alt Hacker NewsI feel like AGI's definition got watered down, and these tests do not cover the original definition, what is your definition and thoughts on aligning with what all of us understood from the original claim?
I feel like this test is just helping someone like Sam Altman pretend like he implemented AGI as originally pitched for an IPO when in fact, he has not. Shameful.
> AGI is essentially the equivalent of a median human that could be hired as a remote co-worker... capable of performing any task that one would be satisfied with a remote colleague doing via a computer.
- Sam Altman on AGI
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Here's another definition of AGI from Sam Altman:
https://www.nytimes.com/2023/11/20/podcasts/hard-fork-sam-al...
Sam Altman: Let’s say we make an A.I. that is really good, but it can’t go discover novel physics. Would you call that AGI?
Kevin Roose (New York Times): I probably would, yeah. Would you?
Sam Altman: Well, again, I don’t like the term, but I wouldn’t call that done with the mission.
If it makes you feel any better the curmudgeon who drives the ARC-AGI tests feels the same way, that's why we're on 3 and I'm sure we'll see 4. Also, we can all avoid calling it "moving the goalposts" so no one feels talked down to.
> I feel like AGI's definition got watered down
Typical result of venture capital and too many bag holders unfortunately.
People need to stop redefining and trying to capture the term AGI. None of this is AGI. Not even close. Can it do things an AGI could do? Yeah some of it, but the difference really matters. These things still regularly fail, and gaslight about answers to questions like "how many r's in strawberry" or "s's in espresso".
An AGI wouldn't struggle with that.
I wonder if Altman's definition also includes taking on the same liability as a coworker would.
Probably not.
ARC-AGI was never "if this benchmark is saturated, we're at AGI". It was always about crafting adversarial tests that humans are good at, but current AIs are bad at. Point out the gap, get AI teams to attack them.
In practical terms? They usually get solved with a bigger badder LLM. "New ideas are needed?" Nah - ten times the params, ten times the test time compute.
ARC-AGI-3 was more of a failure in that regard than -1 or -2, because even on day 0, an off the shelf LLM with a harness could get 50%+. And messing with evals by forbidding "LLM with a harness" from scoring? Yeah no, that was just bad.
I can call a coworker right now and have a real time conversation with them without feeling like I’m talking to a frustrating machine. Most of them, anyway. But I guess that’s “moving the goalposts”.