Until a language model can develop a generalized solution to a real-world phenomena, it's not even close to AGI. The current iteration of ML algorithms are useful, yes, but not intelligent.
> Github Copilot solved my business problem by itself just as I would've done. Is that real-world enough and the solution generalized enough?
No, it isn't. Co-Pilot is unable to provide a rationalisation for the generated code and is incapable of assessing its security or performance properties.
It's a very advanced auto-complete that just happens to have been specialised on auto-completing code.
Actually, I just usually write a usage example, and Copilot does the code including "rationalization", because that's how my codebase looks - an example, then a description and then the implementation. It's using comments and written English language just like any other dev to explain what it does (again, it picked up that from my own code style).
> It's a very advanced auto-complete that just happens to have been specialised on auto-completing code.
It's not just an autocomplete. It's an intelligent autocomplete. As long as you need to generate text, it's practically generally intelligent.
I really wonder what will happen when somebody runs a text generator like Copilot in a loop with a simulated work-memory and longterm-memory and realtime I/O interface.
I mean... it can generate comment summaries explaining any block of code, or an entire class. It can generate comprehensive unit tests and usability tests. It can tell you the Big-O operational complexity of any code you (or it) writes, and it can put those all together. Is that not good enough for you..?
It can't do that. It can try to do that and it might work well in some cases. It is definitely incapable of doing that for any code you throw at it.
It also cannot generate comprehensive unit tests - it can can generate unit tests. The definition of "comprehensive" is way too subjective.
> Is that not good enough for you..?
No, it indeed isn't, but maybe that's because I actually have at least some idea of what happens behind the scenes and how the system works. From the implementation details, I can tell you for a fact that none of what you described can be done by the system in the general case - and especially not correctly. It's hit and miss depending on the input and that's basically a design limitation.
Github Copilot solved my business problem by itself just as I would've done. Is that real-world enough and the solution generalized enough?