Why do we need to Introduce Temporal Behavior in Both Modern Science and Modern Computing, with an Outlook to Researching Modern Effects/Materials and Technologies

Végh, János

doi:10.34257/gjcstavol20is1pg13

Cited by 6 publications

(14 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The poor understanding of basic terms of computing resulted in that in supercomputing "the top 10 systems are unchanged from the previous list" [52], and that "Core progress in Artificial Intelligence (AI) has stalled in some quite different fields" [53]; from brain simulation [54] to ANNs [55]; in general, the AI progress [53] as a whole. Considering temporal behavior is a must [56].…”

Section: How the Presence Of Transfer Time Was Coveredmentioning

confidence: 99%

Revising the Classic Computing Paradigm and Its Technological Implementations

Végh¹

2021

Informatics

View full text Add to dashboard Cite

Today’s computing is based on the classic paradigm proposed by John von Neumann, three-quarters of a century ago. That paradigm, however, was justified for (the timing relations of) vacuum tubes only. The technological development invalidated the classic paradigm (but not the model!). It led to catastrophic performance losses in computing systems, from the operating gate level to large networks, including the neuromorphic ones. The model is perfect, but the paradigm is applied outside of its range of validity. The classic paradigm is completed here by providing the “procedure” missing from the “First Draft” that enables computing science to work with cases where the transfer time is not negligible apart from the processing time. The paper reviews whether we can describe the implemented computing processes by using the accurate interpretation of the computing model, and whether we can explain the issues experienced in different fields of today’s computing by omitting the wrong omissions. Furthermore, it discusses some of the consequences of improper technological implementations, from shared media to parallelized operation, suggesting ideas on how computing performance could be improved to meet the growing societal demands.

show abstract

Section: How the Presence Of Transfer Time Was Coveredmentioning

confidence: 99%

Revising the Classic Computing Paradigm and Its Technological Implementations

Végh¹

2021

Informatics

View full text Add to dashboard Cite

show abstract

“…Figure 1 shows why the time must be considered explicitly in all kinds of computing [20]. The figure shows (for visibility) a three-dimensional coordinate system: how an event behaves in a two-dimensional space plus time (the concept is more comfortable to visualize with the number of spatial dimensions reduced from three to two).…”

Section: Why Temporal Logic Is Neededmentioning

confidence: 99%

“…A similar interpretation was used in former studies in describing neural behavior: the mathematical formalism used time (t) as an independent parameter that was not connected (through the interaction speed of the action under study) to the spatial coordinates. Because of 1 A more general discussion of the consequences of having a limiting interaction speed is given in [20], with examples from sciences and computing.…”

Section: Introductionmentioning

confidence: 99%

On the Spatiotemporal Behavior in Biology-Mimicking Computing Systems

Végh

Berki

2021

Preprint

Self Cite

View full text Add to dashboard Cite

Both the growing demand to cope with ”big data” (based on, or assisted by, artiﬁcial intelligence) and the interest in understanding the operation of our brain more completely, stimulated the eﬀorts to build biology-mimicking computing systems from inexpensive conventional components and build diﬀerent (”neuro-morphic”) computing systems. On one side, those systems require an unusually large number of processors, which introduces performance limitations and nonlinear scaling. On the other side, the neuronal operation drastically diﬀers from the conventional workloads. The conduction time (transfer time) is ignored in both in conventional computing and ”spatiotemporal” computational models of neural networks, although von Neumann warned: ”In the human nervous system the con-duction times along the lines (axons) can be longer than the synaptic delays, hence our above procedure of neglecting them aside of τ [the processing time] would be unsound” [1], section 6.3. This diﬀerence alone makes imitating biological behavior in technical implementation hard. Besides, the recent issues in computing called the attention to that the temporal behavior is a general feature of computing systems, too. Some of their eﬀects in both biological and technical systems were al-ready noticed. Instead of introducing some ”looks like” models, the correct handling of the transfer time is suggested here. Introducing the temporal logic, based on the Minkowski transform, gives quantitative insight into the operation of both kinds of computing systems, furthermore provides a natural explanation of decades-old empirical phenomena. Without considering their temporal behavior correctly, neither eﬀective implementation nor a true imitation of biological neural systems are possible.

show abstract

“…The speed of interaction is finite [6] both in biological computing and technological computing. The finite speed contributes finite transfering timing between computing units.…”

Section: Theory Of Temporal Behaviormentioning

confidence: 99%

“…In the space-time system all coordinates have dimension of distance, and the time coordinate is given as the corresponding time multiplied by the interaction speed; free and homogeneous propagation is assumed. In our time-space system [8,6] the spatial distances are divided by the interaction speed and the time represents itself.…”

Section: The General "Procedure"mentioning

confidence: 99%

Why Learning and Machine Learning Are Different

Végh¹,

Berki²

2021

AAIML

View full text Add to dashboard Cite

Machine learning intends to be a biology-mimicking learning method, implemented by means of technical computing. Their technology and methods, however, differ very much; mainly because technological computing is based on the time-unaware classic computing paradigm. Based on the time-aware computing paradigm, the paper discovers the mechanism of biological information storing and learning; furthermore, it explains, why biological and technological information handling and learning are entirely different. The consequences of the huge difference in transmission speed in those computing systems may remain hidden in "toy"-level technological systems but comes to the light in systems having large size and/or mimicking neuronal operations. The biology-mimicking technological operations are in resemblance to the biological operations only when using time-unaware computing paradigm. The difference leads also to the need of introducing "training" mode (with desperately low efficiency) in technological learning, while biological systems have the ability of life-long learning. It is at least misleading to use technological learning methods to complement biological learning studies. The examples show evidence for the effect of transmission time in published experiments.

show abstract

Why do we need to Introduce Temporal Behavior in Both Modern Science and Modern Computing, with an Outlook to Researching Modern Effects/Materials and Technologies

Cited by 6 publications

References 23 publications

Revising the Classic Computing Paradigm and Its Technological Implementations

Revising the Classic Computing Paradigm and Its Technological Implementations

On the Spatiotemporal Behavior in Biology-Mimicking Computing Systems

Why Learning and Machine Learning Are Different

Contact Info

Product

Resources

About