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Добірка наукової літератури з теми "AI Strategy"

Автор: Grafiati

Опубліковано: 7 червня 2025

Оновлено: 2 серпня 2025

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Статті в журналах з теми "AI Strategy"

笹嶋, 宗彦. "AI戦略（AI Strategy）". Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 35, № 2 (2023): 25. http://dx.doi.org/10.3156/jsoft.35.2_25_1.

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Vykhodets, R. S. "China’s AI Strategy." EURASIAN INTEGRATION: economics, law, politics 16, no. 2 (2022): 140–47. http://dx.doi.org/10.22394/2073-2929-2022-02-140-147.

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Анотація:

The present study is devoted to the consideration of the peculiarities of Chinese policy in the field of artificial intelligence (AI) in the context of global technological confrontation.Aim. To identify the key areas of China’s AI strategy, as well as to identify priority areas of state policy in this area.Tasks. To analyze the results of the development of the AI industry in China, to consider the main economic indicators, achievements in the creation of computing infrastructure, the development of its own research and development in the field of AI, to identify the main provisions of the ke

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Vykhodets, R. S. "The EAEU’s AI Strategy." EURASIAN INTEGRATION: economics, law, politics 16, no. 3 (2022): 106–17. http://dx.doi.org/10.22394/2073-2929-2022-03-106-117.

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This study is devoted to the consideration of the peculiarities of the policy of the EAEU states in the field of artificial intelligence (AI) in the context of global technological confrontation.Aim. To identify the key directions of the strategy of the EAEU member states in the field of AI, as well as to identify priority policy directions in this area at the union level.Tasks. To analyze the results of the development of the AI industry in Armenia, Belarus, Kazakhstan, Kyrgyzstan and Russia, to consider the main economic indicators, achievements in the creation of computing infrastructure, t

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Miyamoto, Michiko. "Measuring AI Governance, AI Adoption and AI Strategy of Japanese Companies." International Journal of Membrane Science and Technology 10, no. 1 (2023): 649–57. http://dx.doi.org/10.15379/ijmst.v10i1.2627.

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Purpose: This study aims to measure the level of AI governance and AI adoption among Japanese companies. Theoretical Framework: The research investigates the extent to which Japanese companies have implemented AI governance frameworks and the degree of AI adoption in their operations. The study also explores the relationship between AI governance, AI adoption, and AI strategy, providing insights into the factors that influence successful AI implementation. Design / Methodology / Approach: a survey questionnaire was administered to a representative sample of Japanese companies across various in

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MIYAKE, Youichiro. "Introduction to Strategy Game AI." Journal of Digital Games Research 15, no. 1 (2022): 31. http://dx.doi.org/10.9762/digraj.15.1_31.

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Tyler, Neil. "UK Organisations Lack AI Strategy." New Electronics 51, no. 20 (2018): 8. http://dx.doi.org/10.12968/s0047-9624(23)60714-x.

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Ma, Haoyuan. "Marketing Strategy of Open AI." Advances in Economics, Management and Political Sciences 73, no. 1 (2024): None. http://dx.doi.org/10.54254/2754-1169/73/20231500.

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In the current society, the field of artificial intelligence is developing rapidly. In the field of artificial intelligence, OpenAI can be said to be one of the best, which promotes technological progress and market dynamic changes. This article discusses OpenAI's marketing strategy in depth, with the aim of understanding its formulation, evolution, and impact on the artificial intelligence industry. Through analysis, this paper examines the company's initial marketing efforts, branding and messaging strategies, and the role of collaborations and partnerships in expanding its market presence.

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Kobelev, Sergei Veniaminovich. "Conceptual model of AI-transformation strategy." Финансы и управление, no. 4 (April 2024): 61–78. http://dx.doi.org/10.25136/2409-7802.2024.4.72461.

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The research subject is the problem of the lack of a systematic approach to developing and implementing AI transformation strategies for business. The author examines differences between digital and AI transformation processes, specific requirements for data, technologies, and personnel competencies in artificial intelligence implementation, as well as ethical aspects of AI use in business processes. Special attention is paid to systematizing existing approaches to AI transformation and identifying their limitations in modern conditions. The paper explores key success factors of AI implementat

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Saputra, Beny, Hartati Hartati, and Olivér Bene. "Hungary’s AI Strategy: Lessons for Indonesia’s AI Legal Framework Enhancement." Jambe Law Journal 7, no. 1 (2024): 25–58. http://dx.doi.org/10.22437/home.v7i1.325.

