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System Environment Setup

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According to the record last week, I'tried to finish the tasks below by order. Since I havent used python before, those works were more difficult than they seem to be. 1. Package climi and GPy installation for python environment  https://github.com/SheffieldML/GPy/issues/649 (resolution for Gpy ) ???? (climin) 2. https://blender.stackexchange.com/a/51800 (link the anaconda environment to Blender) 3. Issues may happen  Error when importing numpy, see here: https://stackoverflow.com/a/56009839 Error when importing keras/GPy, see here: https://stackoverflow.com/a/19105436 • Climin installation This package cannot be found in anaconda package manager, it is currently only available via git from github. I took the research on like ' how to install packages on python', ' how to download packages from github'. All those operations are based on some very simple codes, it still took me a while though. The right approach is:  (1) install gitbash and set it...
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Reference-GAN (updated on 2/28/2020)

https://pathmind.com/wiki/generative-adversarial-network-gan Notes: Discriminative models learn the boundary between classes Generative models model the distribution of individual classes i.e. the discriminator decides whether each instance of data that it reviews belongs to the actual training dataset or not. Here are the steps a GAN takes: The generator takes in random numbers and returns an image. This generated image is fed into the discriminator alongside a stream of images taken from the actual, ground-truth dataset. The discriminator takes in both real and fake images and returns probabilities, a number between 0 and 1, with 1 representing a prediction of authenticity and 0 representing fake. https://ai.googleblog.com/2017/12/introducing-new-foveation-pipeline-for.html Notes: However, current VR/MR technologies present a fundamental challenge: to present images at the extremely high resolution required for immer...
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Reference-DLSS from NVIDA

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As I thought, there's not many examples for AI working with graphics technologies. But there's a big name, NVIDA. NVIDA published 20 series graphics card. One of their new technologies is DLSS, deep learning super sampling. Basically, it is for correcting the missing frames from raytracing, because the AI system has been trained to fill up the missing part in the images from a pointed game. More presentation: https://www.youtube.com/watch?v=KJRZTkttgLw#action=share https://www.nvidia.cn/geforce/gaming-laptops/20-series/ I mean, I can't really know how they realize this with every line of codes, but it provides me with the basic logic of what AI can do with graphics. After another around of research, I have a chart. Like I planned in the last blog, for now, I will get into some simple AI system, try to find out its sampling process and learning target . Except the hardware, another example Prof Paul showed us in class is  https://www.nvidi...
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