In this article, we reflect on the complexity of data relationships and the limiting resources of memory formation. The information bottlenecks have been addressed in both natural and artificial computing systems.

Data driven studies of attention, memory formation, and behavior have been reported in the literature. Multidimensional information scaling and the scale-space topology, across different sensory modalities, have been discussed in our reports.

The evolving dynamics of computational complexity in artificial systems have been discussed in terms of architectures, algorithmic speed, memory requirements, and energy consumption. Current trends in neuromorphic and quantum computing cross-examine neural postulates when applied to artificial and hybrid systems.

Multidimensional information scaling and the scale-space topology

Multidimensional information scaling in the atomic structure has been derived. In the theory of stochastic resonance synergies, the internal states of networked systems propagate information via scale-space waves, coupled quantum oscillators, and tunneling. The information flow does not directly apply to temporal dynamics.

Circular search patterns of information clusters encoded within the nucleons' have been described. Neuroimaging of topological brain source localization has been shown. We have proposed clinical applications in diagnosis, analysis, and monitoring, as well as the treatment of disordered neural states.

Convergence of computing and memory formation

Interdisciplinary studies in neuroscience, computer science, and electrical engineering have brought together an approach known as neuromorphic computing. Pioneered by Carver Mead, it brings back analog transistors to express more than conventional bits of information.

Back in 1988, I took a project course on color enhancement in his class while a graduate student at Caltech. Analyzing images is a challenging task, even for the most powerful computers. Our brains do it easily and effortlessly, thus making our surroundings look so colorful.

Multispectral image analysis was lagging well behind collecting them from satellites at the JPL. Despite the availability of powerful computers, a neuromorphic computer learns to recognize patterns much faster and with less training data by applying the strategies of neural systems instead of programming them in digital computers.

Convergence of information expression and time frame computation

Advances in quantum computing come from utilizing multiple states of quantum bits in information processing. Expressing information in probabilities while optimizing uncertainties is part of the process.

Many hard tasks in chemistry, medicine, and the better utilization of energy could take advantage of quantum computing. This would change the way we use computers. Arguably, many aspects of our daily lives are too. One could say everything, but neither all nor at once. Assisting our daily activities with quantum computers would make us a part of the observation process itself.

Concluding remarks

Time is nature's way of keeping everything from happening at once.

(John Wheeler)

The computing paradigms of nature have been inspirational in designing man-made machines. Since the introduction of Von Neumann architecture and spatio-temporal organization, designers's attention has shifted to include various physiques of computation: architectures, algorithmic speed, memory requirements, and better consumption of energy.

Imagination of nature is far greater than that of man, in a statement of Richard Feynman, heading its impact on science and technology. At the dawn of quantum computing, computing approaches seem to be moving in a direction away from conventional, time-framed finite-state machines.


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