116
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
this post was submitted on 07 Oct 2024
116 points (100.0% liked)
Technology
37664 readers
449 users here now
A nice place to discuss rumors, happenings, innovations, and challenges in the technology sphere. We also welcome discussions on the intersections of technology and society. If it’s technological news or discussion of technology, it probably belongs here.
Remember the overriding ethos on Beehaw: Be(e) Nice. Each user you encounter here is a person, and should be treated with kindness (even if they’re wrong, or use a Linux distro you don’t like). Personal attacks will not be tolerated.
Subcommunities on Beehaw:
This community's icon was made by Aaron Schneider, under the CC-BY-NC-SA 4.0 license.
founded 2 years ago
MODERATORS
I was more hinting at that through conventional computational means we're just not getting there, and that some completely hypothetical breakthrough somewhere is required. QC is the best guess I have for where it might be but it's still far-fetched.
But yes, you're absolutely right that QC in general isn't a magic bullet here.
Yeah thought that might be the case! It's just a thing that a lot of people have misconceptions about so it's something that I have a bit of a knee jerk reaction to.
Haha it's good that you do though, because now there's a helpful comment providing more context :)
the limitation is specifically using the primary machine learning technique, same one all chatbots use at places claiming to pursue agi, which is statistical imitation, is np-hard.
Not just that, they've proven it's not possible using any tractable algorithm. If it were you'd run into a contradiction. Their example uses basically any machine learning algorithm we know, but the proof generalizes.
via statistical imitation. other methods, such as solving and implementing by first principles analytically, has not been shown to be np hard. the difference is important but the end result is still no agigpt in the foreseeable and unforeseeable future.