Last weeks CHI HCA meeting in San Francisco was interesting for a couple of reasons: 1) The emergence of small, personal HCA machines suitable for individual labs or rapid expansion of throughput in core facilities allowing HTS with HCA. 2) Expanded use of machine learning to detect complex features. This requires heavy-duty image analysis (clusters???) post image acquisition. Steve Altschuler’s lab always has a novel take on analyzing image data; look for “PhenoRipper” in the near future in an HCA lab near yours.