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<!--HTML-->Machine learning is used at all stages of the LHCb experiment. It is routinely used: in the process of deciding which data to record and which to reject forever, as part of the reconstruction algorithms (feature engineering), and in the extraction of physics results from our data. This talk will highlight current use cases, as well as ideas for ambitious future applications, and how we can collaborate on them.