I think the rapid rate of change in modern software libraries has left me underwhelmed with ChatGPT when it comes to new libraries, C++, or niche APIs (financial, etc).
If you're writing react/python/angular or something popular it seems to do amazing things and spit out entire websites (per demos).
Unfortunately, when I try to put together C++, Rust, or even C# using recent libraries like Blazor it chokes up. I fully understand at least one reason why (libraries and language features not being in the training data from 2021) but that makes me feel that perhaps software engineering at the cutting edge or niche is safe and still requires human reasoning. Not to mention things like properly understanding when and why to use certain data structures, real-world impact of coding choices, pricing, esoteric speed/efficiency improvements, etc.
I think there's still a broad general area where good, great, and amazing+ developers can operate without much threat and in fact using their knowledge and experience to leverage GPT-4 (or others) as a force multiplier.
Your tool just needs examples of the more recent library calls.
With 32k tokens coming that's like 90kb total chars which 80kb could library or API docs.
Also it can easily be connected to things like pip or GitHub or Google to check documentation. And many tools are coming over the next few months that will put it in a debugging loop.
So maybe it's "safe" in the very near term but that issue of out of date training in no way prevents it from taking software engineering jobs.
I am working hard to build an AI system that can replace me before someone else does.
But with the plugins they announced yesterday this should no longer be an issue. You'll be able to easily connect other APIs or data sources to OpenAI so that your model will write the code exactly the way you want.
Are niche libs safe or software platform will concentrate on the most popular with the most examples and better LLM completion/generation leading to ossification ?
If you're writing react/python/angular or something popular it seems to do amazing things and spit out entire websites (per demos).
Unfortunately, when I try to put together C++, Rust, or even C# using recent libraries like Blazor it chokes up. I fully understand at least one reason why (libraries and language features not being in the training data from 2021) but that makes me feel that perhaps software engineering at the cutting edge or niche is safe and still requires human reasoning. Not to mention things like properly understanding when and why to use certain data structures, real-world impact of coding choices, pricing, esoteric speed/efficiency improvements, etc.
I think there's still a broad general area where good, great, and amazing+ developers can operate without much threat and in fact using their knowledge and experience to leverage GPT-4 (or others) as a force multiplier.