This topic contains 5 replies, has 1 voice, and was last updated by 
josh November 22, 2020 at 7:54 am.
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joshWe can imagine a set of computational approximation techniques that form a lattice of paths to fast. Eventually, ML may be able to train on accumulated pixel differences of each path & other features to help predict which path is Goldilocks in a given situation. That can be built into the development, with a mix of compile time & run time contributions.
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joshI’m not familiar with all the details in this example of expensive rendering but I gather that a program was used to stochastically generate snow ice & then render it with ambient illumination. So the illumination for this type of example could be compared with other techniques for both realism & speed.
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joshprior to 2020
https://www.linkedin.com/in/urban-bradesko-ab159064/ -
joshprior to 2019
https://www.linkedin.com/in/bryonyworth/ -
joshprior to 2018 – E,F,I key claims a rape/dying victim was found in the past
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