Sep 2026· Zenodo (CERN European Organization for Nuclear Research)· 2 citations· 2 references
Abstract
This practical guidance presents a procedure for installing and operating the CubeTechnology system in which artificial intelligence is used as a continuous assistant to the user at all stages of working with the system. The main distinguishing feature of the proposed approach is that the user provides ChatGPT, or another AI service they are accustomed to using, with the CubeTechnology documentation archive. The AI uses a dedicated navigation document within the archive to identify the required manuals and documentation sections, explain the sequence of actions, help verify that the installation has been completed correctly, translate instructions into the user’s native language, support the execution of training and production tasks, and assist in analyzing difficulties that arise during operation. When errors or unexpected results occur, the user can provide the chat with screenshots, calculation logs, program parameters, input and output files, VisualCube scenes, and other diagnostic materials. The AI compares these materials with the system documentation, helps localize the cause of the problem, and proposes a sequence of checks. If the issue cannot be resolved in the chat, the AI can help prepare a message to the author of CubeTechnology, and the author’s reply can then be added to the same chat so that the work can continue. This form of support reduces the user’s dependence on the developer’s constant direct involvement and makes it possible to master the system progressively, from installation and familiarization with the VisualCube multi-window graphical interface to performing seismic data processing and interpretation tasks. The guidance also provides links to the software distribution package, complete documentation, test data, training materials, and related CubeTechnology publications. Related publications: 1. CubeTechnology system presentation: https://doi.org/10.5281/zenodo.22122420 2. Announcement of the book on the theoretical foundations of the system: https://doi.org/10.5281/zenodo.22064681 3. Special Courses on the Theory of the System: https://doi.org/10.5281/zenodo.22108817
This paper investigates developing real-world perception for active agents, proposes Gibson Environment for this purpose, and showcases a set of perceptual tasks learned therein.
F. Xia, Amir Zamir, Zhi-Yang He et al.· 2018 IEEE/CVF Conference on...· 1,069 citations· ⚡112
This publication proposes a definition and a classification of agile software development approaches and analyses ten software development methods that can be characterized as being "agile" against the defined criterion.
P. Abrahamsson, O. Salo, Jussi Ronkainen et al.· arXiv.org· 727 citations· ⚡54
The study shows that agile practices improve both informal and formal communication, but indicates that, in larger development situations involving multiple external stakeholders, a mismatch of adequate communication mechanisms can sometimes even hinder the communication.
M. Pikkarainen, Jukka Haikara, O. Salo et al.· Empirical Software Engineeri...· 401 citations· ⚡48
The results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.
Nicolò Paternoster, Carmine Giardino, M. Unterkalmsteiner et al.· Information and Software Tec...· 394 citations· ⚡54
The results show that the embedded industry has been able to apply agile methods in its development processes and that the appreciation of the agile methods and their individual practices appears to increase once adopted and applied in practice.
O. Salo, P. Abrahamsson· IET Software· 238 citations· ⚡9
Consequences of happiness and unhappiness that are beneficial and detrimental for developers' mental well-being, the software development process, and the produced artifacts are found.
D. Graziotin, Fabian Fagerholm, Xiaofeng Wang et al.· Journal of Systems and Softw...· 236 citations· ⚡13
Related blog posts
Microsoft Research Blog· microsoft.comOct 30, 2026
Evaluating Microsoft Copilot at enterprise scale requires test data that captures the full complexity of real organizations, yet real enterprise data contains sensitive information that cannot be used for evaluation under any circumstances. The post From synthetic enterprise data evaluations to real Microsoft Copilot AI confidence appeared first on Microsoft Research.
Microsoft Research Blog· microsoft.comOct 29, 2026
Host Sowbhagya Suresh shares some of the latest news and cutting-edge research from across Microsoft—from understanding the challenges facing coding agents to uncovering how people use AI at work and improving extended-range weather forecasting. The post Microsoft Research Focus – Edition #97 appeared first on Microsoft Research.
StudentSim is a research system for evaluating and improving AI tutoring tools before they are tested with learners. It models how individuals may engage with tutors, giving feedback to improve tutor performance across subjects like chess, writing, and mathematics. The post Simulating student learning for better AI tutoring appeared first on Microsoft Research.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.