Due to this more measured approach, error-diffusion dithering is even better at preserving details and can produce a more organic looking final image. However, the algorithm itself is inherently serial and not easily parallelised. Additionally, the propagation of error can cause small discrepancies in one part of the image to cascade into other distant areas. This is very obvious during animation, where pixels will appear to jitter between frames. It also makes files harder to compress.
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"At a time when much of the industry is moving toward closed, AI-driven ecosystems, we’re taking a different path, one that puts people, not platforms, in charge," Varma said in an email statement. "We’ve heard clearly from our users: some who don’t want AI, while others want the ability to decide exactly how and when it shows up in their browser. AI controls are how we deliver on that commitment."