Which Emerging Advancements Are Driving the Growth of Edge Artificial Intelligence Accelerators?
Expanding Internet of Things applications drive growth
Overview
Specialized edge artificial intelligence (AI) hardware that enables quick deep learning on-device has become essential due to the rising need for real-time deep learning workloads. Additionally, a cloud-based AI method cannot ensure data privacy, low latency, or offer high bandwidth. As a result, many AI workloads are shifting to the edge, increasing the demand for specialized AI hardware for on-device machine learning inference.
Which technological factors are propelling the edge AI accelerator landscape?
How are chip manufacturers improving processing speed while reducing power consumption?
Which regions pose as promising landscapes for edge AI accelerators?
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