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This study analyses Hungary's approach to regulating artificial intelligence (AI) by analyzing their AI Strategy (2020-2030) and provides insights for improving Indonesia's legal framework. In Hungary, although there is no dedicated legislation for artificial intelligence (AI), the country places a high importance on adhering to current regulations to regulate AI technologies. This paper does a comparative analysis to evaluate the influence of Hungary's approach on the advancement of artificial intelligence (AI), the methods used to enforce regulations, the ethical principles followed, the saf

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Zhao, Yinuo. "Research on momentum strategy and contrarian strategy in AI stock prediction." Applied and Computational Engineering 29, no. 1 (2023): 125–32. http://dx.doi.org/10.54254/2755-2721/29/20231207.

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The emergence of ChatGPT has significantly enhanced the recognition and acceptance of artificial intelligence concept stocks within the Chinese stock market. Nevertheless, the short- and long-term fluctuations in the prices of AI companies remain uncertain. Therefore, the purpose of this research is to determine optimal strategy for evaluating the suitability of the contrarian strategy versus the momentum strategy in predicting the stock prices of AI concept stocks in the Chinese stock market. Based on a cross-comparison of the Chinese financial data sources iFinD and Wind Economic Database (E

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Дисертації з теми "AI Strategy"

Dahlbom, Anders. "An adaptive AI for real-time strategy games." Thesis, University of Skövde, School of Humanities and Informatics, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-908.

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<p>In real-time strategy (RTS) games, the human player faces tasks such as resource allocation, mission planning, and unit coordination. An Artificial Intelligence (AI) system that acts as an opponent against the human player need to be quite powerful, in order to create one cohesive strategy for victory. Even though the goal for an AI system in a computer game is not to defeat the human player, it might still need to act intelligently and look credible. It might however also need to provide just enough difficulty, so that both novice and expert players appreciates the game. The behavior of co

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Svensson, Marcus. "Dynamic Strategy in Real-Time Strategy Games : with the use of finite-state machines." Thesis, Linnéuniversitetet, Institutionen för datavetenskap (DV), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-39604.

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Developing real-time strategy game AI is a challenging task due to that an AI-player has to deal with many different decisions and actions in an ever changing complex game world. Humans have little problem when it comes to dealing with the complexity of the game genre while it is a difficult obstacle to overcome for the computer. Adapting to the opponents strategy is one of many things that players typically have to do during the course of a game in the real-time strategy genre. This report presents a finite-state machine based solution to the mentioned problem and implements it with the help

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Karlsson, Robin. "Cooperative Behaviors BetweenTwo Teaming RTS Bots in StarCraft." Thesis, Blekinge Tekniska Högskola, Institutionen för datalogi och datorsystemteknik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-10955.

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Анотація:

Context. Video games are a big entertainment industry. Many video games let players play against or together. Some video games also make it possible for players to play against or together with computer controlled players, called bots. Artificial Intelligence (AI) is used to create bots. Objectives. This thesis aims to implement cooperative behaviors between two bots and determine if the behaviors lead to an increase in win ratio. This means that the bots should be able to cooperate in certain situations, such as when they are attacked or when they are attacking. Methods. The bots win ratio wi

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ívarsson, Óli. "Improved Combat Tactics of AI Agents in Real-Time Strategy Games Using Qualitative Spatial Reasoning." Thesis, University of Skövde, School of Humanities and Informatics, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-956.

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<p>Real-time strategy (RTS) games constitute one of the largest game genres today and have done so for the past decade. A central feature of real-time strategy games is opponent AI which is suggestively the “last frontier” of game development because the focus of research has primarily been on other components, graphics in particular. This has led to AI research being largely ignored within the commercial game industry but several methods have recently been suggested for improving the strategic ability of AI agents in real-time strategy games.</p><p>The aim of this project is to evaluate how a

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Salis, Francesca <1995&gt. "Digital strategy: la cultura ai tempi del Covid-19. Analisi del fenomeno e casi studio." Master's Degree Thesis, Università Ca' Foscari Venezia, 2021. http://hdl.handle.net/10579/19170.

