The Art of 6G (TAO 6G): how to wire Society 5.0 [Invited]
Bibliographic record
Abstract
The opening Optical Fiber Communication Conference and Exhibition 2021 plenary talk on how technologies and applications drive the evolution of networking concluded by presenting the equation Networking = Art + Science + Engineering. Due to their growing complexity, modern networks may be better viewed as techno-social systems that resemble biological superorganisms. In this paper, we expand on the aforementioned equation in the context of future 6G mobile networks, putting a focus on its first part, the Art of 6G (TAO 6G). To set the stage, we first elaborate on the 6G vision from an optical fiber fixed networks perspective, taking into account the respective viewpoints of the International Telecommunication Union-Telecommunication Standardization Sector and the FTTH Council Europe as well as the European Telecommunications Standards Institute’s recently launched fifth-generation fixed network initiative of bringing fiber to everywhere and everything, which is supposed to be the foundation of the new digital age and is a prerequisite for the digital transformation of the whole society. Towards this end, we present our ideas on what the digital society of the future will or potentially could look like. After briefly reviewing our work on tactile immersive use cases of so-called cyber-physical-social systems (CPSS), we inquire into the emerging human-centric Industry 5.0 and its mutually beneficial underlying principles of digitalization and, more interestingly, biologization. Specifically, we borrow ideas from biological superorganisms with brain-like cognitive capabilities found in natural societies for a stigmergy-enhanced Society 5.0, using tokenized digital twins for advancing collective intelligence in CPSS via indirect communication. Finally, we present our CPSS-based bottom-up token engineering framework designed for Society 5.0.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".