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YerevaNN is a promising scientific foundation with very specific, actual and really interesting objectives. AI (Artificial Intelligence) research is among the especially noteworthy ones. They’ve just recently launched A Guide to Deep Learning, which is a relatively new branch of machine learning. The ultimate goal of this field is “to teach computers to perform various tasks based on the given data”.
We’ve talked to YerevaNN director Hrant Khachatrian and tried to find out more about their upcoming projects and the current state of the existing ones.
Briefly about YerevaNN
“YerevaNN is a research lab that aims to create a good atmosphere for students and researchers interested in machine learning and AI. Unfortunately, state funding of science is inadequate in Armenia, and the difference between salaries for a computer science researcher in academia and industry is extremely high. Most students who want to become scientists leave the country or are forced to go to industry,” said Hrant, further adding, “YerevaNN is an attempt to provide an alternative opportunity for them. We are a non-profit foundation funded by private donations and research grants. We don't do any commercial projects and heavily focus on machine learning research. We hope that YerevaNN will become a hub for machine learning community in Armenia and will accelerate the growth of talent in this sphere”.
Plans for the future
The integration into the global machine learning research community is one of their plans. Particularly, as Hrant noted, “The short-term plan is to publish some high quality research. Our team is very young and we do not yet have solid scientific record. The first step would be to become a part of machine learning research community. We just started to collaborate with University of Southern California with the help of Professor Aram Galstyan. In the longer term, we'll try to grow the team, enhance international collaboration and develop high quality educational materials for Armenian universities.”
The Deep Learning Guide
As for the newly published Deep Learning Guide, Hrant mentioned that “The guide includes links to many high quality resources for studying deep learning. They range from easy-to-read blogposts to math-heavy video courses and books. Those who can read/watch and understand half of the material will be able to easily get involved in our lab. All the content included in the guide is freely accessible.” In addition, it’s going to be updated whenever better educational resources are available.
The global feedback
Global sources like Reddit and Hacker News have already noticed the Deep Learning Guide by YerevaNN. “To our surprise, the guide received a lot of attention around the world. It was trending on Reddit's r/MachineLearning and on Hacker News”, Hrant notes. “There were some negative responses, like "why do we need yet another guide", but most responses were very positive. Some explicitly praised the organization of resources by topics and difficulty. We registered 30K visits in just three days and still have few hundreds daily users, half of which are returning. Visits from Armenia are just 3% of those”, said Hrant.
Thus we can see that the guide is already receiving global recognition and appears to be useful for quite many followers. We don’t doubt that this guide and YerevaNN foundation in general will soon have their valuable contribution in the global machine learning sphere.
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