Every month, we decipher three research papers from the fields of machine learning, deep learning and artificial intelligence, which left an impact on us in the previous month. Apart from that, at the end of the article, we add links to other papers that we have found interesting but were not in our focus that month. So, you can check those as well. Here are the links from the previous months:

• January
• February
• March
• April
• May

In general, we try to present papers that are going to leave a big **impact **on the future of machine learning and deep learning. We believe that these proposals are going to change the way we do our jobs and push the whole field forward. Have fun!

Not so long ago, Andrej Karpathy famously tweeted: “Gradient descent can write code better than you. I’m sorry.” What he was trying to say is that neural networks, which use Gradient descent optimization technique, will soon be able not just to write code, but to write code better than us – software developers. Stay relevant in the rising AI industry an learn all you need to know about deep learning here!

Unsupervised Translation of Programming Languages

If you worked in the software development industry, sooner or later you will face projects where you need to transfer part of functionality from one programming language to another. Sometimes the whole projects are translated from one programming language to another. These are expensiveendeavors. There is a famous example of how Bank of Australia spent around $750 million and 5 years of work to convert its platform from COBOL to Java. Basically, translating functionality from one language to another is not easy. For big projects, you need to be experienced in both languages. Of course, there are a number of tools that can help you with this, in fact, some of these tools are integrated as a part of some programming languages.

For example, Typescript uses such a tool to convert its code into JavaScript. This way you can use an object-oriented approach and type checking, and still use built software in the majority of browsers. These tools are called transcompiler, transpiler, or source-to-source compiler. Their purpose is to convert code from one programming language to another, given that languages work on the same level of abstraction. Authors of this paper use unsupervised learning to do so. Note that they focused on use cases of translation an existing codebase written in an obsolete or deprecated language to a newer one.

#ai #artificaial inteligance #artificial intelligence #artificial neural networks #data science