Auke discusses the challenges of end-to-end neural codecs, highlighting their computational demands compared to traditional methods. He emphasizes the importance of balancing performance with efficiency, as recent advancements focus on developing practical codecs that maintain good rate distortion performance while being less resource-intensive. The call for innovation in this area is echoed by David, who advocates for models that optimize both computational cost and effectiveness.
