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Deep Learning Frameworks refer to specialized software libraries for designing, building, and training artificial neural networks, which are a core component of advanced AI systems. These frameworks simplify and accelerate deep learning tasks by providing pre-built components, tools, and functions for creating complex neural network architectures and managing large datasets. By using these frameworks, developers can build robust, scalable, and high-performance AI models that can be deployed in various applications across different industries, including Robotics, autonomous systems, computer vision, natural language processing, and more. In the hierarchy Technology/Artificial Intelligence/Robotics, Deep Learning Frameworks represent a collection of advanced tools and techniques for creating intelligent machines and systems, leveraging the power of AI algorithms and neural networks to enable new capabilities and functionalities in Robotics and other related fields.