Teratosis

from Xenarch by Purulence

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TERATOSIS
Hypothesis: convolutional neural networks can be used to generate real-world
cancers which can then be used by nanosurgery bots, which themselves will
use convolutional neural networks. Results: categorical cross-entropy has unusual behaviour. Even with massive amounts GPU power, no stable set of hyperparameters has been found. One interesting area for further research are the larger teratomas generated, some of which have fully-formed eyes and scattered teeth. Some of the artificial
cancers have exhibited rapid-eye movement (R.E.M), while others display a
“chewing” motion, should a set of teeth be reasonably humanoid. Update: due to irreconcilable error rates in the first CNN out of the two, making a viable product for government and private practices should be handled carefully. It will require a human touch to select appropriate training tumours. The rejects will not be sold, and instead suspended in extracellular fluid for further study. Reminder to self: patent these models

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from Xenarch, released October 29, 2021

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