Journal
ACTA BIOTHEORETICA
Volume 70, Issue 4, Pages -Publisher
SPRINGER
DOI: 10.1007/s10441-022-09450-6
Keywords
Computing paradigm; Technological computing; Biological computing; Information transfer speed; Information storage; Lifelong learning; Redundancy; Temporal behavior; Machine learning
Categories
Funding
- Semmelweis University [136496]
- National Research, Development and Innovation Fund of Hungary
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In all implementations of computing, the speed of information propagation is limited by the speed of its carrier. This limitation requires consideration of transfer time between computing units. Different mathematical methods result in different descriptions of computing systems' features. Our findings align with experimental evidence in both biological and technological computing.
In all kinds of implementations of computing, whether technological or biological, some material carrier for the information exists, so in real-world implementations, the propagation speed of information cannot exceed the speed of its carrier. Because of this limitation, one must also consider the transfer time between computing units for any implementation. We need a different mathematical method to consider this limitation: classic mathematics can only describe infinitely fast and small computing system implementations. The difference between mathematical handling methods leads to different descriptions of the computing features of the systems. The proposed handling also explains why biological implementations can have lifelong learning and technological ones cannot. Our conclusion about learning matches published experimental evidence, both in biological and technological computing.
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