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I used GPT-3 yesterday for the first time myself - I wanted some code to list the DynamoDB tables available to me (I had to run it from an EC2 instance and I wa

I used GPT-3 yesterday for the first time myself - I wanted some code to list the DynamoDB tables available to me (I had to run it from an EC2 instance and I wanted to see what that particular EC2 instance could see). I was pretty impressed - it put the code together so I asked it for a POM and it put that together. The POM failed with an error because it was trying to load from Maven central using HTTP, so I asked ChatGPT how to fix that error and it told me how to update my settings.xml file (it did make a mistake, but it was an easy one to fix). Like - I knew how to do all of that, but it probably would have taken a half hour vs about 5 minutes with ChatGPT.

RugnirViking 4y ago
exactly. It makes mistakes, but so do I. It makes mistakes far faster however, because it takes about 5 seconds to finish each attempt, so they seem far more prevalent. However, I can fix it's mistakes almost as fast as I can fix my own, so this speeds up iteration nicely. It's not a "perfect tool", but nothing is
elboru 4y ago
ChatGPT is great with well known tools and libraries. I’ve been able to build HTML/JS apps in minutes. Then I tried building a MAUI app, it started pretty good, but then when I tried to add charts it failed (it’s important to mention this was my first MAUI app), I tried different approaches, in the end I went back to HTML/JS. That led me to a realization, this could mean that people will likely discard less known libraries or technologies more easily than before. Popular technologies will become even more popular since we’ll be 10x more productive with them compared to less known ones since we won’t have LLMs super powers for those.
- burlesona 4y ago
  I agree and have had the same thought. This is gas on the fire to winner-take-all dynamics. It’s already hard for new languages and systems to catch up fast enough to technically weaker existing options bc they have mature tooling. But when the robot is fluent in Java and can’t understand $newlang it’s going to be even harder.
  - akiselev 4y ago
    It's way too early to tell. I'm betting that projects will be able to fine tune LLMs against their code bases and documentation, making it easier to adopt new open source projects because mini-GPTs will help new users get set up with their exact use case instead of having them dig through a bunch of semi-irrelevant examples.
- sharkjacobs 4y ago
  When I ask it about Swift, I'm often surprised by how good it is. When I ask it about Objective-C it bullshits and fabricates APIs. When I ask it about python or bash scripts it is astonishingly good
  - vkazanov 4y ago
    A couple of weeks ago I made an absurdly efficient arithmetic expression language compiler in python, complete with a RD/pratt parser, control flow graph IR , optimizer (dead code elimination, algebraic, etc) and a simple x86 codegen. Chatgpt wrote most of it. Then I asked chatgpt to port it piece by piece to C. Took a while to get a hang of gpt4's token length limitations, as well as fixes here and there... 1.5 hours. But damn... Most programmers are just not capable of doing this at all.

RugnirViking 4y ago

exactly. It makes mistakes, but so do I. It makes mistakes far faster however, because it takes about 5 seconds to finish each attempt, so they seem far more prevalent. However, I can fix it's mistakes almost as fast as I can fix my own, so this speeds up iteration nicely. It's not a "perfect tool", but nothing is

elboru 4y ago

ChatGPT is great with well known tools and libraries. I’ve been able to build HTML/JS apps in minutes. Then I tried building a MAUI app, it started pretty good, but then when I tried to add charts it failed (it’s important to mention this was my first MAUI app), I tried different approaches, in the end I went back to HTML/JS. That led me to a realization, this could mean that people will likely discard less known libraries or technologies more easily than before. Popular technologies will become even more popular since we’ll be 10x more productive with them compared to less known ones since we won’t have LLMs super powers for those.

burlesona 4y ago
I agree and have had the same thought. This is gas on the fire to winner-take-all dynamics. It’s already hard for new languages and systems to catch up fast enough to technically weaker existing options bc they have mature tooling. But when the robot is fluent in Java and can’t understand $newlang it’s going to be even harder.
- akiselev 4y ago
  It's way too early to tell. I'm betting that projects will be able to fine tune LLMs against their code bases and documentation, making it easier to adopt new open source projects because mini-GPTs will help new users get set up with their exact use case instead of having them dig through a bunch of semi-irrelevant examples.
sharkjacobs 4y ago
When I ask it about Swift, I'm often surprised by how good it is. When I ask it about Objective-C it bullshits and fabricates APIs. When I ask it about python or bash scripts it is astonishingly good
- vkazanov 4y ago
  A couple of weeks ago I made an absurdly efficient arithmetic expression language compiler in python, complete with a RD/pratt parser, control flow graph IR , optimizer (dead code elimination, algebraic, etc) and a simple x86 codegen. Chatgpt wrote most of it. Then I asked chatgpt to port it piece by piece to C. Took a while to get a hang of gpt4's token length limitations, as well as fixes here and there... 1.5 hours. But damn... Most programmers are just not capable of doing this at all.