From datapro.news titled "How Large Behaviour Models Are Rewriting Data Engineering Pipelines," explores the transformative impact of Large Behaviour Models (LBMs) on data engineering practices. It highlights a significant shift from language-based AI to embodied, action-oriented intelligence, where machines learn from real-world behaviour and physical interactions. The article explains how traditional batch-oriented data pipelines are becoming obsolete, replaced by real-time, continuous data streams originating from various sensors and human teleoperation. This necessitates new engineering workflows focused on low-latency ingestion, complex temporal and spatial data transformation, and advanced behavioural data curation. Finally, it addresses the critical ethical and technical risks associated with LBMs, such as bias-induced physical harm, bodily privacy concerns, and economic concentration, offering strategic recommendations for data engineers to adapt and lead in this evolving field. Join the Data Innovators Exchange for free at https://www.skool.com/data-management-innovators-4116/about Sign up for the free Data Pro Newsletter at https://www.datapro.news/subscribe

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