mlsanityData to 13 Oct 2026

Telecom AI Native Systems in the Age of Generative AI -- An Engineering Perspective

arXiv 2310.11770 ↗First posted 18 Oct 2023cs.SE cs.AIcited by 3

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Abstract (arXiv)

The rapid advancements in Artificial Intelligence (AI), particularly in generative AI and foundational models (FMs), have ushered in transformative changes across various industries. Large language models (LLMs), a type of FM, have demonstrated their prowess in natural language processing tasks and content generation, revolutionizing how we interact with software products and services. This article explores the integration of FMs in the telecommunications industry, shedding light on the concept of AI native telco, where AI is seamlessly woven into the fabric of telecom products. It delves into the engineering considerations and unique challenges associated with implementing FMs into the software life cycle, emphasizing the need for AI native-first approaches. Despite the enormous potential of FMs, ethical, regulatory, and operational challenges require careful consideration, especially in mission-critical telecom contexts. As the telecom industry seeks to harness the power of AI, a comprehensive understanding of these challenges is vital to thrive in a fiercely competitive market.

Key facts. Cited by 3 papers in the map (data through 13 Oct 2026). Builds on 2 of its 3 references that are in the map. First posted on arXiv 18 Oct 2023.

Builds on

2 of 3 references.

References · 2

  1. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,231
  2. 2020A Software Engineering Perspective on Engineering Machine Learning Systems: State of the Art and Challengescited by 33

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Citing papers per year: 2023: 1; 2024: 2.

3 papers.