If someone showed you such a path, would you consider changing your mind? You're always going to be able to find a reason that such an explanation doesn't count if you're dedicated to looking for one.
Yes, actually I would. There's a long list of people in my career path who bet on me sticking to my guns against compelling evidence to the contrary. But I know, I know, that's impossible! Anyway, after they figured out I would change my mind, then they described me as lacking conviction because you can't win, but I digress.
But upfront, it's a detailed path with specific breakthroughs and a concrete plan to achieve or it's just more fanfic from doomer fanbois. Gary Marcus wrote a fantastic critique of AI 2027. Start there.
I've read Gary Marcus's critique of AI 2027. How do you grapple with the fact that superhuman coding arrived on schedule, despite his skepticism that it would? Doesn't that mean that the other predictions are also more plausible than we may think?
I work with Codex and Claude daily. They're fantastic for script coding, config issues, and simple projects. They lose the plot on bigger things to this day. Just last night, Astra decided to cheat to present the illusion of progress until I called its BS. And I was so looking forward to finally working with the AGI. Humans remain the muse, the common sense, and the manager of making these things productive. And as much as I agree with Carmack's suggestion to not become the out of touch Kung Fu Master:
We understand "superhuman coding" to mean very different things, and I think it's a me problem that I can't figure out where you're coming from, because it doesn't sound like our practical experience differs. I'm going to have to think on this.
Define it. I haven't seen anything yet from a coding agent I couldn't write myself and usually write better. But I don't have to gold plate every line of code, just the 5% or so that eats 90+% of the cycles. And this is where the agents are weakest. This does get to one of the reasons I don't believe AI cures death or builds von Neumann replicators any time soon because that requires out of sample breakthroughs. And that's not their strong point.
Just like AlphaFold 2 genuinely increased the weak sequence but strong structural homology detection of proteins, but it did far less for out of sample domains and it provides no intel into the kinetics of folding. Details matter. And nobody likes to hear about them.
Is there a retrospective on AlphaFold you’d recommend? Maybe that’s the insight I’m missing, I didn’t realize it had broad identifiable gaps like that.
I see similar conceptual gaps in coding agents when I work with them, even Astra and Fable, so maybe this a is decent proxy to describe the gap between hype and reality.
