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The Impact of Technology on the US Energy Market

Hoskin would visit nearly a dozen different Canadian homes, moving about Ontario and Quebec before arriving in the "more cultured, more civilised" Vancouver. He became a Canadian citizen and continued to create books, each one more absurd than the last. Rampa allegedly flew as an air ambulance pilot in World War II, evaded capture and torture, and fled a prison camp near Hiroshima on the day the bomb was dropped. In Vancouver, Hoskin stayed in a West End hotel. According to his secretary's self-published memoir, he liked the waterfront vistas but found Vancouver difficult to navigate. He couldn't recreate The Third Eye's success; it had been difficult to find a home that could accommodate his cats, and health difficulties required the use of a wheelchair in an inhospitable metropolis. Hoskin became more reclusive as his writings expanded to include aliens, prophecies about future conflicts, and previously unreported escapades of Christ. Hoskin moved again, this ti...
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The Role of AI in Enhancing US Business Processes

Research suggests that intelligence can help organizations achieve their goals (Braganza et al. Chen et al.  Côrte-Real et al. Ghasemaghaei, Hassanein, and Turel 2017; Wamba et al. The Textile and Apparel business can benefit from Artificial Intelligence, however it may face implementation hurdles. To meet these difficulties, manufacturers must establish resources, capabilities, intelligence, and knowledge management. Our findings indicate that organizations should prioritize intangible resources while building AI capabilities.

While large organizations may easily acquire tangible resources like

Hardware and infrastructure, hiring experienced individuals to build and run AI-based projects presents significant obstacles. Organizations should prioritize building talent resources that are easily obtained, taking into account the complexity of technology. The study aligns with the theoretical frameworks of RBV and DCT, but highlights the need for intelligence and knowledge management to effectively integrate AI in T&A manufacturing. The study suggests that integrating RBV, DCT, and knowledge-based perspectives is crucial for addressing AI implementation issues. The survey found that employees have a negative impression of AI, believing it will replace their skills. Many in the industrial business believe that AI will replace humans and lead to job losses. Manufacturers acknowledge the benefits of AI, but are concerned about its potential impact on unemployment rates. To mitigate the influence of technology on job security and employment levels, organizations and governments might focus on upgrading and diversifying people's abilities. According to Braganza et al. (2017), DCT allows organizations to continuously evolve by reconfiguring new capacities to achieve outcomes.Our analysis highlights the need for expanding AI capabilities in agile manufacturing. DCT is crucial in the agile T&A business, since manufacturers must respond to changing client needs, short product lifecycles, and design challenges. 

The study's conclusions have some practical consequences

AI has the ability to impact production, marketing, retail, and customer behavior in the fashion industry. Our study identifies various hurdles for deploying AI, including data-related concerns, intangible resource shortages, explainability of outcome models, a lack of experienced personnel, and an AI-oriented management culture. We identified that data-related issues and a lack of qualified human resources had a greater impact due to a lack of dependable sources and a high volume of data. Inadequate training facilities limit the organization's potential. capability, making a significant theoretical and practical contribution. Future research could use a quantitative method to investigate the influence of disruptive information technologies on the Textile and Apparel business. After feeding the big data into the AIThe manufacturing industry is experiencing widespread AI due to the convergence of computational, machine-learning, technological, statistical, and research developments. AI is widely seen as a disruptive technology with substantial economic and cognitive implications for manufacturers.Although the tool generates an outcome model, users may disagree with it as there is no explanation to change their view. In the industrial industry, routine work is acceptable. However, when it comes to creative design, users/adopters may disagree, creating a bottleneck, especially when projecting customer preferences.

Furthermore the biasness of any result model is strongly connected to data quality

Another challenge is to ensure explainability.This paper examines the role of AI as a dynamic capability in the T&A business, highlighting the significance of Big Data and Business Analytics (BDBA) in improving agile manufacturing procedures. The study's findings will improve our understanding of AI's impact on agile production and operations management, especially in the T&A business. Fashion serves a useful purpose and plays a significant role in human lives. It expresses and investigates emotions and creativity. The industry's dynamic nature necessitates adaptation to new technologies. AI's various skills are transforming the T&A business. Each application area, technique, and tool has unique strengths and disadvantages while executing similar activities for various goals. AI capabilities are often used to solve specific demands, such as image and language processing. Before using AI, it's crucial to thoroughly understand the approaches and tools. AI, particularly machine learning and deep learning, can analyze data and predict outcomes beyond human comprehension. The T&A industry can benefit from increased processing power, open-source machine and deep learning models, specialized hardware, system architecture, and cloud technology to enhance AI capabilities. Manufacturers should recognize the value of competent and knowledgeable workers as intangible resources and capabilities. Integrating RBV, capability, and knowledge-based views offers a holistic method to implementing AI as a dynamic.

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