BYOC: Strategic Choices Along the AI Compute Ownership Spectrum

Contemporary business sustainability relies on its flexibility and adaptability to unforeseen changes in societal and environmental challenges. In that sense, Speculative Design and Future Thinking offer a unique methodology for businesses to plan for the unpredictable. While those theories have been tested by decades of artistic and business applications, the recent introduction of generative AI tools widened the complexity and likelihood of answers that can be thoroughly investigated. At the same time, this enhanced capability to peek into our futures raises several concerns: How can we retain control of generative AI creative output using future thinking as a steering tool? Would that allow designers to proceed beyond strategic choices, addressing specific product development?This paper shares a case study of how future thinking was applied to provide a lighting manufacturer with design visualisations related to the lighting industry's future. HE institution offered this service (hidden for peer review) through an interdepartmental collaboration (Industrial Design and Architecture). Futures Thinking and Speculative Design apply as a methodology for consulting firms on strategic and communication choices (Mc Kinsey & Company, report, 2021). This case study explores the impact of such methodologies on choices related to product, interior, and systems design. Generative AI tools were prompted to visually interpret the forecasted scenarios through narrative discourse and creative works. the questions addressed were: What is the future of the light industry in the context of human emotions, enhanced user experience, well-being, or energy and resources?MethodsA workshop involving undergraduate and postgraduate students of the respective departments was organised in two phases: the first phase was about describing a scenario ten years in the future and conceptualising the design vision; the second phase was addressing the materialisation of light and its execution in a product or service proposal. After selecting the context, students followed methodological steps to envision future products, spaces and interactions following the four identified possible scenarios (Slaughter, 2013). In both phases, students used generative AI tools to visualise scenarios and solutions, Midjourney for the conceptual narrative, and Vizcom was used to generate illustrations of the interior/product lighting ecosystem. The latest tool does not rely solely on prompting but requires the designer to submit a sketch or a draft rendering of the proposed solution.ResultsThe design team of the participating lighting company attended each phase presentation involving products unfolding the relationship with the light in the future. The feedback received from the company appreciates the depth of the research and acknowledges the competitiveness of the identified research directions. The results achieved in the second phase of the workshop will be showcased at the IDI Shanghai yearly exhibition 2023.The format proposed could be easily adapted and implemented in a range of specific design domains, such as transportation and automotive, fashion and accessories, consumer electronics and household appliances, to name a few.

Much of the existing literature on generative AI applications is conflicting, with findings suggesting that investing in AI will lead to better organizational outcomes but also pointing out that incorporating AI may be a wasteful even counterproductive initiative. We develop a conceptual framework to characterize generative AI benefits based on the types of tasks that generative AI may be used for in management. Our work suggests that task creativity plays a key role in successful generative AI outcomes, but human validation - the extent to which a human engages in a supervisory role - is required to reap the benefits. Our conceptual framework is focused on white collar jobs and suggests that the management of generative AI is a strategic choice with important managerial implications.

Another Reality? Encounters with Generative AI in the Swedish Subject at the Upper-Secondary Level. This article presents a qualitative study that investigates how upper-secondary teachers of Swedish engage with Generative AI (GAI). Drawing on interviews with eight teachers, the researchers analysed the perceived challenges and opportunities the technology poses and how it reshapes instruction and conceptions of the subject. The interviews were reflexively thematised, and the salient themes were elaborated through an ecological framework of teacher agency, which formed the basis for a metaanalytic discussion of subject specific educational approaches and the professional spaces for action they enable. The findings show that GAI can both transform teaching and learning and challenge task design, assessment practices, and relational dynamics in the classroom. The study further demonstrates how encounters with GAI can be critically understood as temporal movements in relation to surrounding social, material, and cultural resources. It also offers nuanced perspectives on constructive didactic stances and strategic choices regarding the teacher’s role and conceptions of the subject in relation to generative AI.

The plural form refers to the adoption of a multiple-distribution strategy: franchise, management, and full ownership. This study aims to help hotel owners, operators, and researchers to understand better the superiority of the plural form over a single form and the impacts of franchising and management on a firm's overall risk and various performance variables. This study proves the plural form to be better than a single form at improving performance and lowering risk. The findings also suggest that a higher franchise percent within the mix of franchise, management, and ownership is likely to further reduce a firm's risk. A higher management percent can increase some performance measures, but it does not reduce a firm's risk. This study also suggests that the optimal proportion of franchising varies according to a firm's emphasis on a particular performance. Lodging firms could utilize the findings of this study in making strategic choices about different business forms, before expanding their number of u...

