PIXELS_TRUENAS_PORT
Author(s): Junwei Che, Xuezhi Wang
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The government reportedly agreed to those terms, according to the New York Times, but the contract's legal language provided too much wiggle room for Anthropic’s comfort. Anthropic is known for taking a more cautious approach to AI development, and its founders famously left OpenAI over AI safety concerns.
Another way to approach dithering is to analyse the input image in order to make informed decisions about how best to perturb pixel values prior to quantisation. Error-diffusion dithering does this by sequentially taking the quantisation error for the current pixel (the difference between the input value and the quantised value) and distributing it to surrounding pixels in variable proportions according to a diffusion kernel . The result is that input pixel values are perturbed just enough to compensate for the error introduced by previous pixels.
However, due to modern LLM postraining paradigms, it’s entirely possible that newer LLMs are specifically RLHF-trained to write better code in Rust despite its relative scarcity. I ran more experiments with Opus 4.5 and using LLMs in Rust on some fun pet projects, and my results were far better than I expected. Here are four such projects: