The HE processes data completely differently to conventional explicitly programmed machine learning and neural network architecture systems. The HE genuinely processes data non-algorithmically, the HE learns autonomously, minimal pre-training is required.
The totally unique and complex core HE invention displays quantum-like behaviour of superposition and entanglement and is inspired by theories of harmonic resonance, wave mechanical, fractal intelligence, autopoietic systems, cybernetics, practopoiesis, and information theory.
The HE technology identifies complex patterns in vast volumes of data with minimal pre-programming time, no code computation is more data efficient and accurate, the HE can self-train and process without any domain specific training models.
The Holometric Engine is designed to facilitate; adoption of advanced AI analytics for superior optimization, improved accuracy, and better pattern recognition and prediction, for anomaly and signal detection, clustering, segmentation, video, and image recognition purposes.
The revolutionary HE architecture provides a powerful real time AI processing capability enabling the opportunity to “solve particular complex problems that conventional AI architecture cannot solve”, and facilitating significantly reduced pre-programming and training time costs dependant on the specific use case / application.
General Problem Solving Ability: Domain and application agnostic, the core HE system does not require re-coding, reducing software engineering technical complexity, creating significant cost savings.
Low level Input Pre-Programming: Minimal pre-programming, significantly reducing data scientist’s pre-software development time, allowing valuable programming time to be efficiently re-deployed.
Self-supervised Learning (SSL): The HE self-learns by “habituation”, an explicit training model for any domain is not required to process during the testing phase, to find an optimal solution in any domain the innate behavioural changes inside the HE are monitored and interpreted for a specific application.
Life-long Learning (LLL): The HE continually and perpetually self learns and self-trains adapting and evolving to changed environmental conditions without any re-coding within the core HE processor.
Faster Processing Time: No complex multi network layer mathematical computation is required effecting instantaneous processing enabling lower latency, improving and enhancing system operations.
Solving Problems Conventional AI Cannot Solve: Superior processing accuracy, less errors and massive state space that facilitates solving particular complex computational problems that conventional AI cannot solve, enabling development of new AI solutions, applications and use cases.
Highly Scalable: The HE is non-linear and highly scalable, no human programming intervention is required within the core HE processing system, limited only by CPU / GPU speed and memory capacity.
Ingeniation’s Holographic AI represents an advanced form of Oscillatory Neural Network (ONN) like technology which enables brain-like neural processing on standard computing platforms. ONN’s are networks which work on the principles of wave mechanics, similar to the function of neurons interacting in the living human brain.
The Holometric Engine (HE) realises a complex ONN based on interacting units (oscillators) which Ingeniation call Holons. An elementary holon is simultaneously a whole and a part leading to the unusual phenomenon that by composing many of them will result in a larger holon. If an elementary holon is stimulated by external influences, it enters a distinctive vibrational state reflective of the type of stimulus presented.
In a compositional holon system, individual vibrations ultimately synchronize creating a resonant state in the system. The uniqueness in the HE operation is that it has the capability to dynamically modify its internal processing logic to achieve resonant states regardless of the type of input presented. The HE is effectively a harmony seeking device continuously trying to achieve synchronization with its environment and in a continuous and perpetual feedback loop.
Ingeniation’s successfully uses the HE capability in different problem use-cases including image recognition, signal and anomaly detection, segmentation, classification, and logical problem solving, all without the need to modify a single line of code or binary bit in the HE original core code. The HE is dynamically adapting and self-modifying its programming logic according to the problem at hand without any need of external programming intervention. We believe this is a clear sign of “general purpose problem solving” intelligence capabilities.
ONN’s traditionally rely on physical realization such as mechanical and / or electronic components to achieve vibrational effects, whereas the holon is a virtual entity which can be realised on a standard computer platform. The virtualization technology invented by Ingeniation is based on holographic principles as evident in wave mechanical domains such as optics (light has both wave-like and particle-like properties).
In principle, the HE can also be implemented using spiking neural network (SNN) technology, opening an unseen opportunity to transform conventional neural network technologies into ONN’s.
Wave mechanical theory proposes that electrons circling an atoms nucleus occupying a specific orbital field are almost as much like a wave of energy as they are like particles. A mechanical wave is an oscillation of matter, transferring energy through a medium.