The proliferation of Generative Artificial Intelligence (Generative AI) presents a systemic challenge to the multilateral trading system, centred on its unresolved legal classification. The determination of whether Generative AI constitutes ‘goods’ under General Agreement on Tariffs and Trade (GATT) or ‘services’ under General Agreement on Trade in Services (GATS) is a strategic choice that dictates the applicable legal regime and shapes the permissibility of divergent national regulations. This article dissects this dilemma, arguing that a generalized ‘goods’ classification is legally and strategically untenable. Proceeding from a services-based framework, the analysis examines the significant tensions between emerging national AI regulations and core World Trade Organization (WTO) disciplines, particularly under GATS and the TradeRelated Aspects of Intellectual Property Rights (TRIPS) Agreement. This legal analysis further illuminates the divergent regulatory philosophies of the regulations, and the corresponding strategic responses available to different national blocs. The article concludes by advocating for international cooperation to adapt the multilateral trading system, ensuring a predictable, rulesbased environment for the digital economy.

The aims of this research are to observe, analyze, and discuss the performance of business management and strategic choice for small scale industry for food products (crispy bakes, cake and bread,soya-beans and toffu) in Palembang City. This research applies survey method by using 30 small scale business- holders as sample respondents. Data was analyzed by using quantitative and qualitative methods, such as statistical tabulation, financial ratio analysis, and SWOT analysis. The research findings as follows: 1) the small scale industry holders have simple organization and management, 2) most of them are having some problems in getting production input, absolette facilities, and low quality product; 2) the demand on small scale industrial products is still increasing continuously, 3) competition among small businesses is very tight, 4) most of them are facing lack of working capital and investment fund to expand their businesses and refinancing new production facilities To empower the owners of small scale industry for food products in Palembang City, they can choose SO, ST, WO, and WT strategies that fit to their businesses. We, researchers, recommend that the small scale industry business holders have to: 1) do more creative and eficiency in production, 2) raise fund for capital needed from foster parent company and/or local bank, 3) receive business management training program from related government agency, private institution, business association, and/or university. We also recommend that the related local government institutions have to encourage people to do fishery farming dan soybean farming. Finally, management of Primkopti in Palembang has to cooperate with BULOG in soybean supply.

In recent years, due to the influence of technological development, epidemic situation and international situation, the development of the semiconductor industry has both risks and opportunities. Compared with other semiconductor companies, NVIDIA's share price and corporate value are at a high level. This raises several questions: is the value of NVIDIA fair? Under such circumstances, what competitive advantages does it have and what strategic choices will it make? This paper will use two multiples valuation methods to evaluate NVIDIA. Through the SWOT method, the paper puts forward suggestions for the development of NVIDIA. The conclusion is that NVIDIA is overvalued, and the five pieces of advice are to transform the supply chain in Gaming market, tilt resources towards the data center, expand the business volume in the field of artificial intelligence and self-driving cars, open new segments and reduce overlap with strong competitors and maintain a good relationship with chip foundries. These suggestions are of certain reference significance to semiconductor enterprises with scientific and technological advantages.

Human vs. Generative AI: Strategic content creation mode choices for competing creators

Research on the power management of server units and server room spaces can ease the installation of a Data Center, inferring cost reduction, and environmental protection for its operation. This type of research focuses either on the restriction of power consumption of the devices of a data center, or on the minimization of energy exchange between the data center space as a whole and its environment. The work presented here focuses mainly on the latter. In particular, we attempt to estimate the effect that can infer on the energy performance of a data room, various interventions on the structural envelop of the building that hosts the data center. The performance of the data center is evaluated in this work by measuring its PUE index. Our modeling methodology includes the selection of a proper simulation tool for the creation of the digital twin, that is of a digital clone, of our real data center, and then building its thermal model via energy measurements. In this work, the researchers exploit the potential of EnergyPlus software for modelling and simulating the behavior of a data center space. The energy measurements were conducted for a long period, using low cost IoT infrastructure, in the data center space of an Educational building in Heraklion Crete. This paper describes the procedures and the results of this work.

Artificial intelligence in dermatology: Clinical promise and environmental impact.

The rapid increase in the IT infrastructure has led to demands in more Data Center Space & Power to fulfil the Information and Communication Technology (ICT) services hosting requirements. Due to this, more electrical power is being consumed in Data Centers therefore Data Center power & cooling management has become quite an important and challenging task. Direct impacting aspects affecting the power energy of data centers are power and commensurate cooling losses. It is difficult to optimise the Power Usage Efficiency (PUE) of the Data Center using conventional methods which essentially need knowledge of each Data Center facility and specific equipment and its working. Hence, a novel optimization approach is necessary to optimise the power and cooling in the data center. This research work is performed by varying the temperature in the data center through a machine learning-based linear regression optimization technique. From the research, the ideal temperature is identified with high accuracy based on the prediction technique evolved out of the available data. With the proposed model, the PUE of the data center can be easily analysed and predicted based on temperature changes maintained in the Data Center. As the temperature is raised from 19.73 oC to 21.17 oC, then the cooling load is decreased in the range 607 KW to 414 KW. From the result, maintaining the temperature at the optimum value significantly improves the Data Center PUE and same time saves power within the permissible limits.

