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phil917 | 1 year ago

Quote from the creators of the AGI-ARC benchmark: "Passing ARC-AGI does not equate achieving AGI, and, as a matter of fact, I don't think o3 is AGI yet. o3 still fails on some very easy tasks, indicating fundamental differences with human intelligence."

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qnleigh|1 year ago

I like the notion, implied in the article, that AGI won't be verified by any single benchmark, but by our collective inability to come up with benchmarks that defeat some eventual AI system. This matches the cat-and-mouse game we've been seeing for a while, where benchmarks have to constantly adapt to better models.

I guess you can say the same thing for the Turing Test. Simple chat bots beat it ages ago in specific settings, but the bar is much higher now that the average person is familiar with their limitations.

If/once we have an AGI, it will probably take weeks to months to really convince ourselves that it is one.

nopinsight|1 year ago

I'd need to see what kinds of easy tasks those are and would be happy to revise my hypothesis if that's warranted.

Also, it depends a great deal on what we define as AGI and whether they need to be a strict superset of typical human intelligence. o3's intelligence is probably superhuman in some aspects but inferior in others. We can find many humans who exhibit such tendencies as well. We'd probably say they think differently but would still call them generally intelligent.

CooCooCaCha|1 year ago

Yeah the real goalpost is reliable intelligence. A supposed phd level AI failing simple problems is a red flag that we’re still missing something.

gremlinsinc|1 year ago

You've never met a Doctor who couldn't figure out how to work their email? Or use street smarts? You can have a PHD but be unable to reliably handle soft skills, or any number of things you might 'expect' someone to be able to do.

Just playing devils' advocate or nitpicking the language a bit...

93po|1 year ago

they say it isn't AGI but i think the way o3 functions can be refined to AGI - it's learning to solve a new, novel problems. we just need to make it do that more consistently, which seems achievable