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Analisi del fenomeno di accelerazione subito dalla digital strategy all’interno del settore culturale, durante la crisi sanitaria. Il capitolo I si incentra sulla situazione internazionale: le perdite subite dal settore, dati e statistiche sull’impiego del digitale da parte degli enti, sondaggi e considerazioni sul cambiamento delle strategie comunicative. Il capitolo II è un focus sul percorso nazionale, la digitalizzazione prima e dopo il Covid, le iniziative virtuali degli istituti culturali, rapporto con i sistemi informatici tra enti e pubblico fruitore (raccolta di dati statistici). I ca

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Butt, Rehman. "Performance Comparison of AI Algorithms : Anytime Algorithms." Thesis, Blekinge Tekniska Högskola, Avdelningen för programvarusystem, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-5845.

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Анотація:

Commercial computer gaming is a large growing industry that already has its major contributions in the entertainment industry of the world. One of the most important among different types of computer games are Real Time Strategy (RTS) based games. RTS games are considered being the major research subject for Artificial Intelligence (AI). But still the performance of AI in these games is poor by human standards due to some fundamental AI problems those require more research to be better solved for the RTS games. There also exist some AI algorithms those can help us solve these AI problems. Anyt

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Viro, Sebastian. "Using statistics and game knowledge to create better bots in Dota 2." Thesis, Malmö universitet, Fakulteten för teknik och samhälle (TS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:mau:diva-43442.

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Анотація:

Multiplayer online battle arena (MOBA) games and games in general offer developers opportunities to design and test AI to further push research within the area. MOBA is a genre that has seen an increase in popularity during recent years alongside a rapidly growing esports scene. The game's main purpose is ultimately to be enjoyed and played by human players, who often come up with and are encouraged to create their own strategies in order to beat the game or win out over their opponents. This thesis will explore how mimicking human behavior in AI and using statistics from human players can b

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Berg, Jens, and Tony Högye. "Reifying Game Design Patterns : A Quantitative Study of Real Time Strategy Games." Thesis, Uppsala universitet, Institutionen för speldesign, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-324158.

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Communicating design is in many aspects a difficult process. Game design is not only directives on look and feel, but also carries intentionality. To properly convey intentionality, a common abstract vocabulary is a well-established method for expressing design. Game design patterns are an attempt to formalize and establish such a vocabulary. Game design patterns are a debated tool and this paper aims to examine the practical application of a pattern through a quantitative study in order to strengthen the potential for a more cohesive definition of the term. This is done by first establishing

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Válek, Lukáš. "Multiagentní podpora pro vytváření strategických her." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2018. http://www.nusl.cz/ntk/nusl-413329.

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Анотація:

This thesis is focused on design of framework for creation an articial opponents in strategy games. We will analyze different types of strategy games and artificial intelligence systems used in these types of games. Next we will describe problems, which can occur in these systems and why agent-based systems makes better artificial opponents. Next we will use knowledge from this research to design and implement framework, which will act as support for creating an artificial intelligence in strategy games.

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Válek, Lukáš. "Rozhraní pro propojení strategických her s multiagentními systémy." Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2019. http://www.nusl.cz/ntk/nusl-403186.

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Книги з теми "AI Strategy"

Mahendra, Adhiguna. AI Startup Strategy. Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9502-1.

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D, Quagliarella, ed. Genetic algorithms and evolution strategy in engineering and computer science: Recent advances and industrial applications. J. Wiley & Sons, 1998.

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Ujwary-Gil, Anna, and Anna Florek-Paszkowska. AI, Analytics and Strategic Decision Making. Routledge, 2025. https://doi.org/10.4324/9781003507840.

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Fabio, Roia, ed. Strategie efficaci per il contrasto ai maltrattamenti e allo stalking: Aspetti giuridici e criminologici. FrancoAngeli, 2011.

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Giacomo, Enzo Di. Il marxismo italiano: Analisi e critica : con particolare riferimento ai problemi dell'organizzazione e della strategia ai fini della trasformazione in Gramsci, Togliatti e Berlinguer. Lalli, 1988.

