🤖 AI Summary
This work proposes a novel networked computing architecture to advance trustworthy, sustainable, and technologically sovereign artificial intelligence and automation for broader societal benefit. The architecture integrates three core pillars—task-oriented communication, predictive decision-making, and hyper-digital computation—and uniquely translates fundamental physical constraints from Shannon, Landauer, Turing, and Einstein into system design principles. It realizes a quantifiable socio-technical system through post-Shannon goal-oriented communication, a negative-latency pre-action mechanism bounded by confidence thresholds, and energy-efficient, deadline-aware selection of computational substrates. Empirical validation across remote education, robotic tutoring, and elderly care demonstrates its efficacy using metrics including task-level latency, bits per event, energy and carbon footprint per task, security, privacy, and robustness.
📝 Abstract
The Shared Prosperity Internet (SPI) is a network-computing architecture that makes the benefits of automation and Artificial Intelligence (AI) broadly accessible to the society. To ground its design, this paper maps the physical constraints of Shannon, Landauer, Turing, and Einstein to three design principles: trustworthiness, sustainability, and technological sovereignty, and maps them into three technical pillars: i) post-Shannon, goal-oriented communication that transmits only what the task requires; ii) anticipatory decision-making ("negative latency") with confidence-bounded pre-action and correction; and iii) beyond-digital computing that selects energy-optimal substrates under deadline and computability constraints. The SPI is grounded in three societal use cases: remote teaching for pupils, remote teaching of robots and cyber-physical systems, and elder care. Furthermore, this paper defines measurable outcomes for an SPI, including latency decomposition, bits per event, energy and CO2 per task, safety and privacy indicators, and robustness.