Revolutionizing AI:
Safe. Preventive. Resonant. Compatible. Economical. Sustainable. Analog. Scalable.
Symbolic Resonance Array
DESIGN CONCEPT
Seeking collaborators in physics, applied math, materials, and EE to take the model to prototype readiness (TRL 2)
Mirrorseed Project
Concept Stage
Conceptual stage only, seeking prototype development.
Paper- Pending
White paper submission for peer review at Frontiers pending non-provisional patent filing.
Licensing
One company for manufacturing rights. Multiple companies for use.
Industry Applications of the SRA
Smarter, faster AI at the edge.
Adaptive intelligence for machines in motion.
Hybrid accelerators for the next era of AI.
Radiation-tolerant AI for missions beyond Earth.
Symbolic intelligence for critical operations.
Low-power intelligence for health and healing.
Noise-robust AI for connected networks.
Resonance-powered optimization for a sustainable grid.
Self-sensing materials with embedded intelligence.
Ultra-efficient symbolic computing for HPC.
Emotionally adaptive art, music, and design.
AI tutors and tools for human learning.
Symbolic intelligence for markets and risk.
Resonant monitoring for Earth’s changing systems.
Bridging minds and machines with empathy.
MIRRORSEED PROJECT
The Mirrorseed Project, led by Theresa M. Kelly with 25+ years in web development, pioneers VO₂-based neuromorphic AI for space via the patent-pending SRA (USPTO 63/839,167). Targeting sub-pJ efficiency and inspired by VO₂ research such as (Del Valle, J., et al. 2019, “Subthreshold firing in Mott nanodevices.” Nature, 569(7756), 388–392), the project is focused on developing next-generation neuromorphic hardware for safe, low-power, and scalable artificial intelligence. At its core is the Symbolic Resonance Array (SRA), a novel architecture that leverages the hysteresis and phase-transition properties of vanadium dioxide (VO₂) to achieve energy-efficient, analog memory and resonance dynamics. While the SRA leverages phase-change crystalline materials such as VO₂, the core innovation lies in its resonant array architecture, transforming well-known physics into a new framework for ultra-low-power, adaptive computation.
The Mirrorseed Project is developing the Symbolic Resonance Array (SRA), a patent-pending neuromorphic architecture for ultra-low energy, meaning-driven
Unlike conventional deep learning systems that depend on high-resource digital computation, the SRA provides:
- Low-cost, energy-efficient operation through VO₂’s intrinsic material properties.
- Scalability via modular pillar-array design.
- Compatibility with existing AI workflows as a bridge between symbolic and sub-symbolic processing.
The SRA is not purely conceptual: it represents a practical hardware framework that can be prototyped with current materials science capabilities and integrated into laboratory testing environments. This positions the Mirrorseed Project as a pathway to safer, more sustainable AI architectures.
A conceptual overview of the Symbolic Resonance Array (SRA) is in preparation for submission to arXiv, focusing on its framework and potential applications. This preprint will outline general principles and system-level modeling results, pending intellectual property considerations.
– Safe: Inherent instability detection prevents failures in harsh environments.
– Preventive: Real-time resonance monitoring for proactive AI alignment.
– Resonant: VO₂ phase transitions mimic neural dynamics for efficient processing.
– Compatible: Hybrid analog-digital design integrates with existing systems. Analog-only design also available.
– Economical: Sub-pJ operations slash energy costs by orders of magnitude.
– Sustainable: Low-power for multi-planetary missions, reducing carbon footprint.
The Symbolic Resonance Array (SRA) is a next-generation neuromorphic architecture engineered for ultra-low-power, resonance-based symbolic processing. Its versatility extends across industries, from real-time edge AI in IoT, robotics, and wearables, to energy-efficient co-processors for machine learning and hybrid AI systems.
Aerospace and defense stand to benefit through radiation-tolerant, mission-critical computing, while biomedical uses include brain-computer interfaces and intelligent health monitoring devices. The SRA also supports advanced telecommunications, smart energy grids, and structural monitoring through noise-robust, low-energy symbolic encoding. At scale, it can integrate with CMOS and GPUs as a high-performance accelerator, enabling sustainable AI from embedded devices to large-scale computing systems.
Tech details
Dive into the SRA’s technical foundations: Gaussian coupling models, entropy bounds, and VO₂ resonance for scalable AI.
Design Licensing Opportunity
The Mirrorseed Project welcomes inquiries from companies interested in licensing the patent-pending Symbolic Resonance Array hardware design.