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Doni, Manuela, ed. Strumenti e strategie della comunicazione scritta in Europa fra Medioevo ed Età Moderna. Firenze University Press, 2017. http://dx.doi.org/10.36253/978-88-6453-612-5.

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Il tema della comunicazione scritta che attraversa i saggi storici qui raccolti, non riguarda lo studio del mezzo e della sua storia, bensì i metodi applicati alla realizzazione di scritture o iniziative editoriali per il conseguimento di obiettivi specifici sotto tale profilo. Scrittura ed editoria sono i due poli intorno ai quali ruotano i vari contributi, il cui taglio risponde alle linee di un progetto teso a sondare l’intenzione sottesa all’operato di autori ed editori impegnati nel trasmettere non tanto o non soltanto notizie, ma soprattutto contenuti: dal campo religioso a quello cultur

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Busacca, Maurizio, and Alessandro Caputo. Valutazione, apprendimento e innovazione nelle azioni di welfare territoriale. Edizioni Ca' Foscari, 2020. http://dx.doi.org/10.30687/978-88-6969-408-0.

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Tra il 2017 e 2019 i due Autori hanno condotto una ricerca valutativa sui Piani Giovani della Regione del Veneto e sulle politiche giovanili locali. La ricerca è stata l’occasione per approfondire le modalità di funzionamento di coalizioni locali di welfare organizzate in modo reticolare e per coinvolgerle nella progettazione partecipata di un sistema di valutazione dell’impatto sociale. Lo SROI Explore è un mix-method che cerca di rispondere ai problemi storici della valutazione nell’ambito delle politiche sociali attraverso una strategia partecipativa e l’ancoraggio alle teorie incorporate n

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Ammannati, Francesco, ed. Assistenza e solidarietà in Europa Secc. XIII-XVIII / Social assistance and solidarity in Europe from the 13th to the 18th Centuries. Firenze University Press, 2013. http://dx.doi.org/10.36253/978-88-6655-367-0.

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Il periodo compreso fra Medioevo ed Età Moderna registra una significativa evoluzione del welfare, attraverso il consolidamento e la specializzazione di istituzioni nate o trasformatesi con la precisa funzione di fare attività di solidarietà e assistenza. È attorno a queste istituzioni che si sono concentrate le ricerche raccolte in questo volume, con l’obiettivo di delinearne la nascita e l’evoluzione, ma anche le fonti di finanziamento e autofinanziamento, le strategie e le modalità di acquisizione delle risorse, la gestione e la evoluzione dei patrimoni, l’organizzazione funzionale e i cost

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JONES, Phillip C. Business Cases for Ai: Authority Manual for AI Business Strategy. Independently Published, 2022.

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Mitson, Justin. Corporate Strategy in the Age of AI. Indy Pub, 2023.

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Частини книг з теми "AI Strategy"

Sharma, Rohan. "AI Strategy." In AI and the Boardroom. Apress, 2024. http://dx.doi.org/10.1007/979-8-8688-0796-1_6.

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Mahendra, Adhiguna. "AI Product Strategy." In AI Startup Strategy. Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9502-1_5.

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Sharma, Rohan. "AI Talent Strategy." In AI and the Boardroom. Apress, 2024. http://dx.doi.org/10.1007/979-8-8688-0796-1_15.

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Mahendra, Adhiguna. "AI Startup Landscape." In AI Startup Strategy. Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9502-1_2.

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Mahendra, Adhiguna. "Go-to-Market Strategy for an AI Startup." In AI Startup Strategy. Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9502-1_9.

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Mahendra, Adhiguna. "Product-Market Validation for AI-First SaaS." In AI Startup Strategy. Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9502-1_3.

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Mahendra, Adhiguna. "Fundamental of AI Startups." In AI Startup Strategy. Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9502-1_1.

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Mahendra, Adhiguna. "AI Startup Exit Strategy." In AI Startup Strategy. Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9502-1_10.

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Mahendra, Adhiguna. "Building an AI Platform." In AI Startup Strategy. Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9502-1_8.

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Mahendra, Adhiguna. "Human-Centered AI Developer Experience Design." In AI Startup Strategy. Apress, 2023. http://dx.doi.org/10.1007/978-1-4842-9502-1_7.

