Hi everyone, I've released an open-source project called QuantumAccel which is built around a symbolic logic engine that transforms traditional logic gates like AND, XOR, and Toffoli into optimised quantum-inspired operations, all within a constrained mathematical space.
Features:
Ultra-fast logic compression using sparse attention
Evolving symbolic gates that simulate Hadamard, CNOT, XNOR
Memory-efficient operation (as low as 4 KB for massive input)
Reversible logic operations for feature extraction, pattern recognition, and error detection
Use Cases:
Quantum simulation
Edge AI with kilobytes of RAM
Memory compression & logic acceleration
NLP/vision feature extraction without neural nets
This is part of a larger symbolic AI framework I'm building. Would love your feedback or contributions! Let me know if you're interested in symbolic computation, quantum logic, or memory-efficient learning.
Demo benchmarks and documentation are available in the repo. Apache Licensed.
Features:
Ultra-fast logic compression using sparse attention
Evolving symbolic gates that simulate Hadamard, CNOT, XNOR
Memory-efficient operation (as low as 4 KB for massive input)
Reversible logic operations for feature extraction, pattern recognition, and error detection
Use Cases:
Quantum simulation
Edge AI with kilobytes of RAM
Memory compression & logic acceleration
NLP/vision feature extraction without neural nets
This is part of a larger symbolic AI framework I'm building. Would love your feedback or contributions! Let me know if you're interested in symbolic computation, quantum logic, or memory-efficient learning.
Demo benchmarks and documentation are available in the repo. Apache Licensed.