How AI at the edge is sparking the adoption of edge computing

AI is advancing to the edge, requiring infrastructure for low latency and reliability. This report reveals AI needs real-time responses and data processing beyond cloud capabilities to truly thrive.

Edge computing brings compute power near data sources, enabling real-time AI inference, operations, model refinement, and data engineering. However, edge AI's growth faces hurdles like fragmented ecosystems, legacy systems, hardware requirements, and market entry challenges.

Ecosystems that promote collaboration can address these barriers, helping AI and edge firms to quickly market solutions, drive edge adoption, and expand market

Vendor:: Red Hat and Intel
Posted:: Mar 14, 2024
Published:: Mar 14, 2024
Format:: HTML
Type:: White Paper

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