Real Time Communications Bits

With the latest improvements in ML technology, especially generative algorithms and large language models, more and more conferencing applications are adding these capabilities to their offerings. This ML technology can be applied to conferencing applications at two different levels: the infrastructure level with improvements in media handling and transmission, and the application level with new features or capabilities for the users. At the infrastructure level (codecs, noise suppression, etc.) most of the high-level ideas were covered in this other post . Some interesting recent advances are applying “ML codecs” for audio redundancy, and the next frontier is applying generative algorithms also to video, as well as general applications to photorealistic avatars. This post focuses on the second level (the application part) and how to implement typical features such as summarization, image generation, or moderation. The idea here is to present a reference architecture that can be used