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Equation 4 · Part 9 · How AI for Science and Medicine Actually Works

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xt=αˉt x0+1−αˉt ϵ,x^0=fθ(xt,t),x_t = \sqrt{\bar{\alpha}_t}\, x_0 + \sqrt{1-\bar{\alpha}_t}\, \epsilon, \qquad \hat{x}_0 = f_\theta(x_t, t),
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The passage around this formula

The larger change is in how coordinates are produced. Rather than a Structure Module built on rotations and translations, AlphaFold3 uses a diffusion module that operates directly on raw atom coordinates and a coarse token representation, without rotational frames at all. Diffusion models are trained on a simple, general task: take a true data point, corrupt it with noise at a known level, and train a network to recover the original from the corrupted version. For coordinates x0x_0 noised to xtx_t at noise level t , xt=αˉt x0+1−αˉt ϵ,x^0=fθ(xt,t)x_t = \sqrt{\bar{\alpha}_t}\, x_0 + \sqrt{1-\bar{\alpha}_t}\, \epsilon, \qquad \hat{x}_0 = f_\theta(x_t, t). with ϵ\epsilon drawn from a standard normal distribution and fθf_\theta the trained network. Generating a structure then means starting from coordinates that are…

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A variable is a named place for a value. Its letter is a local label: x can mean position in one formula and a data point in another.

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