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64 points m-hodges | 2 comments | | HN request time: 0s | source
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prisenco ◴[] No.45078963[source]
For junior devs wondering if they picked the right path, remember that the world still needs software, ai still breaks down at even a small bit of complexity, and the first ones to abandon this career will be those who only did it for money anyways and they’ll do the same once the trades have a rough year (as they always do).

In the meantime keep learning and practicing cs fundamentals, ignore hype and build something interesting.

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tombert ◴[] No.45079019[source]
I think the concern isn't so much about the current state of AI replacing software engineers, but more "what if it keeps getting better at this same rate?"

I don't really agree with the reasoning [1], and I don't think we can expect this same rate of progress indefinitely, but I do understand the concern.

[1] https://en.wikipedia.org/wiki/Jevons_paradox

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echelon ◴[] No.45079046[source]
If software developers wind up replaced by AI, I think it's safe to say every industry's labor will be replaced. Trade jobs won't be far behind, because robotics will be nipping at their heels.

If software falls, everything falls.

But as we've seen, these models can't do the job themselves. They're best thought of as an exoskeleton that requires a pilot. They make mistakes, and those mistakes multiply into a mess if a human isn't around. They don't get the big picture, and it's not clear they ever will with the current models and techniques.

The only field that has truly been disrupted is graphics design and art. The image and video models are sublime and truly deliver 10,000x speed, cost, and talent reductions.

This is probably for three reasons:

1. There's so much straightforward training data

2. The laws of optics and structure seem correspondingly easier than the rules governing intelligence. Simple animals evolved vision hundreds of millions of years ago, and we have all the math and algorithmic implementations already. Not so, for intelligence.

3. Mistakes don't multiply. You can brush up the canvas easily and deliver the job as a smaller work than, say, a 100k LOC program with failure modes.

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bc569a80a344f9c ◴[] No.45079103[source]
> If software developers wind up replaced by AI, I think it's safe to say every industry's labor will be replaced. Trade jobs won't be far behind, because robotics will be nipping at their heels. If software falls, everything falls.

I don’t think that follows at all. Robotics is notably much, much, much harder than AI/ML. You can replace programmers without robotics. You can’t replace trades without them.

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echelon ◴[] No.45079125[source]
> Robotics is notably much, much, much harder than AI/ML.

Are you so sure?

Almost every animal has solved locomotion, some even with incredibly primitive brains. Evolution knocked this out of the park hundreds of millions of years ago.

Drosophila can do it, and we've mapped their brains.

Only a few animals have solved reasoning.

I'm sure the robotics videos I've seen lately have been cherry picked, but the results are nothing short of astounding. And there are now hundreds of billions of dollars being poured into solving it.

I'd wager humans stumble across something evolution had a cake walk with before they stumble across the thing that's only happened once in the known universe.

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1. bc569a80a344f9c ◴[] No.45079171[source]
Yes, robotics is harder. Here’s some links. Wiki as an intro, and a reasonably entertaining write up that explains the concept in some depth, specifically comparing the issue to LLM progress as of 2024

https://en.m.wikipedia.org/wiki/Moravec%27s_paradox

https://harimus.github.io/2024/05/31/motortask.html

Edit: just to specifically address your argument, doing something evolution has optimized for hundreds of millions of years is much harder than something evolution “came up with” very recently (abstract thought).

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2. echelon ◴[] No.45079367[source]
> Edit: just to specifically address your argument, doing something evolution has optimized for hundreds of millions of years is much harder than something evolution “came up with” very recently (abstract thought).

You've got this backwards.

If evolution stumbled upon locomotion early -- and several times independently through convergent evolution --, that means it's an easy problem, relatively speaking.

We've come up with math and heuristics for robotics (just like vision and optics). We're turning up completely empty for intelligence.