Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Massive Twinning to Enhance Emergent Intelligence   Future Industrial Internet-of-Things in the upcoming 6G era is expected to
deploy artificial intelligence (AI) and digital twins (DTs) ubiquitously. As a
complement to conventional AI solutions, emergent intelligence (EI) exhibits
various outstanding features including robustness, protection to privacy, and
scalability, which makes it competitive for 6G IIoT applications. However,
despite its low computational complexity, it is challenged by its high demand
of data traffic in massive deployment. In this paper, we propose to exploit the
massive twinning paradigm, which 6G is envisaged to support, to reduce the data
traffic in EI and therewith enhance its performance.

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The categories of this paper are: hep-ph
13
The categories of this paper are: quant-ph
31
The categories of this paper are: ao-sci
11
The categories of this paper are: hep-lat
25
The categories of this paper are: patt-sol
10
The categories of this paper are: q-bio
2
The categories of this paper are: math
6
The categories of this paper are: astro-ph
24
The categories of this paper are: dg-ga
19
The categories of this paper are: eess
16
The categories of this paper are: stat
4
The categories of this paper are: cond-mat
20
The categories of this paper are: acc-phys
9
The categories of this paper are: nlin
17
The categories of this paper are: q-fin
3
The categories of this paper are: physics