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I was using Meteor for my messenger project. I was so curious about the real time connection. I wanted to know how exactly this mechanism works. In this post, I will go through the DDP Specification, an overview of WebSocket, and a simple demo about how to subscribe a publication of Rocket.Chat (containing a DDP server) from an external webpage. At a glance, I knew that Meteor invented a protocol called DDP which uses for handling real time connection. So then, what is DDP? "DDP (Distributed Data Protocol) is the stateful WebSocket protocol that Meteor uses to communicate between the client and the server." [1] All right! Why does DDP matter? "DDP is a standard way to solve the biggest problem facing client-side JavaScript developers: querying a server-side database, sending the results down to the client, and then pushing changes to the client whenever anything changes in the database" . [2] In order to understand deeply the protocol, I decided

I enjoyed reading this post: https://words.steveklabnik.com/the-culture-war-at-the-heart-of-open-source Here is my highlight: If you ask a random developer what “open source” means to them, you won’t often hear “software that follows the Open Source Definition.” If you ask them “what’s the difference between free software and open source software,” you’ll often hear “aren’t those the same thing?” or “you can charge money for open source software, it’s not always free.” You may even hear “it’s on GitHub.” In brief, there was a man Richard Stallman (and his team) starting a project called "GNU Project" in 1983. This project was about to develop a free software system. The term "free" here meant "freedom", not only about the price. The Free Software Foundation appeared to support this project. But then, the term "free software" was so ambiguous. "In addition, the ambiguity of the term “free software” was seen as discouraging busine

You might have heard of a lot about AI, Machine learning, Data science, Deep learning, etc,... But, what exactly these terms mean and how is the connection between those. Here is my understanding: There are two ideas of AI: - ANI (Artificial Narrow Intelligence): E.g., smart speaker, self-driving car and web search. - AGN (Artificial General Intelligence): do anything a human can do. ANI is realistic and incredibly valuable. Though AGN is still too far away, and there is no need to unduly worry about it. When talking about data in term of AI that means talking about dataset . There are several methods to get a dataset: - Manual labeling - Observing user behaviors - Observing behaviors of other things such as machine - Downloading dataset from a website or acquiring it from a partner. Machine learning  (ML) is a tool in AI.  Supervised learning is a type of ML that learns A to B, or input to output mappings.  Deep learning/Neural networks is a type of sup