Artificial Intelligence (AI), Rio Tinto and Firm Leading-Edge AI Competitiveness
Hamilton, John R., and Maxwell, Stephen J. (2023) Artificial Intelligence (AI), Rio Tinto and Firm Leading-Edge AI Competitiveness. In: Proceedings of the 23rd International Conference on Electronic Business (23) pp. 36-44. From: ICEB 2023: 23rd International Conference on Electronic Business, 19-23 October 2023, Chiayi, Taiwan.
![[img]](https://researchonline.jcu.edu.au/style/images/fileicons/application_pdf.png) |
PDF (Published Version)
- Published Version
Restricted to Repository staff only |
Abstract
This study frames AI into five successive generational AI All development phases of increasing complex program and platform diversity, whilst drawing on involving increasingly diverse and rich ‘global’ sources of ‘relevant’ data. It considers the AI techniques Rio Tinto applies at each generational level. It recognizes the AI complexities of resourcing, technologies, connectivities integrations, intelligent devices, and data-recall capacities on leading-edge firms and their ongoing competitiveness. It proposes a leading-edge firm timeline stagewise strategic AI feedback model.
| Item ID: | 81564 |
|---|---|
| Item Type: | Conference Item (Research - E1) |
| ISSN: | 1683-0040 |
| Keywords: | AI generation, AI techniques, big data complexity, deep learning AI, intelligent augmented AI, machine learning, strategic AI competitiveness, super-intelligent AI |
| Related URLs: | |
| Date Deposited: | 06 Feb 2024 01:28 |
| FoR Codes: | 46 INFORMATION AND COMPUTING SCIENCES > 4602 Artificial intelligence > 460299 Artificial intelligence not elsewhere classified @ 100% |
| SEO Codes: | 28 EXPANDING KNOWLEDGE > 2801 Expanding knowledge > 280115 Expanding knowledge in the information and computing sciences @ 100% |
| Downloads: |
Total: 1 |
| More Statistics |
Actions (Repository Staff Only)
 |
Item Control Page |