Edge computing involves processing and storing data close to the data sources and users. Unlike traditional centralized data centers, edge computing brings computational power to the network's edge, ...

Model quantization bridges the gap between the computational limitations of edge devices and the demands for highly accurate models and real-time intelligent applications. The convergence of ...

Picture this scenario: At 2:37 a.m. during a storm, lightning strikes a distribution feeder line in rural Wisconsin. A massive power surge races through the distribution network. Instead of triggering ...

The emergence of DeepSeek as a transformative force in edge AI development has supply chain operators anticipating a new wave of consumer upgrades across smart devices, from smartphones to AI PCs.

New developments that will leverage a focus on cloud-native technologies, including serverless and containers, will change the level of I/O requirements. Internet egress (i.e., the on-ramps and ...

Overview Growing need for specialised AI hardware as traditional processors fall short on modern AI workloads.AI chip ...

Large language models (LLMs) such as GPT-4o and other modern state-of-the-art generative models like Anthropic’s Claude, Google's PaLM and Meta's Llama have been dominating the AI field recently.

If you want to see the future of AI, forget the server farms of Northern Virginia or the startup incubators of San Francisco. Go to a car wash company just outside Fort Lauderdale. The intelligence ...