Imagine with this AmalGAN AI to create art

In the world of today, anything could be possible in the world of technological era. An art is a creative stuff illustrated by artists to perform drawings and paintings to cover audience. It is not like logical ability to solve tasks but rather it needs far more creative interest to sculpture it. We could see no. of great artists even making up wonderful art these days. Now a machine generated imagery with the aide of human collaboration  these tasks are now becoming so easier for artists. 

Interestingly, we could see ai is currently performing so many actions like writing horror stories , SKETCHAR : AI  that helps the non artists to draw from the direction through AI and NN. Now another AI has taken a foot further that creates an art with the pure imaginative perspective from Rebben. His latest work AmalGAN that actually derived from Google's Big GAN ( Generative Adverserial Networks ) efforts to generate high fidelity images diversification extracted from data. This training involves Generator and Discriminator networks where its sole purpose is to map random noise to samples and discriminate real and generated samples.

Google's Big GAN is actually a wonderful , complex and rather dynamic sample training that actually backed by Google's extra ordinary computing ability and uses its magnificent credit ability to create reality type images. This is actually a web based type where Big GAN engine is used to separate images into various mashups. It also could generate and combine into various images on how they are getting close to the abstractism of various interfaces.

Combining images to an art like stuff could be done with the supporting software GANbreeder application . With the help of that application , the process could be automated like humanly created art stuff which is totally complies with the certain attributions that combines different words together and also produces variants of the images with the other images and child images. Another AI will then show up the several images as child images measuring brain waves and body signals to select which image like the best..

Those steps are again repeated until the AI finds out and determines the optimal image and increases the resolution of the image by filling in the blanks by telling there what should exists there. The result is then painted in the canvas by anonymous painters in a Chinese painting village . The final AI checks and comes out with the title by figuring it out.

As you can imagine the first two steps are handled by GANbreeder app and that will increase or decrease the color and brightness of the images of two models. As soon it finalizes the model then it analyzes and increases the hueness and image recognition and AI is excellently trained to determine the strength through deep learning system on the body sensors through wearing it.. This has been tested by Reben himself.

Reben uses the data to train simple art method and neuron network technique by linking to the autonomous system through visual tracking like eye ball movement . The neuron network is trained in very higher degree through brain signals via. EEG , heart rate and GSR. It might add facial emotion recognition through webcam is truly excellent

Art created by AmalGAN AI from the pictures

From the digitized image of Microsoft Caption Bot AI to make sure the title is been created for the images generated from the AI . Even Reben is so excited about the process rendering and image generation technique through NN and AI also interpreted this. AI visualizes , scans and proliferates the image and then captions the title of the image generated through human help.

As Google Big GAN is under research and it is not been used in many applications yet. It is still under progressive state which needs lots of improvements to fix the present test results. However, these newly developed conceptual stuff is still a promising work for developers to do more research works with the continual problem. There are several implications and trainer models are adapted to the canonical search to make it more alliteratively intuitive.

Not only the developers but also the artists could able to train and develop the system to perform more characteristic level approach with the help of algorithm trained in more advanced process with the less problems. Reben says artists can develop and train this tool to generate own images not just the google stock set alone. He also adds that this is just a progressive state with wonderful idea that helps the artists to come with the imaginative ideas through AI and NN concept.