Artificial intelligence (AI), the development of computer systems to simulate human intelligence, has permeated our everyday activities, from conducting an internet search to driving a car. Within medicine, AI has facilitated maintaining and mining of electronic medical records. In medical imaging, it has been applied to static images such as chest computed tomography; the large amount of information within scans has been evaluated more quickly by AI than by human experts.1 AI has also been applied to echocardiographic images, to identify views, measure ejection fraction and strain, and detect disease.2 However, echocardiography poses particular challenges for AI: spatial and temporal information in image video clips varies considerably among patients, is affected by ultrasound systems and settings, and is highly influenced by sonographer skill.