Sep 2013· International Conference on e-Business· pp. 169-176· 2 citations· ⚡ 1 influential· 13 references
Computer Science
TL;DR
It is claimed that consumers' technology foresight horizon is limited by the existing technological base and the idea database should be an interesting source of ideas for service developers.
Abstract
Lead user driven innovation and open innovation paradigms seek to involve consumers and common people to innovative product development projects. In order to help developers choose ideas that meet the end users' needs, we undertook a massive collaborative research effort and collected 40000 ideas from 2150 common people about future mobile services that they would like to use. We inspired each people to produce tens of mobile service ideas. In this paper we carry out an analysis for 4000 ideas from the idea database. We had a particular interest in whether peoples' ideas can be used in foreseeing the technology development needs. The results show that end users produce ideas that are conservative more than novel. Therefore, we claim that consumers' technology foresight horizon is limited by the existing technological base. The second finding, linked to the previous one, is that the great majority of the ideas that consumers expressed could be realised utilizing existing technologies. The implication of this finding is that the idea database should be an interesting source of ideas for service developers. The third finding of the study, related to the methodology, is that a vast number of ideas can be collected fairly easily but analyzing them cost effectively is a challenge.
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 possibility of inferring high-dimensional data inference in a model that consists of a prior and an auxiliary differentiable constraint given some additional information is considered, thereby allowing a range of potential applications in adapting models to new domains and tasks.
Alexandros Graikos, Esmeralda S. Whitammer, N. Jojic et al.· Neural Information Processin...· 316 citations· ⚡15
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
Microsoft Research Blog· microsoft.comOct 21, 2026
For decades, a fundamental question about the difficulty of computing in high-dimensional spaces has resisted proof. New research resolves this question, removing a major theoretical obstacle to understanding the efficiency of randomized algorithms used across science and computing. The Kannan–Lovász–Simonovits (KLS) conjecture was proposed in 1995. It asks whether, for a broad class of high-dimensional […] The post Solving a 31-year-old grand challenge in mathematics – the KLS conjecture appear…
Computer scientist, entrepreneur, and philanthropist will collaborate with the MIT Schwarzman College of Computing to advance AI and scientific discovery.
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.