Abstract In this chapter, we focus on a digital innovation which is not confined to a single application such as digital platforms, but on one – Artificial Intelligence or AI – which is in course of pervading the whole of the economy and society, and fully deserves the title of one (or several) general purpose technologies or GPTs. Estimates of its likely economic effects, particularly on productivity and labour demand, remain extremely varied and deeply uncertain. The risks which it imposes on individual groups, or even the whole human race, are still speculative. The European Union passed in 2024 an AI Act which seeks to guard against some of those risks. More prosaically, the possibility of monopolization of the supply of AI, for example by dominance of key inputs such as chips, ‘compute’ or Large Language Models, has receded as rivalry has extended to massive AI investments by several major platform companies, as well as the emergence of inventive western rivals and serious Chinese competitors. Finally, AI pervades even the field of regulation. There will not only be regulation of AI, but also regulation being done with AI, leading to a possible arms race between the AI tools deployed by regulatees and those available to regulators.
GAOKAO-Bench is introduced, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test samples, including both subjective and objective questions that contribute a robust evaluation benchmark for future large language models and offers valuable insights into the advantages and limitations of such models.
Xiaotian Zhang, Chun-yan Li, Yi Zong et al.· arXiv.org· 216 citations· ⚡17
The results are packaged in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible, and the need to shorten time-to-market, by speeding up the development through low-precision engineering activities.
Carmine Giardino, Nicolò Paternoster, M. Unterkalmsteiner et al.· IEEE Transactions on Softwar...· 178 citations· ⚡14
Software startup companies develop innovative, software-intensive products within limited timeframes and with few resources, searching for sustainable and scalable business models.
M. Unterkalmsteiner, P. Abrahamsson, Xiaofeng Wang et al.· e-Informatica Software Engin...· 157 citations· ⚡17
This study conducts a case survey study based on the secondary data of the major pivots happened in 49 software startups, and demonstrates that customer need pivot is the most common among all pivot types.
Sohaib Shahid Bajwa, Xiaofeng Wang, Anh Nguyen-Duc et al.· Empirical Software Engineeri...· 127 citations· ⚡15
The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.
Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al.· Journal of Systems and Softw...· 111 citations· ⚡8
The ongoing work building a Raspberry Pi cluster consisting of 300 nodes is presented, with potential use cases being an inexpensive and green test bed for cloud computing research and a robust and mobile data center for operating in adverse environments.
P. Abrahamsson, S. Helmer, Nattakarn Phaphoom et al.· IEEE International Conferenc...· 110 citations· ⚡7