S02E04: Game of Streams (The new wave of television)


  • Machine learning / AI: Machine learning is advancing within video production, both in the “early phases” with for example metadata enhancement and automation and in the “late phases” where machine learning is used to extract clips and highlights. Machine learning could also be used during encoding to find the best profiles and settings for the codec of choice.
  • Personalization: The technology used for online streaming is very well suited for personalization. In most cases, you could add personalization without extra cost for production and distribution. One example is personal linear channels that we at Eyevinn have been experimenting with. This concept was seen from a couple of vendors at the show.
  • More efficient use of the H.264 codec: Most encoder and transcoder vendor present more efficient use of H.264. Call it content aware encoding, quality-based encoding, per title encoding or per scene encoding, the concept is the same. You use some kind of pre-processing to determine the best possible encoder settings for the specific content. The trick moving forward would be to make this pre-processing step as slim as possible, and also encoder agnostic.
  • Cloud is no longer a selling point, it’s commodity and taken for a fact. At the last few shows (NAB or IBC), cloud has been a feature that was marketed by the vendors. This year cloud was replaced by software-based, agnostic to cloud or own datacenter. Personally, I believe that on-premise will still be around, and the most suitable deployment option for the specific usage will be chosen.
  • VR is more or less gone from the show when it comes to video. I believe that VR will be big in gaming and other areas, but for video, it seems to have left the building.

To watch out for the coming months…



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Eyevinn Technology

Eyevinn Technology

We are consultants sharing the passion for the technology for a media consumer of the future.