Quantum Artificial Intelligence

Self-Programming Energy Circuits Tentacular Recurrent Electronics

This simple example demonstrates how undifferentiated QAI SPECTRE™ neurons self-program using quantum wave diffusion to recognize a verbal audio command taken from the 1970 Colossus science fiction movie. The structure formed demonstrates Poincaré recurrence self-organization.

Any dynamical system defined by an ordinary differential equation determines a flow mapping phase space on itself. The system is said to be volume-preserving if the volume of a set in phase space is invariant under the flow. For instance, all Hamiltonian systems are volume-preserving because of Liouville's theorem. The theorem is then: If a flow preserves volume and has only bounded orbits, then for each open set there exist orbits that intersect the set infinitely often.

The resulting self-organized dynamic recurrent neural MCM solution is automatically synthesized into a GDS2 integrated circuit description to be fabricated into GaAs and GaN QAI SPECTRE™ 3 THz BRAIN CHIP. 

The QAI SPECTRE™ BRAIN CHIP integrated circuit super Turing analog neural machine solutions are automatically synthesized into an industry standard GDS2 integrated circuit description ready for end to end electromagnetic modeling, full design rule check verification, VLSI photomask generation and rapid fabrication at the state of the art United Monolithic Semiconductor foundry front end in Ulm Germany.

Fabed BRAIN CHIP GaAs/GaN wafers are next sent to the UMS French microelectronics center and Paris QAI SPECTRE™ facility for broad band testing, precision cutting into thousands of 90%+ yield die per IC wafer. The die are MCM integrated, packaged and shipped to worldwide destinations for QAI SPECTRE™ MCM full system integration into new adaptive robots, intelligent UAVs, sensors, space platforms, life science precision CRISPR analysis systems and green 1 Watt Blockchain deployments, orders of magnitude faster than Visa.

QAI SPECTRE™ Super Turing Machine Design Process. This involves defining QAI SPECTRE™analog neurons using the QAI SPECTRE™language, which is automatically translated by the design, simulation and synthesis environment into ordinary differential equations analog circuits. The I/O pads are then configured with either simulated or real data sources to stimulate the configured neuron circuit descriptions. The neurons wirelessly interact and self-program using quantum signaling to create the optimal hardware solution. The neurons are then synthesized into a GDS2 file for downstream analog layout optimization using Cadence Virtuoso and end to end simulation using Keysight ADS. DRC is performed and a photomask is created to be sent to the foundry.