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At which point do we not need to understand what is in front of us? eg: The Code. I was using chatgpt, with a groovy project (havent used groovy in years), I

At which point do we not need to understand what is in front of us? eg: The Code. I was using chatgpt, with a groovy project (havent used groovy in years), I prompted chatgpt for an answer, and it gave me a solution. The solution (to me) was a bit obfuscated, but it worked. Since I'm only using groovy to figure out this one task, it would've been extremely easy for me to not check what the solution did, and just keep going with my day. Luckily, I'm curious and wanted to know how things worked. What if we increasingly stop to care, because of the confidence instilled by the media. "It can make errors" but also "This show SIGNIFICANT improvements over last generation (which tbh was pretty okay)" A lot of dis/misinformation. I like using copilot/chatgpt, but it's incredibly hard to believe that we wont just become 100% reliant on this tool, and coding will be something akin to assembly code to engineers.

jnovek 4y ago
One hypothesis I have is that the future of programming is natural language and the “compiler” is a LLM. This would be no different from the days when C took over for asm.
- NeuNeurosis 4y ago
  This was my take on the tech. Ultimately it will need to be prompted. Now the form that prompt takes is open to a bunch of speculation but even if it gets superhuman at producing code or any output it is directionless by itself, for now. We are what direct its ability, which I think is really cool. I think getting good at extracting exact outputs from the LLM will be the new engineer.
- layer8 4y ago
  The difference is that natural language doesn't have a well-defined semantics and is open to interpretation. Programming languages being compiled, on the other hand, have precise, well-defined semantics (excluding UB I guess) that you can formally reason about. Using an LLM for programming is not like compiling, it's like employing a developer you either have to trust how they may happen to interpret your instructions, or to manually double-check their work.
  - jnovek 4y ago
    I understand where you're coming from, but I didn't mean it quite that literally. More like, in the same way that compilers fundamentally changed how we program by adding a layer of (deterministic) abstraction, natural language assisted by AI could add a new (non-deterministic) layer of abstraction to programming.

jnovek 4y ago

One hypothesis I have is that the future of programming is natural language and the “compiler” is a LLM. This would be no different from the days when C took over for asm.

NeuNeurosis 4y ago
This was my take on the tech. Ultimately it will need to be prompted. Now the form that prompt takes is open to a bunch of speculation but even if it gets superhuman at producing code or any output it is directionless by itself, for now. We are what direct its ability, which I think is really cool. I think getting good at extracting exact outputs from the LLM will be the new engineer.
layer8 4y ago
The difference is that natural language doesn't have a well-defined semantics and is open to interpretation. Programming languages being compiled, on the other hand, have precise, well-defined semantics (excluding UB I guess) that you can formally reason about. Using an LLM for programming is not like compiling, it's like employing a developer you either have to trust how they may happen to interpret your instructions, or to manually double-check their work.
- jnovek 4y ago
  I understand where you're coming from, but I didn't mean it quite that literally. More like, in the same way that compilers fundamentally changed how we program by adding a layer of (deterministic) abstraction, natural language assisted by AI could add a new (non-deterministic) layer of abstraction to programming.