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Тези доповідей конференцій з теми "AI Strategy"

Horwitch, Mel. "The AI Challenge for National Technology Strategy." In 2024 Portland International Conference on Management of Engineering and Technology (PICMET). IEEE, 2024. http://dx.doi.org/10.23919/picmet64035.2024.10653430.

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Xi, Jingyi, Xiaoyin Hu, and Duo Xiao. "Energy Management Strategy for Fuel Cell Hybrid Emergency Power System based on Deep Reinforcement Learning." In 2024 4th International Symposium on AI (ISAI). IEEE, 2024. http://dx.doi.org/10.1109/isai63299.2024.00018.

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Satapathy, Shashank Mouli, Debashreet Das, Abhyudoy Chaki, Hriday Agarwal, and Vidit Shah. "A Hybrid Quantum Particle Swarm Optimization based on Differential Evolution Strategy for Healthcare Applications." In 2025 AI-Driven Smart Healthcare for Society 5.0. IEEE, 2025. https://doi.org/10.1109/ieeeconf64992.2025.10963147.

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Chiatsé Mireille Patricia, Anassin. "Adaptability of data security in a changing environment: a strategy based on artificial intelligence." In International Conference on AI-generated Content (AIGC 2024), edited by Duoqian Miao and Feng Zhao. SPIE, 2025. https://doi.org/10.1117/12.3065204.

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Liu, Liang, Yuxiang Chen, Xun Shao, Kailin Wang, and Yu Huang. "Adaptive load balancing Strategy for VR Microservices with Edge AI." In 2024 7th International Conference on Electronics Technology (ICET). IEEE, 2024. http://dx.doi.org/10.1109/icet61945.2024.10672636.

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Dutta, Arijit, Floriano De Rango, Teresa Le Feudo, and Claudia Roberta Calidonna. "An AI-based Cost-Effective Solar Energy Resource Estimation Strategy." In 2025 15th International Renewable Energy Congress (IREC). IEEE, 2025. https://doi.org/10.1109/irec64614.2025.10926767.

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Han, Yuna, Simon Shim, Deva Kumar Gajulamandyam, and Hangbae Chang. "Prompt-Based Generation Strategy for Imbalanced Information Security Rating Dataset Augmentation." In 2024 International Conference on AI x Data and Knowledge Engineering (AIxDKE). IEEE, 2024. https://doi.org/10.1109/aixdke63520.2024.00029.

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Zhao, Weibin, Zhuqiao Li, Xitong Mai, and Ruomei Huang. "Anti-counterfeiting noise addition strategy model for voice cloning." In 2024 5th International Conference on Computer, Big Data and Artificial Intelligence (ICCBD+AI). IEEE, 2024. https://doi.org/10.1109/iccbd-ai65562.2024.00066.

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Singla, Lalit, Anju B. Nandrajog, Navjot Singh, Komal Ahuja, and Shiva Mehta. "AI and Consumer Behavior: Innovations in Marketing Strategy and Consumer Engagement." In 2024 15th International Conference on Computing Communication and Networking Technologies (ICCCNT). IEEE, 2024. http://dx.doi.org/10.1109/icccnt61001.2024.10725771.

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Zheng, Kouquan, Feng Jing, Linsheng Zhang, Le Zhao, and Yijun Zhang. "Research on Panoramic Video Download Strategy Based on PI Controller." In 2024 5th International Conference on Computer, Big Data and Artificial Intelligence (ICCBD+AI). IEEE, 2024. https://doi.org/10.1109/iccbd-ai65562.2024.00015.

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Звіти організацій з теми "AI Strategy"

Osborne, Cailean. Charting Strategic Directions for Global Collaboration in Open Source AI: Key Takeaways from the GOSIM Open Source AI Strategy Forum. The Linux Foundation, 2025. https://doi.org/10.70828/kcrf4119.

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The 2025 GOSIM Open Source AI Strategy Forum took place on May 5, 2025 in Paris, bringing together experts from industry, academia, civil society, and open source communities. The group represented countries and organizations from around the world, sharing their perspectives on the critical challenges facing global collaboration in open source AI. This report summarizes the key highlights from the forum and pathways forward.

