In AI and computing, the speed of light imposes fundamental limitations on how fast data can be transmitted and processed over long distances. For example, in distributed systems or cloud computing environments, latency is directly tied to the time it takes for signals to travel between distant data centers. This latency can introduce delays in tasks like real-time AI model inference or large-scale data processing. In more theoretical contexts, the speed of light is central to constraints in the simulation of physical systems and in the development of quantum computing, where entanglement and quantum communication present alternatives to classical signal transmission. The limit set by the speed of light also affects deep space communication and interstellar exploration, as signals sent to and from spacecraft take minutes or hours depending on the distance.
The significance of the speed of light in physical theory was solidified with Einstein's theory of relativity in 1905. In computing and communication, these issues became prominent as networks expanded globally in the 20th century, especially with the advent of the internet and global-scale data systems in the 1990s and 2000s.
Albert Einstein's work on the theory of relativity defined the speed of light as a fundamental constant in physics, while contributions to the modern understanding of these limitations in computing come from pioneers in network theory and distributed systems, such as Leonard Kleinrock (ARPANET development) and Vint Cerf (Internet Protocol co-creator).