[spprashant]

Its in a weird space right now.

These models are actually extremely good but they are far from an intelligence unto themselves. Truth is if someone told you they could build these things 5 years ago, you d write them a check for a trillion dollars. Problem is once we got them, we realized they are not all that. Its like a mecha suit in a universe, where mecha suits are abundant and cheap. Someone has to climb into them everyday and put in the work for it to be effective.

So now the skeptics are saying this technology is overrated. And the optimists are accusing the skeptics of moving goal posts.

[4ffss]

I think we are learning in real-time what intelligence re. humans is as we go along.

Humans only what they know, until they acquire more information about what's possible.

The goal post narrative is stupid to begin with.

[batshit_beaver]

Humans have goal seeking behavior. LLMs don’t. You could maybe call the combination of LLMs and the RL-based harnesses somewhat “intelligent” in aggregate, but the problem is that it’s not “general” intelligence like these labs want to argue, since it’s by definition only good for the set of problems the RL part has been trained to solve, which is a subset of programming problems.

[cautiouscat]

> Problem is once we got them, we realized they are not all that.

Isn't this just the hype cycle? [1]

Fake edit: I know its not a perfect model.

1: https://www.gartner.com/en/research/methodologies/gartner-hy...

[asdfman123]

The problem is what they can do is rapidly expanding. Software development is becoming increasingly hands off.

If they get to the point where they're smart enough to make tasteful code decisions based on stakeholder input... we're cooked as a profession.

[human305893]

Most of the skeptics exist because of the grandiose claims made by the AI companies saying pure hype marketing bs. If this was just a tool, discussed at the scope of what the tools can actually produce and do, there would be sensible discourse about it.