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The proliferation of the Internet of Things (IoT) and its cutting-edge AI-enabled applications (e.g., autonomous vehicles and smart industries) combine two paradigms: data-driven systems and their deployment on the edge. Usually, edge…

Machine Learning · Computer Science 2025-08-01 Ghazal Sobhani , Md. Monzurul Amin Ifath , Tushar Sharma , Israat Haque

Generative AI is rapidly reshaping creative work, raising critical questions about its beneficiaries and societal implications. This study challenges prevailing assumptions by exploring how generative AI interacts with diverse forms of…

Human-Computer Interaction · Computer Science 2024-12-06 Meiling Huang , Ming Jin , Ning Li

Most models that try to explain economic growth indicate exponential growth paths. In recent years, however, a lively discussion has emerged considering the validity of this notion. In the empirical literature dealing with drivers of…

Economics · Quantitative Finance 2018-03-06 Steffen Lange , Peter Pütz , Thomas Kopp

The artificial intelligence industry is not an isolated economic phenomenon; it is the current physical substrate for a broader, multi-billion-year process: the evolution of an abstract intelligence on Earth. As the scale of computation…

Physics and Society · Physics 2026-05-29 William Yicheng Zhu , Lei Zhu

Facing the current debate on whether Large Language Models (LLMs) attain near-human intelligence levels (Mitchell & Krakauer, 2023; Bubeck et al., 2023; Kosinski, 2023; Shiffrin & Mitchell, 2023; Ullman, 2023), the current study introduces…

Artificial Intelligence · Computer Science 2024-05-21 Junqi Wang , Chunhui Zhang , Jiapeng Li , Yuxi Ma , Lixing Niu , Jiaheng Han , Yujia Peng , Yixin Zhu , Lifeng Fan

We argue that representations in AI models, particularly deep networks, are converging. First, we survey many examples of convergence in the literature: over time and across multiple domains, the ways by which different neural networks…

Machine Learning · Computer Science 2024-07-26 Minyoung Huh , Brian Cheung , Tongzhou Wang , Phillip Isola

As large-scale AI models expand, training becomes costlier and sustaining progress grows harder. Classical scaling laws (e.g., Kaplan et al. (2020), Hoffmann et al. (2022)) predict training loss from a static compute budget yet neglect time…

Machine Learning · Computer Science 2025-01-09 Chien-Ping Lu

Artificial and biological systems may evolve similar computational solutions despite fundamental differences in architecture and learning mechanisms -- a form of convergent evolution. We demonstrate this phenomenon through large-scale…

Neurons and Cognition · Quantitative Biology 2025-07-04 Guobin Shen , Dongcheng Zhao , Yiting Dong , Qian Zhang , Yi Zeng

With the advancements in machine learning (ML) methods and compute resources, artificial intelligence (AI) empowered systems are becoming a prevailing technology. However, current AI technology such as deep learning is not flawless. The…

Machine Learning · Computer Science 2023-01-10 Pin-Yu Chen , Payel Das

This work presents a large-scale analysis of artificial intelligence (AI) and machine learning (ML) references within news articles and scientific publications between 2011 and 2019. We implement word association measurements that…

Computation and Language · Computer Science 2021-02-26 Autumn Toney

This study aims to evaluate quantitatively, albeit in arbitrary units, the evolution of complexity of the human system since the domestication of fire. This is made possible by studying the timing of the 14 most important milestones, breaks…

Physics and Society · Physics 2025-06-18 Theodore Modis

As AI systems appear to exhibit ever-increasing capability and generality, assessing their true potential and safety becomes paramount. This paper contends that the prevalent evaluation methods for these systems are fundamentally…

Artificial Intelligence · Computer Science 2024-07-15 John Burden

AI that can accelerate research could drive a century of technological progress over just a few years. During such a period, new technological or political developments will raise consequential and hard-to-reverse decisions, in rapid…

Computers and Society · Computer Science 2025-06-19 William MacAskill , Fin Moorhouse

Deep models are dominating the artificial intelligence (AI) industry since the ImageNet challenge in 2012. The size of deep models is increasing ever since, which brings new challenges to this field with applications in cell phones,…

Generative AI compresses within-task skill differences while shifting economic value toward concentrated complementary assets, creating an apparent paradox: the technology that equalizes individual performance may widen aggregate…

Machine Learning · Computer Science 2026-03-10 Xupeng Chen , Shuchen Meng

The dominant narrative of artificial intelligence development assumes that progress is continuous and that capability scales monotonically with model size. We challenge both assumptions. Drawing on punctuated equilibrium theory from…

Artificial Intelligence · Computer Science 2026-03-17 Mark Baciak , Thomas A. Cellucci , Deanna M. Falkowski

AI technology has a long history which is actively and constantly changing and growing. It focuses on intelligent agents, which contain devices that perceive the environment and based on which takes actions in order to maximize goal success…

Artificial Intelligence · Computer Science 2018-04-05 Jahanzaib Shabbir , Tarique Anwer

A robust nonproliferation regime has contained the spread of nuclear weapons to just nine states. Yet, emerging and disruptive technologies are reshaping the landscape of nuclear risks, presenting a critical juncture for decision makers.…

Computers and Society · Computer Science 2025-12-10 David M. Allison , Stephen Herzog

In the last couple of years, the rise of Artificial Intelligence and the successes of academic breakthroughs in the field have been inescapable. Vast sums of money have been thrown at AI start-ups. Many existing tech companies -- including…

Artificial Intelligence · Computer Science 2018-10-10 Jean-Marie Chauvet

Large language models (LLMs) promise to democratize financial analysis by reducing information-processing costs. Yet equal access does not ensure equal outcomes, as the locus of friction may shift from processing information to evaluating…

General Finance · Quantitative Finance 2025-10-23 Edward Li , Min Shen , Zhiyuan Tu , Dexin Zhou