinated controllers/waveforms/schedules/policies that beat baselines beyond additive effects).
Sensor‑/telemetry‑guided methods of use (thresholds/decision rules for safe performance or efficiency).
Diagnostics/monitoring/imaging for selection, operations, or predictive maintenance (e.g., grid state estimation, link‑quality prediction, thermal early‑warning, structural health monitoring).
We prioritize inventions that:
Show a clear performance edge (efficiency, safety, reliability, latency/throughput, cost, convenience) and a path to real‑world adoption.
Demonstrate novelty with an explicit prior‑art map and a draft claim (see "IP & Claiming" in the form).
Are replicable from your repo/zip (data inventory, prompts chain, environment files, commands).
Include a human‑contribution log (who conceived what; how AI was used; why a human is an inventor).
Note: Stay at an in‑silico level here—no lab/factory build instructions. We evaluate computation + rationale + claimability.
Deployment & integration upgrades: cloud→edge splits; packaging/thermal routes that deliver SLA‑stable latency or energy savings under realistic loads; standardized device/stack integration methods.
Service‑life / reliability engineering: controller/design variants that measurably extend asset life or reduce variance (e.g., grid components, batteries, RF front‑ends, actuators) with bounded risk.
"Heavy‑element/structure" strategies: dopants, interlayers, coatings, metamaterials, and surface/phase engineering that plausibly shift stability, efficiency, or safety—computationally demonstrated.
Activation/triggered systems solving bottlenecks (e.g., temperature/field‑responsive materials, protocol activation gates) with specific rationale and safe operating windows.
Synergistic combinations with quantified uplift over baselines (e.g., coordinated schedulers/controllers/waveforms/policies with robust statistical tests) and dose‑window analogs for safe operation.
Telemetry‑defined methods of use (predictive, enrichment, or safety thresholds) with a decision rule (sensor features, limits, inclusions/exclusions).
Repurposing (new use contexts) where physics/controls evidence supports feasibility (standards alignment, deployment constraints).
✔ Content that includes PII, secrets, or controlled/dual‑use details enabling misuse.
✔ Public postings of enabling details pre‑filing (kills foreign rights).
✔ Unverifiable "black‑box" claims without data lineage and reproducibility.
