81,798 research outputs found
How is Artificial Intelligence redefining modern international marketing?
Due to the advancement of Artificial Intelligence and its development in the International Marketing area, specialists have now the tools to completely redefine the current understanding of branding, marketing, advertising. This paper concentrates on introducing the reader to the available AI-based tools for marketing purposes and provides an insight on how the presented solutions contribute to the modern marketing worldwide. Additionally the paper presents theoretical insights on how to effectively manage highly innovative products such as Marketing AI and how to implement them in the International Marketing strategies of corporate market agents. The theoretical part is supported with an empirical study based on two semi-structured interviews with the representatives of companies offering Marketing AI products for international corporate clients
Towards Responsible AI in the Era of ChatGPT: A Reference Architecture for Designing Foundation Model-based AI Systems
The release of ChatGPT, Bard, and other large language model (LLM)-based
chatbots has drawn huge attention on foundations models worldwide. There is a
growing trend that foundation models will serve as the fundamental building
blocks for most of the future AI systems. However, incorporating foundation
models in AI systems raises significant concerns about responsible AI due to
their black box nature and rapidly advancing super-intelligence. Additionally,
the foundation model's growing capabilities can eventually absorb the other
components of AI systems, introducing the moving boundary and interface
evolution challenges in architecture design. To address these challenges, this
paper proposes a pattern-oriented responsible-AI-by-design reference
architecture for designing foundation model-based AI systems. Specially, the
paper first presents an architecture evolution of AI systems in the era of
foundation models, from "foundation-model-as-a-connector" to
"foundation-model-as-a-monolithic architecture". The paper then identifies the
key design decision points and proposes a pattern-oriented reference
architecture to provide reusable responsible-AI-by-design architectural
solutions to address the new architecture evolution and responsible AI
challenges. The patterns can be embedded as product features of foundation
model-based AI systems and can enable organisations to capitalise on the
potential of foundation models while minimising associated risks
Expectile Matrix Factorization for Skewed Data Analysis
Matrix factorization is a popular approach to solving matrix estimation
problems based on partial observations. Existing matrix factorization is based
on least squares and aims to yield a low-rank matrix to interpret the
conditional sample means given the observations. However, in many real
applications with skewed and extreme data, least squares cannot explain their
central tendency or tail distributions, yielding undesired estimates. In this
paper, we propose \emph{expectile matrix factorization} by introducing
asymmetric least squares, a key concept in expectile regression analysis, into
the matrix factorization framework. We propose an efficient algorithm to solve
the new problem based on alternating minimization and quadratic programming. We
prove that our algorithm converges to a global optimum and exactly recovers the
true underlying low-rank matrices when noise is zero. For synthetic data with
skewed noise and a real-world dataset containing web service response times,
the proposed scheme achieves lower recovery errors than the existing matrix
factorization method based on least squares in a wide range of settings.Comment: 8 page main text with 5 page supplementary documents, published in
AAAI 201
Software Engineering Timeline: major areas of interest and multidisciplinary trends
Ingeniería del software. EvolucionSociety today cannot run without software and by extension, without Software Engineering. Since this discipline emerged in 1968, practitioners have learned valuable lessons that have contributed to current practices. Some have become outdated but many are still relevant and widely used. From the personal and incomplete perspective of the authors, this paper not only reviews the major milestones and areas of interest in the Software Engineering timeline helping software engineers to appreciate the state of things, but also tries to give some insights into the trends that this complex engineering will see in the near future
The effect of surveillance and appreciative inquiry on puerperal infections : a longitudinal cohort study in India
Peer reviewedPublisher PD
A new QoS routing algorithm based on self-organizing maps for wireless sensor networks
For the past ten years, many authors have focused
their investigations in wireless sensor networks. Different
researching issues have been extensively developed: power
consumption, MAC protocols, self-organizing network algorithms,
data-aggregation schemes, routing protocols, QoS
management, etc. Due to the constraints on data processing
and power consumption, the use of artificial intelligence
has been historically discarded. However, in some special
scenarios the features of neural networks are appropriate to
develop complex tasks such as path discovery. In this paper,
we explore and compare the performance of two very well
known routing paradigms, directed diffusion and Energy-
Aware Routing, with our routing algorithm, named SIR,
which has the novelty of being based on the introduction of
neural networks in every sensor node. Extensive simulations
over our wireless sensor network simulator, OLIMPO, have
been carried out to study the efficiency of the introduction
of neural networks. A comparison of the results obtained
with every routing protocol is analyzed. This paper attempts
to encourage the use of artificial intelligence techniques in
wireless sensor nodes
Complex networks analysis in socioeconomic models
This chapter aims at reviewing complex networks models and methods that were
either developed for or applied to socioeconomic issues, and pertinent to the
theme of New Economic Geography. After an introduction to the foundations of
the field of complex networks, the present summary adds insights on the
statistical mechanical approach, and on the most relevant computational aspects
for the treatment of these systems. As the most frequently used model for
interacting agent-based systems, a brief description of the statistical
mechanics of the classical Ising model on regular lattices, together with
recent extensions of the same model on small-world Watts-Strogatz and
scale-free Albert-Barabasi complex networks is included. Other sections of the
chapter are devoted to applications of complex networks to economics, finance,
spreading of innovations, and regional trade and developments. The chapter also
reviews results involving applications of complex networks to other relevant
socioeconomic issues, including results for opinion and citation networks.
Finally, some avenues for future research are introduced before summarizing the
main conclusions of the chapter.Comment: 39 pages, 185 references, (not final version of) a chapter prepared
for Complexity and Geographical Economics - Topics and Tools, P.
Commendatore, S.S. Kayam and I. Kubin Eds. (Springer, to be published
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