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Inhaltsangabe
Self-evolving AI systems represent a new stage in the development of intelligent technology, where a system is designed not only to perform a task but also to improve its own performance over time. Unlike conventional software, which remains largely static unless a developer manually changes it, a self-evolving system is built to absorb new information, evaluate its own outcomes, and adjust its behavior in response to changing conditions. This makes the system more dynamic, more resilient, and more capable of operating in complex real-world environments where patterns rarely stay fixed for long.The core idea behind such systems is that intelligence should not stop at deployment. In traditional machine learning workflows, a model is trained, tested, and then placed into use, often with the expectation that it will continue to function adequately until the next maintenance cycle. In self-evolving AI, however, deployment is not the end of learning but the beginning of a longer process of adaptation.
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Über die Autorin bzw. den Autor
Rahul. J is working as Assistant Prof. in Department of AI&DS in Agni college of technology.S. Gayathri is working as Assistant Prof. in Department of AI&DS in Agni college of technology.Dr S. Thylashri is working as Assistant Prof. senior grade in Department of CSE in Vel Tech Rangarajan Dr Sagunthala R&D institute of science and technology.
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Paperback. Zustand: new. Paperback. Self-evolving AI systems represent a new stage in the development of intelligent technology, where a system is designed not only to perform a task but also to improve its own performance over time. Unlike conventional software, which remains largely static unless a developer manually changes it, a self-evolving system is built to absorb new information, evaluate its own outcomes, and adjust its behavior in response to changing conditions. This makes the system more dynamic, more resilient, and more capable of operating in complex real-world environments where patterns rarely stay fixed for long.The core idea behind such systems is that intelligence should not stop at deployment. In traditional machine learning workflows, a model is trained, tested, and then placed into use, often with the expectation that it will continue to function adequately until the next maintenance cycle. In self-evolving AI, however, deployment is not the end of learning but the beginning of a longer process of adaptation. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9786630019155
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Self-evolving AI systems represent a new stage in the development of intelligent technology, where a system is designed not only to perform a task but also to improve its own performance over time. Unlike conventional software, which remains largely static unless a developer manually changes it, a self-evolving system is built to absorb new information, evaluate its own outcomes, and adjust its behavior in response to changing conditions. This makes the system more dynamic, more resilient, and more capable of operating in complex real-world environments where patterns rarely stay fixed for long.The core idea behind such systems is that intelligence should not stop at deployment. In traditional machine learning workflows, a model is trained, tested, and then placed into use, often with the expectation that it will continue to function adequately until the next maintenance cycle. In self-evolving AI, however, deployment is not the end of learning but the beginning of a longer process of adaptation. Bestandsnummer des Verkäufers 9786630019155
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SENTIENT PIPELINES: SELF EVOLVING AI SYSTEMS
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Taschenbuch. Zustand: Neu. SENTIENT PIPELINES: SELF EVOLVING AI SYSTEMS | Rahul J (u. a.) | Taschenbuch | Englisch | 2026 | LAP LAMBERT Academic Publishing | EAN 9786630019155 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand. Bestandsnummer des Verkäufers 136021419
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Self-evolving AI systems represent a new stage in the development of intelligent technology, where a system is designed not only to perform a task but also to improve its own performance over time. Unlike conventional software, which remains largely static unless a developer manually changes it, a self-evolving system is built to absorb new information, evaluate its own outcomes, and adjust its behavior in response to changing conditions. This makes the system more dynamic, more resilient, and more capable of operating in complex real-world environments where patterns rarely stay fixed for long.The core idea behind such systems is that intelligence should not stop at deployment. In traditional machine learning workflows, a model is trained, tested, and then placed into use, often with the expectation that it will continue to function adequately until the next maintenance cycle. In self-evolving AI, however, deployment is not the end of learning but the beginning of a longer process of adaptation. 160 pp. Englisch. Bestandsnummer des Verkäufers 9786630019155
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ISBN 13: 9786630019155
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Paperback. Zustand: new. Paperback. Self-evolving AI systems represent a new stage in the development of intelligent technology, where a system is designed not only to perform a task but also to improve its own performance over time. Unlike conventional software, which remains largely static unless a developer manually changes it, a self-evolving system is built to absorb new information, evaluate its own outcomes, and adjust its behavior in response to changing conditions. This makes the system more dynamic, more resilient, and more capable of operating in complex real-world environments where patterns rarely stay fixed for long.The core idea behind such systems is that intelligence should not stop at deployment. In traditional machine learning workflows, a model is trained, tested, and then placed into use, often with the expectation that it will continue to function adequately until the next maintenance cycle. In self-evolving AI, however, deployment is not the end of learning but the beginning of a longer process of adaptation. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9786630019155
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