In reply to a developer on one of the Linux kernel mailing lists, Linux creator Linus Torvalds firmly put a foot down to push back against anti-AI comments.
I personally think both pro LLM and anti LLM are wrong. One group think they are gods. The other think they are demons. LLMs can be useful for programming to some extent. But they will create a disaster if you don’t know what are you doing. I have recently published a post about the matter on me blog. I think the best part is:
I strongly believe that LLMs are useful for programming to some extent. Imagine you have a shop and you get a robot to do the moves for you. So you instead focus on the main business concerns.
So if you want to make some changes to the code which don’t require intelligence, that is they are just mechanical tasks, LLMs are good. If you want the LLMs to understand semantics of your code, you have chosen the wrong tool. Maybe in future we’ll have new AI software and tools which also understand semantics to some extent. But I highly doubt a transformer will be able to do it. They just predict the next likely token.
There is something I haven’t yet added to the post. So I am writing it here. Our computers are Universal Turing Machines. There are some fundamental limits to what a turing machine can’t do. Those are called undecidable problems. For instance a turing machine can never check if two pieces of code are semantically equivalent[1]. But that’s what human programmers can do. That’s why I emphasize on tasks which require no intelligence.
[1] That’s about the general case. Sure there are exceptions. But as we say “exception is not the rule”.
I personally think both pro LLM and anti LLM are wrong. One group think they are gods. The other think they are demons. LLMs can be useful for programming to some extent. But they will create a disaster if you don’t know what are you doing. I have recently published a post about the matter on me blog. I think the best part is:
So if you want to make some changes to the code which don’t require intelligence, that is they are just mechanical tasks, LLMs are good. If you want the LLMs to understand semantics of your code, you have chosen the wrong tool. Maybe in future we’ll have new AI software and tools which also understand semantics to some extent. But I highly doubt a transformer will be able to do it. They just predict the next likely token.
There is something I haven’t yet added to the post. So I am writing it here. Our computers are Universal Turing Machines. There are some fundamental limits to what a turing machine can’t do. Those are called undecidable problems. For instance a turing machine can never check if two pieces of code are semantically equivalent[1]. But that’s what human programmers can do. That’s why I emphasize on tasks which require no intelligence.
[1] That’s about the general case. Sure there are exceptions. But as we say “exception is not the rule”.