181–190 of 321 posts
Earlier quoted context omitted.
What language(s), out of interest?
I use node.js, but I think it will work for anything. I recommend trying small chunks first vs dumping your whole file.
Earlier quoted context omitted.
> Not to a competent programmer when reading well-written code. No, literally reading a one line about what the next 4 lines do is mechanically faster. It does not matter that you are good or bad, it is about simple reading speed. > This also means that you read what the code does, rather than what a comment says the code does. Otherwise you will be blind to bugs. Any experienced developer will tell you that code ver…
> For me, this type of thinking that comment are unnecessary, that competent ppl can just read the code, etc. is actually a sign of younger dev who never had to work on a long-lived codebase. It sounds like you're conflating "helpful comments that explain why" with "no comments are needed ever because read the code", and we're talking past each other.
Author of HumanifyJS here! I've created specifically a LLM based tool for this, which uses LLMs on AST level to guarantee that the code keeps working after the unminification step: https://github.com/jehna/humanify
Train on java compiled to class files. Then go from class back to java.
Or even:
Train java compiled to class files, and have separate models that train from Clojure to class and Scala to class files. Then see if you can find some crufty (but important) old java project and go: crufty java -> class -> Clojure (or Scala).
If you could do the same with source -> machine instructions, maybe COBAL to C++! or whatever.
This might be fun: Train on java compiled to class files. Then go from class back to java. Or even: Train java compiled to class files, and have separate models that train from Clojure to class and Scala to class files. Then see if you can find some crufty (but important) old java project and go: crufty java -> class -> Clojure (or Scala). If you could do the same with source -> machine instructions, maybe COBAL to C…
Earlier quoted context omitted.
GPT is not a brand. A court ruling turned down that notion. It's a technology.
That only means it’s not a legally recognised brand, but it is a brand nonetheless if people associate the two (and they do). A bit like the way people associate tissue paper with Kleenex, or photocopies with Xerox, or git with GitHub.
This might be fun: Train on java compiled to class files. Then go from class back to java. Or even: Train java compiled to class files, and have separate models that train from Clojure to class and Scala to class files. Then see if you can find some crufty (but important) old java project and go: crufty java -> class -> Clojure (or Scala). If you could do the same with source -> machine instructions, maybe COBAL to C…
AI cannot even lint properly right now and you want it to decompile? good luck, there's too much hype going on people really think this is possible this year?
In the end always remember it's just autocomplete, it's pretty terrible at translations that are not natural language to natural language. I worked on a natural language to SQL and it was impossible to make it consistently generate valid SQL for Postgres, and I'm talking about natural language to SQL not virtual machine instructions...
Earlier quoted context omitted.
Sure, but that claim wouldn't be true for humans, right? So it's a nonsequiteur. The relevant claim would be: all humans can do is move around in their environments, adapt the world around them through action, observe using adaptive sensory motor systems, grow and adapt their brains and bodies in response to novel and changing environments, abstract sensory motor techniques into symbolic concepts, vocalize this using…
> all they can do is, in fact, sample from a compression of historical texts To me, results like the Othello paper make any sort of "stochastic parrot" thinking completely untenable. https://thegradient.pub/othello/
It is good at unminifying and "minifying" as well. I have been doing the Leetcode thing recently, and even became a subscriber to Leetcode. What I have been doing is I go through the Grind 75 list (Blind 75 successor list), look for the best big O time and space editorial answer, which often has a Java example, and then go to ChatGPT (I subscribe) or Perplexity (don't subscribe to Pro - yet) and say "convert this to…
This does seem to be a smart use of the tools available to skip the grind and get to the point of the leetcode questions. However, I wonder about this: What will you do in a live interview situation? Will you pull up ChatGPT?
As a next step - even within these 75 questions, Grind 75's eighth answer and fourteenth answer are answered essentially the same way, as are other questions in there. So the next step would be to see these patterns (binary search, priority queues, sliding window, backtracking) and how to answer them, and then be able to solve them in slightly novel problems (in the more complex questions I understand one might run into more than one of these patterns).