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.
The Problem With Doing This The Obvious Way
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But you could also read those quotes as the latest example of a hot startup’s ethics becoming grayer as its valuation rises. (Remember Google’s old “Don’t be evil” mantra that it later removed from its code of conduct?) The latest versions of Claude have drawn widespread praise, especially in coding. In February, Anthropic raised $30 billion in new investments. It now has a valuation of $380 billion. (Speaking of the competition Kaplan referred to, rival OpenAI is currently valued at over $850 billion.)
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