Hello Forum,
Is there any deep learning, neural network, or ML algorithm that includes a specific domain search for data, labeled (supervised) or non-labeled (unsupervised) data? As well do they can process or can engineer the data automatically and feed themselves? For example, Sophia uses SingurarityNET.io as well as probably the whole internet to get her data. Similarly, I think, if AI algorithms could find (from kaggle etc.) and use their data on their own and could fetch back the engineered data for others’ use in the future, hopefully, that would lessen the terse workload for data management. I dream that AI would be able to label the non-labeled data from their past experiences in handling labeled data or training data as well could automatically prepare the data by removing null values, outliers, etc. If there are such algorithms, please let me know.
Read through the post, I don’t know of any myself but is an interesting idea. Though the complexity of the such model pipeline would be high. I guess the tech giants are using such models for at least the benefit of the services they provide and those "they don’t officially provide 
" but they are privately owned for many reasons including cost to build.
Thanks for your reply but what I think, biggest tech giants are other than none but the open source community, no one could stand out against their collaborative strength. I will open a Github repo on this idea and I like to welcome OS Veterans and everybody of this forum to contribute. What is your opinion regarding this?
Definitey, you can try it
.