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Another way to look at our threshold matrix is as a kind of probability matrix. Instead of offsetting the input pixel by the value given in the threshold matrix, we can instead use the value to sample from the cumulative probability of possible candidate colours, where each colour is assigned a probability or weight . Each colour’s weight represents it’s proportional contribution to the input colour. Colours with greater weight are then more likely to be picked for a given pixel and vice-versa, such that the local average for a given region should converge to that of the original input value. We can call this the N-candidate approach to palette dithering.

“I don’t see why “taste” and direction are uniquely human, like many people say. If an AI can train on it, it can learn it,” Schumer added in a later post on X.

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Historically, tactile sensing always seemed like a technology that was 10 years away, Lepora says. But he thinks the billions of dollars being invested in humanoid robots is making a difference.

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Prototype pollution defense: One test patches Object.prototype.then to intercept promise resolutions, then verifies that pipeTo() and tee() operations don't leak internal values through the prototype chain. This tests a security property that only exists because the spec's promise-heavy internals create an attack surface.

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