Explore AI at the edge with Red Hat
The growing need for real-time AI processing at the edge
Three key trends are transforming how organizations process and act on data: the proliferation of edge computing, advancements in artificial intelligence (AI), and the integration of open source platforms.
Edge devices—including internet of things (IoT) sensors, industrial controllers, and retail automation systems—are generating more data than ever.1 This data explosion makes analyzing massive amounts of information increasingly complex. Organizations must therefore employ advanced analytical tools and AI models that can identify meaningful patterns and insights in diverse, messy, and distributed datasets.
Three key trends are transforming how organizations process and act on data: the proliferation of edge computing, advancements in artificial intelligence (AI), and the integration of open source platforms.
Edge devices—including internet of things (IoT) sensors, industrial controllers, and retail automation systems—are generating more data than ever.1 This data explosion makes analyzing massive amounts of information increasingly complex. Organizations must therefore employ advanced analytical tools and AI models that can identify meaningful patterns and insights in diverse, messy, and distributed datasets.
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