[5th May 2024] Interesting Things I Learnt This Week

Nerves 

1. Nerves Project: The Nerves Project is a toolkit for building software for small devices (embedded systems) like routers or sensors. It combines Elixir, a powerful programming language, with a reliable runtime environment to make development easier. Imagine building with Legos instead of tinkering with wires. Nerves takes care of complex tasks like networking and device control, so you can focus on the unique features of your project.

My Take: This is a very interesting project. Someone like Sun(now Oracle) tried doing something like this for Java and were not very successful IIUC. Would love these folks to succeed. Maybe this will be the turning point where Elixir finds its perfect use and widespread adoption.


2. Bank scam with genuine notifications: A scammer used a badly implemented bank notification to trick users into authenticating and drained user of USD 18,000. Details in the blog post and on reddit.

My Take: I had talked about Monzo implementing a very nice mechanism which tells users when the bank is calling and to verify that in a previous post. But seems like Chase implemented a horrible version of it which the link above has very well pointed out. All security changes need to be thought through and blindly implementing stuff like this just leads to bigger disasters. 

 

3. Perplexia: Its is an open-source AI-powered searching tool or an AI-powered search engine that goes deep into the internet to find answers. Inspired by Perplexity AI, it's an open-source option that not just searches the web but understands your questions. It uses advanced machine learning algorithms like similarity searching and embeddings to refine results and provides clear answers with sources cited.

My Take: New open source implementations like Perplexity are popping up all the time. They seem to run smoothly on powerful modern computers. With better hardware and software in the future, even basic computers might handle them well. This could be a real threat to Google. Their dominance in search might be weakening with these new developments. The next generation of researchers and students would not be using Google but solutions like these.


4. Full line code completion in Jetbrain IDE: JetBrain IDEs now offer Full Line Code Completion, a machine-learning powered feature that suggests entire lines of code as you type. This translates to faster development by reducing repetitive typing and improving accuracy with context-aware suggestions. In the 2024.1 version of JetBrains IDEs,  uses a language model that has 100 million parameters, with a maximum context size of 1,536 tokens, which is roughly 170 lines of code.

My Take: The future looks bright for language models! There will soon be more options available, even in different languages, and many will be open source. While I haven't used them myself yet, I'm a bit cautious. My past experiences with LLMs for similar tasks haven't been great. Honestly, I'd rather code it myself than rely on copied code from these AI tools. Instead, I'd prefer to find help with APIs and learn how to do it myself, kind of like searching for solutions on Google or Stack Overflow. The key is to understand the code, not just copy it blindly. I've seen too many people fall into that trap!

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