Confluent Cloud has launched new features like Flink Native Inference and Flink search, targeting challenges that developers face in real-time AI application development. Adi Polak outlines how these tools address fragmented workflows, which often lead to inefficiencies and increased costs. By allowing open-source AI models to run within Confluent Cloud, developers can benefit from greater data security and lower latency. Flink Native Inference keeps data private and eliminates the need for external model endpoints, while Flink search and built-in ML functions facilitate data enrichment and make advanced analytics more accessible to developers.
Flink Native Inference streamlines real-time AI development by integrating AI models directly into Confluent Cloud, enhancing operational efficiency and security through reduced network hops.
Developers often struggle with fragmented workflows in AI applications; these new features aim to unify the process, minimizing overhead and maximizing productivity.
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