o_nate

So many great lines, as usual:

- "Breakage" is a social construct

- Everyone can change everything -- of course! -- but not if tests break -- also of course!

- You basically repeat yourself another time, saying, like, I really meant it the first time, don't just rip it to shreds, please.

We also read these kinds of rebuttals almost every day. The original article made a number of substantive critiques about where AI falls short in the actual requirements for building maintainable, reliable, business-critical software. So its not enough just to point to newer models without explaining how the newer models solve these problems. Can the new models take full end-to-end ownership of a system? If not, how do they solve the problem of humans taking ownership of AI generated code?

I think its easy for us to think we can understand what a program is going to do when we're dealing with high level abstractions. I think if we really came to grips with everything the program is doing all the way down to the hardware level, we might have less confidence that we can predict what its going to do with 100% accuracy every time, even in the case of supposedly simple programs.

I think there are two ways to interpret this question, not sure which one you meant.

Question one: if you don't remember being conscious, were you actually conscious?

Seems the answer should be yes. Just because you don't remember something doesn't mean it didn't happen.

Question two: can you be conscious without something like memory?

This one I think may depend on future understanding of what consciousness is. It seems like consciousness without any memory would be consciousness without anything like perception.

There's a lot of wisdom in this. In addition to reserving some capacity for when true high-value work comes along, I think software engineering is not the type of job that you can do well if you're constantly busy. Trying to write some code as quickly as possible seldom yields the best design. This article doesn't get into another important aspect of this, which is how to get away with working at 80% capacity without getting in trouble with your manager. This takes a bit of care around communication and estimation of work. One of the first good pieces of advice that I got from older seasoned developers when I started my first real programming job has stayed with me to this day: take your estimate of how long it will take to do something and double it before communicating to your manager/users. As you get more experienced that ratio can come down to maybe 1.5x instead of 2x, but the principle still applies.

If students are allowed to use AI to accomplish their goals, then I think the real question is why should they go to an expensive university for four years to learn how to ask AI to do something?

The title may be needlessly aggressive. I think Rovelli could have framed this better by acknowledging there is a hard problem and then arguing that we have a better chance of resolving that problem by seeking a better understanding of conciousness as a physical process before drawing metaphysical lines in the sand. Or as Rovelli memorably puts it: "How can we know now what we would understand if we were to understand something we do not currently understand?" His point is that science is inextricable from subjective experience and subjective experience is inextricable from the physical world - a point made over 100 years ago by William James.

I'm currently reading (and enjoying) "How Life Works: A User's Guide to the New Biology" by Philip Ball. It proceeds from the bottom up: the first half is all about cells and smaller structures. Pretty readable but doesn't gloss over complexity.

Yeah, I guess what goes around comes around. Bad if true though.

I don't think the author is missing this distinction. It seems that you agree with him in his main point which is that companies bragging about LOCs generated by AI should be ignored by right-thinking people. It's just you buried that substantive agreement at the end of your "rebuttal".