Edge AI: Bringing Intelligence to the Periphery
Keywords:
Edge AI, AI Privacy and Security, AI Scalability, AI PrivacyAbstract
Edge AI is rapidly transforming the way we interact with technology, bringing sophisticated artificial intelligence capabilities directly to the periphery of networks and devices. By enabling AI processing to occur locally, at the edge of the network rather than relying solely on centralized cloud infrastructure, Edge AI offers significant advantages in terms of latency, privacy, and scalability.
References
. IDC. (2021). The Rise of Edge AI: A Market Analysis and Forecast for 2021-2025. Retrieved from https://www.idc.com/
. IEEE Spectrum. (2020). Privacy-Preserving AI: How Edge Computing Keeps Data Secure. Retrieved from https://spectrum.ieee.org/
. Cisco. (2021). Scaling AI at the Edge: Strategies for Managing Data and Processing. Retrieved from https://www.cisco.com/
. NVIDIA. (2020). AI Accelerators: Enhancing Edge Device Capabilities. Retrieved from https://www.nvidia.com/
. Google AI. (2021). TensorFlow Lite: Deploying AI Models on Edge Devices. Retrieved from Google AI.
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©2023. COMPUSOFT: AN INTERNATIONAL OF ADVANCED COMPUTER TECHNOLOGY by COMPUSOFT PUBLICATION is licensed under a Creative Commons Attribution 4.0 International License. Based on a work at COMPUSOFT: AN INTERNATIONAL OF ADVANCED COMPUTER TECHNOLOGY. Permissions beyond the scope of this license may be available at Creative Commons Attribution 4.0 International Public License.