Wireless data center network has recently received a lot of academic attention. Relevant studies have shown that Free Space Optical (FSO) technology can bring flexible topologies, high speed transmission and low energy consumption to data centers. However, it can also make the cloud data broadcast in the data center space. Some work has shown that outdoor FSO channel is vulnerable to eavesdropping attacks due to the combined attenuation effects of atmospheric turbulence and long distance transmission. Unfortunately, it is not clear the security of FSO channel in data centers and there are few studies discussing it. We study the physical layer security of FSO link in the data center indoor scenario. A suitable tapping channel model was given based on the viable mechanism of eavesdrop communication in data center. We also numerically simulate the FSO eavesdropping channel in short distance and study the impact of the relevant factors on probability of secrecy capacity. The results show that in data centers, only path attenuation of FSO also poses a channel eavesdropping risk. Under certain conditions, the distance of a few tens of meters combined with the use of shorter wavelengths can result in serious channel security risks. At the same time, the use of long wavelengths or special window wavelengths with small attenuation of FSO in FSO-based data centers has significantly improved channel security.

Increasing energy-efficient performance built into today’s servers has created significant opportunities for expanded Information and Communications Technology (ICT) capabilities. Unfortunately the power densities of these systems now challenge the data center cooling systems and have outpaced the ability of many data centers to support them. One of the persistent problems yet to be overcome in the data center space has been the separate worlds of the ICT and Facilities design and operations. This paper covers the implementation of a demonstration project where the integration of these two management systems can be used to gain significant energy savings while improving the operations staff’s visibility to the full data center; both ICT and facilities. The majority of servers have a host of platform information available to the ICT management network. This demonstration project takes the front panel temperature sensor data from the servers and provides that information over to the facilities management system to control the cooling system in the data center. The majority of data centers still use the cooling system return air temperature as the primary control variable to adjust supply air temperature, significantly limiting energy efficiency. Current best practices use a cold aisle temperature sensor to drive the cooling system. But even in this case the sensor is still only a proxy for what really matters; the inlet temperature to the servers. The paper presents a novel control scheme in which the control of the cooling system is split into two control loops to maximize efficiency. The first control loop is the cooling fluid which is driven by the temperature from the physically lower server to ensure the correct supply air temperature. The second control loop is the airflow in the cooling system. A variable speed drive is controlled by a differential temperature from the lower server to the server at the top of the rack. Controlling to this differential temperature will minimize the amount of air moved (and energy to do so) while ensuring no recirculation from the hot aisle. Controlling both of these facilities parameters by the server’s data will allow optimization of the energy used in the cooling system. Challenges with the integration of the ICT management data with the facilities control system are discussed. It is expected that this will be the most fruitful area in improving data center efficiency over the next several years.

Continuous rise in cloud computing and other web-based services propelled the data center proliferation seen over the past decade. Traditional data centers use vapor-compression-based cooling units that not only reduce energy efficiency but also increase operational and initial investment costs due to involved redundancies. Free air cooling and airside economization can substantially reduce the information technology equipment (ITE) cooling power consumption, which accounts for approximately 40% of energy consumption for a typical air-cooled data center. However, this cooling approach entails an inherent risk of exposing the ITE to harmful ultrafine particulate contaminants, thus, potentially reducing the equipment and component reliability. The present investigation attempts to quantify the effects of particulate contamination inside the data center equipment and ITE room using computational fluid dynamics (CFD). An analysis of the boundary conditions to be used was done by detailed modeling of ITE and the data center white space. Both two-dimensional and three-dimensional simulations were done for detailed analysis of particle transport within the server enclosure. An analysis of the effect of the primary pressure loss obstructions like heat sinks and dual inline memory modules inside the server was done to visualize the localized particle concentrations within the server. A room-level simulation was then conducted to identify the most vulnerable locations of particle concentration within the data center space. The results show that parameters such as higher velocities, heat sink cutouts, and higher aspect ratio features within the server tend to increase the particle concentration inside the servers.

The business consulting industry is at the cusp of a revolution mainly precipitated by strides in generative artificial intelligence systems. Drawing from the generated AI in this paper, the paper proposes a framework that integrates generative AI in consulting to improve the choice of strategy and deliver value. By examining the state-of-the-art approaches and authentic success stories, the current work reveals how AI may enhance consulting businesses, increase client satisfaction, and stimulate innovation. Due to the high speed of data processing, generative AI helps consultants break complex processes into easily understandable steps and enhance the accuracy of the forecasts and insights they provide. Moreover, by using big data and means of AI, the following characteristics are introduced: Customization of solutions specific to the needs of each particular client is provided, which improves the clients' satisfaction, and consolidation of the relation between the two parties is bolstered. The technology also helps consultants with new trends and decide on emerging trends that will allow the client to compete well. Because consulting firms are likely to incorporate AI tools in their work, they can solve the complexity that accompanies today’s business problems by being more efficient in service delivery. Finally, the paper explores potential scenarios of how generative AI could evolve and its effects on consulting businesses, pointing out that generative AI is a powerful tool from which consulting services might change the course. AI’s role will remain necessary and evolve, providing firms with what they require to improve strategic choices and create lasting client value in an increasingly fluctuating market.