Recently I came across this interesting paper In-Domain GAN Inversion for Real Image Editing (a.k.a IDInvert), and I was amazed by the potential of this technique and the large number of potential applications of it. Below is a list of applications this paper has envisioned.

List of applications by In-Domain GAN Inversion For Real Image Editing (IDInvert)

To me, the applications should not stop at “Real Image Editing”, and should be extended to the art creation world. Just imagine that, after an artist has drawn his character, he can edit the character’s pose and expression without redrawing it. He can even pick a certain feature from another character, and blend into his…


https://blog.applovin.com/ai-in-video-games-mobile-development/

Artificial Intelligence (AI) has progressed with supersonic speed in recent years.

Big game companies like EA and Ubisoft are actively integrating these machine-learning and deep-learning techs into their development pipeline. DeepMind and OpenAI have used reinforcement learning to train AI agents play Starcraft and Dota 2, and beat top-notch human players. Nvidia uses deep-learning to achieve real-time ray-tracing, and further improve the performance through DLSS. There is a consensus that AI will revolutionize the game industry.

It may feel that those sexy AI tools are only relevant to the big companies and not very accessible to us common folks. …


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In 2017, the paper “Attention is all you need” shocked the land of NLP (Natural Language Processing). It was shocking not only because it has a good paper title, but also because it introduced to the world a new model architecture called “Transformer”, which proved to perform much better than the traditional RNN type of networks and paved its way to the state of the art NLP model “BERT”.

This stone cast in the pond of NLP has created ripples in the pond of GANs (Generative Adversarial Networks). Many have been inspired by this and attempt to garner the magic…


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Style2Paints is an all-star project, it has over 10k stars on Github, and according to this post, it has been ranked the 4th among the most popular machine learning projects on Github. The picture above is one example shown in the repository. Just with a few color hints, the AI model can convert the line sketch on the left to this fabulous color image on the right. I can’t help but think that I can be an artist too.


Since we were very young, we dreamed of using our hands to remotely control things around us. Certainly, we can touch things, move things, roll things around, throw things away, but none of these are cool. We can only become a Wizard or a Jedi Master when we can control something without being in contact with it.


Prerequisites for this post: basic knowledge of Python and Jupyter Notebook; basic understanding of machine learning.

In this post, I will introduce how to build fanciful and interactive data visualization like this.

But before we jump into that, let’s start by understanding why we need to visualize data.

Why We Need Data Visualization?

Data visualization is a group of techniques which can convert giant data with hundreds or thousands of dimension into a 2D/3D representation so that we tiny human beings can have a good understanding.

There are usually two reasons for using it:

  1. Visualize raw data, once the data is represented in 2D/3D space…

Jiasheng Tang

AI practitioner | Game developer | Yoozoo.{AI}

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