The purpose of this talk is to debunk a number of streaming analytics myths, Ha-Joon Chang style.

We discuss 7 “thing”s which address common misconceptions ranging from marketing ploys (*ahem*), such as how we are all empowering our video analytics pipelines with AI, to legitimate confusions, such as what makes an appropriate QoE representation for a given stakeholder and/or use case. Thing 1: Streaming analytics is not only for debugging errors. Thing 2: The video community is not actually using AI for streaming analytics. Thing 3: What we talk about when we talk about QoE might be wildly different. Thing 4: We do not have enough standards for streaming analytics. Thing 5: Energy consumption should be a bigger concern for streaming analytics. Thing 6: Open source software and open datasets can also benefit commercial streaming analytics products. Thing 7: Streaming analytics is not ready for the metaverse. We provide use cases, examples and lessons learned from both research and industry. Bite-sized takeaways guaranteed. This talk was presented at Demuxed ’22, a conference for video nerds in San Francisco featuring amazing talks like this one. Demuxed ’22 was made possible by sponsors like our Platinum sponsor Daily (https://daily.co) and organized by people from Mux (https://mux.com). For more information about the conference and community, see https://2022.demuxed.com.