The energic economy of cyberchronotopia

As social media, virtual reality, the internet of things, artificial intelligence, mobile computing, cloud computing, virtual collaboration platforms and other new technologies become an integral part of our life, more and more of us are facing a practical issue: insufficiency of psychic energy. Approaching the cyberneticization of the human condition from the perspective of psychic energy makes for a sorely needed critical intervention. This article reveals the vampiric nature of cyberspacetime, looks into vitalistic philosophy and spiritual praxes for coping strategies, and calls for homo ludens to rise above apparatuses of capture and conserve psychic energy for negentropic endeavours, psychosomatic events and spiritual awakening. It proceeds with the assumption that news about one’s autopoiesis and becoming is the most important news. Part of the motive is to demonstrate media theory and time-tested spiritual praxes as equipment for living.

Which Factors Determine the Adoption of the Internet of Things? Impacts and Benefits

This paper provides first econometric evidence on the determinants of the Internet of Things among firms and on potential performance impacts. The analysis is based on representative firm-level data from 874 German firms. A probit model and an instrumental variable regression serve as econometric approach. The results reveal that especially collaboration platforms and B2B e-commerce increase the propensity to use the Internet of Things. The results further indicate that product innovation is highest for firms jointly using the Internet of Things and collaboration platforms while a reduction of the workforce is also highest in this case. In contrast, there is no evidence for a potential impact on sales development.

Cloud Communications During the Pandemic From the Perspective of Collaboration Platforms

Purpose: The aim of this research is focused on the identification of communication patterns prior and after COVID-19 was announced and the approach to the choices that end users make in various aspects of life. Design/methodology/approach: The authors decided to execute two-step research including practical use of 4 popular collaboration platforms: Microsoft Teams, Zoom, Jitsi, Google Meet, based on the proved user experience. After a defined focus group of respondents gathered hands-on experience in a controlled manner, using the defined communication platforms, further research was carried out in the form of a survey to assess the change of behavior of respondents, considering IT tools used to support distance learning and collaboration. The research included a comparison of behavior prior the epidemic and during the epidemic period. The research covered the following aspects: how the behavior patterns of UCC use have changed across the identified areas (business, educational, private) and what are the most preferred toolsets. The following structure was applied: a short introduction to the communication platforms, definition of the research method, analysis, and discussion of the identified results. Findings: The conducted survey identified the following elements: the level of digital communication among respondents and the familiarity with different platforms have a significant role in the use and development of UCC platforms. The generic conclusion of the research was that almost all respondents have prior experience using UCC platforms. The survey has proved the 100% use of UCC cross various areas of life. Based on the research, it has been noticed that respondents tend to use one or two UCC platforms as a standard for business and private use. UCC platforms that are more widely used across different areas of life are rated as the most preferred by the respondents and include Microsoft Teams (30%) and Google Meet (23%). Research limitations/implications: The usage of non-probabilistic sampling, a relatively small sample and the usage of qualitative analysis methods were major limitations of the conducted research. Firstly, the research data was collected from students of one specialty, from one specific university. The research did not find any cultural differences in distance learning and communication. Secondly, the study uses basic statistical measures without cross analysis to enable a deeper analysis of the research. Originality/value: The presented paper is a part of the research area related to communication platforms across various areas of peoples’ life. The research was aimed at the identification of the most preferable UCC platforms and features that serve the communication purpose. The cognitive value of the paper might also be seen in the focus on a relatively narrow and homogenous group of respondents (students of e-business and digital marketing).

Towards scalable online machine learning collaborations with OpenML

Is massively collaborative machine learning possible? Can we share and organize our collective knowledge of machine learning to solve ever more challenging problems? In a way, yes: as a community, we are already very successful at developing high-quality open-source machine learning libraries, thanks to frictionless collaboration platforms for software development. However, code is only one aspect. The answer is much less clear when we also consider the data that goes into these algorithms and the exact models that are produced. A tremendous amount of work and experience goes into the collection, cleaning, and preprocessing of data and the design, evaluation, and finetuning of models, yet very little of this is shared and organized in a way so that others can easily build on it. Suppose one had a global platform for sharing machine learning datasets, models, and reproducible experiments in a frictionless way so that anybody could chip in at any time to share a good model, add or improve data, or suggest an idea. OpenML is an open-source initiative to create such a platform. It allows anyone to share datasets, machine learning pipelines, and full experiments, organizes all of it online with rich metadata, and enables anyone to reuse and build on them in novel and unexpected ways. All data is open and accessible through APIs, and it is readily integrated into popular machine learning tools to allow easy sharing of models and experiments. This openness also allows a budding ecosystem of automated processes to scale up machine learning further, such as discovering similar datasets, creating systematic benchmarks, or learning from all collected results how to build the best machine learning models and even automatically doing so for any new dataset. We welcome all of you to become a part of it.

SOME CHARACTERISTICS OF ENTREPRENEURSHIP IN MEDICINE. THE DIGITALIZATION OF THE MEDICAL SYSTEM IN ROMANIA

Entrepreneurship and medicine are in continuous growth alongside, and even if they appear to be completely different fields, entrepreneurship in medicine is becoming of remarkable interest, further highlighted by the COVID-19 pandemic. A main reason for this is its ability to use digital technologies, which are meant to improve healthcare. Applying digitalization in healthcare includes not only computer and database use (cloud computing, big data), but more complex methods such as robotics, automation, internet of things, artificial intelligence and, not lastly, collaboration platforms. Some shortcomings in respect to digitalization can be identified in the Romanian healthcare system and these may impact public health. Digitalization may contribute fundamentally to the improvement of public health by increasing performance. However, in the context of the COVID-19 pandemic, other ailments that burden the healthcare system should not be neglected (cardiovascular diseases, malignancies, etc.).

IMPROVING VIDEO CONFERENCE SECURITY WITH ARTIFICIAL INTELLIGENCE

As virtual workspaces become more sophisticated, the challenge of protecting an organization's sensitive data from accidental or intentional disclosure and compliance is becoming more challenging. With AI-powered security solutions specifically designed to monitor collaboration platforms, organizations can identify and respond to risks in real time to protect their data and that of their employees.

China's Artificial Intelligence Industry Alliance

As part of its strategy to achieve global leadership in AI, the Chinese government brings together local governments, academic institutions, and companies to establish collaboration platforms. This data brief examines the role of China’s Artificial Intelligence Industry Alliance in advancing its AI strategy, and the key players in the Chinese AI industry.

The Comparative Legislators Database

Knowledge about political representatives' behavior is crucial for a deeper understanding of politics and policy-making processes. Yet resources on legislative elites are scattered, often specialized, limited in scope or not always accessible. This article introduces the Comparative Legislators Database (CLD), which joins micro-data collection efforts on open-collaboration platforms and other sources, and integrates with renowned political science datasets. The CLD includes political, sociodemographic, career, online presence, public attention, and visual information for over 45,000 contemporary and historical politicians from ten countries. The authors provide a straightforward and open-source interface to the database through an R package, offering targeted, fast and analysis-ready access in formats familiar to social scientists and standardized across time and space. The data is verified against human-coded datasets, and its use for investigating legislator prominence and turnover is illustrated. The CLD contributes to a central hub for versatile information about legislators and their behavior, supporting individual-level comparative research over long periods.