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Mishra, Nayan Chandra. India needs a strategy reboot after US AI controls. East Asia Forum, 2025. https://doi.org/10.59425/eabc.1741125600.

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Buchanan, Ben. The AI Triad and What It Means for National Security Strategy. Center for Security and Emerging Technology, 2020. http://dx.doi.org/10.51593/20200021.

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One sentence summarizes the complexities of modern artificial intelligence: Machine learning systems use computing power to execute algorithms that learn from data. This AI triad of computing power, algorithms, and data offers a framework for decision-making in national security policy.

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Hwang, Tim. Shaping the Terrain of AI Competition. Center for Security and Emerging Technology, 2020. http://dx.doi.org/10.51593/20190029.

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How should democracies effectively compete against authoritarian regimes in the AI space? This report offers a “terrain strategy” for the United States to leverage the malleability of artificial intelligence to offset authoritarians' structural advantages in engineering and deploying AI.

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Goode, Kayla, and Heeu Millie Kim. Indonesia’s AI Promise in Perspective. Center for Security and Emerging Technology, 2021. http://dx.doi.org/10.51593/2021ca001.

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The United States and China are keeping an eye on Indonesia’s artificial intelligence potential given the country’s innovation-driven national strategy and flourishing AI industry. China views Indonesia as an anchor for its economic, digital, and political inroads in Southeast Asia and has invested aggressively in new partnerships. The United States, with robust political and economic relations rooted in shared democratic ideals, has an opportunity to leverage its comparative advantages and tap into Indonesia’s AI potential through high-level agreements.

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Pasupuleti, Murali Krishna. AI in Global Strategy: Harnessing Game Theory and Reinforcement Learning for Diplomatic Innovation. National Education Services, 2025. https://doi.org/10.62311/nesx/rr125.

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Abstract: This article explores the integration of game theory and reinforcement learning (RL) in the context of global diplomacy, emphasizing the transformative potential of strategic AI in international relations. It provides an in-depth analysis of how game theory principles, such as Nash equilibrium and cooperative strategies, are leveraged by AI to model and optimize diplomatic interactions. The Article explains how reinforcement learning enables AI systems to learn and adapt strategies over time, improving their effectiveness in negotiation and conflict resolution. Through case studies a

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Arnold, Zachary, and Ngor Luong. China’s Artificial Intelligence Industry Alliance. Center for Security and Emerging Technology, 2021. http://dx.doi.org/10.51593/20200094.

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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.

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Buchanan, Ben. A National Security Research Agenda for Cybersecurity and Artificial Intelligence. Center for Security and Emerging Technology, 2020. http://dx.doi.org/10.51593/2020ca001.

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Machine learning advances are transforming cyber strategy and operations. This necessitates studying national security issues at the intersection of AI and cybersecurity, including offensive and defensive cyber operations, the cybersecurity of AI systems, and the effect of new technologies on global stability.

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Fedasiuk, Ryan, Jennifer Melot, and Ben Murphy. Harnessed Lightning: How the Chinese Military is Adopting Artificial Intelligence. Center for Security and Emerging Technology, 2021. http://dx.doi.org/10.51593/20200089.

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This report examines nearly 350 artificial intelligence-related equipment contracts awarded by the People’s Liberation Army and state-owned defense enterprises in 2020 to assess how the Chinese military is adopting AI. The report identifies China’s key AI defense industry suppliers, highlights gaps in U.S. export control policies, and contextualizes the PLA’s AI investments within China’s broader strategy to compete militarily with the United States.

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Hannas, William, Huey-Meei Chang, Daniel Chou, and Brian Fleeger. China's Advanced AI Research: Monitoring China's Paths to "General" Artificial Intelligence. Center for Security and Emerging Technology, 2022. http://dx.doi.org/10.51593/20210064.

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China is following a national strategy to lead the world in artificial intelligence by 2030, including by pursuing “general AI” that can act autonomously in novel circumstances. Open-source research identifies 30 Chinese institutions engaged in one or more of this project‘s aspects, including machine learning, brain-inspired AI, and brain-computer interfaces. This report previews a CSET pilot program that will track China’s progress and provide timely alerts.

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