US Patent Application 20180039485A1

Synchronized True Random Number Generator

Abstract

A synchronized true random number generator (SRNG) includes a pulse source that provides a synchronized pulse signal synchronized with a known time, an oscillator to make a clock signal, a time synthesizer, and a triggerable true random number generator (TRNG). Another embodiment includes a plurality of independent triggerable TRNGs, separated by a separation distance, that produce free TRNG output. A separation distance is a distance greater than the product of the speed of light (C) multiplied by the generation period. A generation period of a TRNG is the period from the start of generating a random number until the random number can be determined. A triggerable single-photon-detector TRNG comprises first and second single-photon detectors, a light source, first and second pulse-generator circuits, and a first-pulse detector. A triggerable photon-shot-noise TRNG contains a photonic detector comprising two photodiodes connected back-to-back, and light source (e.g., an LED) providing illumination to the two photodiodes; a current-to-voltage converter; an amplifier; and a comparator for converting the amplified voltage noise to a binary random bit output.

US Patent Application 20160283197A1

Artificial Intelligence Device and Method Responsive to Influences of Mind

Abstract

A device for detecting an influence of mind comprises a source of non-deterministic random numbers, SNDRN, a phase-sensitive filter, and a results interface. In some embodiments, the phase-sensitive filter comprises a complex filter. An artificial sensory neuron comprises a SNDRN. An analog artificial sensory detector comprises a plurality of analog artificial sensory neurons, an abstracting processor and a control or feedback unit. Some embodiments include an artificial neural network. An artificial consciousness network contains a plurality of artificial neural networks. One of the artificial neural networks comprises an activation pattern meta-analyzer. An artificial intelligence device comprises a cluster of artificial consciousness networks, a sensory input device to provide sensory input signals to the input of one or more ANNs, and an output device.

US Patent Number 9,367,288

Device and Method Responsive to Influences of Mind

Abstract

An anomalous effect detector responsive to an influence of mind comprises a source of non-deterministic random numbers, SNDRN, a phase-sensitive filter and a results interface. In some embodiments, the phase-sensitive filter comprises a complex filter. An artificial sensory neuron comprises a SNDRN. Preferably, several artificial sensory neurons are grouped in a small volume. An analog artificial sensory detector comprises a plurality of analog artificial sensory neurons, an abstracting processor and a control or feedback unit. Some embodiments include an artificial neural network. An artificial consciousness network contains a plurality of artificial neural networks. One of the artificial neural networks comprises an activation pattern meta-analyzer. An artificial consciousness device comprises a cluster of artificial consciousness networks, a sensory input device to provide sensory input signals to the input of one or more ANNs in ACD, and an output device.

US Patent Application 20160062735A1

Acquisition and Assessment of Classically Non-Inferable Information

Abstract

Mind-enabled question answering (MEQA) systems (300, 340) and methods (400, 500) produce answers (313) that are not inferable from information available from private databases, online searching or other traditional sources. MEQA systems utilize information provided by using devices (200) and methods that are responsive to an influence of mind. Preferred embodiments of MEQA technology use a Bayesian Network to calculate the probability of an answer’s correctness. MEQA systems and methods utilize high speed non-deterministic random number generators (NDRNGs). Preferred NDRNGs (202) achieve high statistical quality without randomness correction, which allows improved response of a mind-enabled device (200, 302).

PCT Patent Application WO201482672A1

Acquisition and Assessment of Classically Non-Inferable Information

Abstract

Mind-enabled question answering (MEQA) systems (300, 340) and methods (400, 500) produce answers (313) that are not inferable from information available from private databases, online searching or other traditional sources. MEQA systems utilize information provided by using devices (200) and methods that are responsive to an influence of mind. Preferred embodiments of MEQA technology use a Bayesian Network to calculate the probability of an answer’s correctness. MEQA systems and methods utilize high speed non-deterministic random number generators (NDRNGs). Preferred NDRNGs (202) achieve high statistical quality without randomness correction, allowing the special properties of quantum measurements to be preserved.

US Patent Number 8,423,297

Device and Method for Responding to Influences of Mind

Abstract

Mental influence detectors and corresponding methods are useful for detecting an influence of mind and hidden or classically non-inferable information. An anomalous effect detector includes a source of non-deterministic random numbers, a converter to convert a property of numbers, a processor to accept converter output and to produce an output signal representative of an influence of mind. The processor output signal contains fewer numbers than the input. A quantum computer includes a physical source of entropy to generate output numbers; a source of test numbers; a measurement processor to accept output numbers and to measure a relationship between process numbers and at least one test number to produce an output representative of an influence of mind.

US Patent Number RE44,097 E

Device and Method for Responding to Influences of Mind

Abstract

In the field of direct mind-machine interactions, prior art devices and methods do not provide sufficiently fast and reliable results. Mental influence detectors (100, 140, 400, 430) and corresponding methods provide fast and reliable results useful for detecting an influence of mind and hidden or classically non-inferable information. An anomalous effect detector (100) includes a source (104) of non-deterministic random numbers (110), a converter (114) to convert a property of numbers, a processor to accept converter output (118) and to produce an output signal (124) representative of an influence of mind. The processor output signal (124) contains fewer numbers than the input (110). A quantum computer (400) includes a physical source of entropy (404) to generate output numbers (405); a source (406) of test numbers (407); a measurement processor 410) to accept output numbers (405) and to measure a relationship between process numbers and at least one test number to produce an output (414) representative of an influence of mind.

US Patent Number 6,862,605 (Under License)

True Random Number Generator and Entropy Calculation Device and Method

Abstract

A random number generator includes a first oscillator that provides a first oscillatory signal to a processor, and a second oscillator that provides a signal to a frequency multiplier, which in turn provides a second oscillatory signal to the processor. The relative jitter between the two oscillatory signals contains a calculable amount of entropy that is extracted by the processor to produce a sequence of true random numbers.

US Patent Numbers 6,324,558, 6,763,364, 7,096,242 and 7,752,247 (Under License)

Random Number Generator and Generation Method

Abstract

An RNG circuit is connected to the parallel port of a computer. The circuit includes a flat source of white noise and a CMOS amplifier circuit compensated in the high frequency range. A low-frequency cut-off is selected to maintain high band-width yet eliminate the 1/f amplifier noise tail. A CMOS comparator with a 10 nanosecond rise time converts the analog signal to a binary one. A shift register converts the serial signal to a 4-bit parallel one at a sample rate selected at the knee of the serial dependence curve. Two levels of XOR defect correction produce a BRS at 20 kHz, which is converted to a 4-bit parallel word, latched and buffered. The entire circuit is powered from the data pins of the parallel port. A device driver interface in the computer operates the RNG. The randomness defects with various levels of correction and sample rates are calculated and the RNG is optimized before manufacture.