this post was submitted on 16 Jul 2023
76 points (100.0% liked)
Technology
37717 readers
525 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
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
Humans (and animals) learn through a combination of their own experiences and observing the experiences of others. But this actually proves my point: if you feed an AI its own experiences (content it has created in response to prompts) and the experiences of other AIs (content they have produced in response to prompts), it cycles itself into oblivion. This is ultimately because it cannot create anything new.
This is why Model Autophagy Disease occurs, I think. Humans, when put in repetitive scenarios, will actively work to create new stimuli to respond to. This varies from livening up a boring day by doing something ridiculous, to hallucinating when kept in extreme sensory deprivation. The human mind's defence against repetitive stimuli is to literally create something new. But the AI's can't do that. They literally can't. They can't create anything that doesn't have a basis in their training data, and when exposed only to iterations of their own training data (which is ultimately what all AI-generated content is: iterations of the training data), there is no process that allows them to break out of that repetitive cycle. They end up just spiralling inwards.
From a certain perspective, AI's are therefore essentially parasites. They cannot progress without sucking in more human-generated content. They aren't self-sustaining on their own, because they literally cannot create the new ideas needed to prevent degradation of their own data sets.
From your other comments here, it seems like you're imagining a fully conscious mind sitting alone in a box, with nothing to react to. But that's not the case: AIs aren't sapient, going mad from a lack of stimulation. They are completely dormant until prompted to do something, and then they create an output that is statistically likely from the data set they've been trained on. If you add no new data, the AI doesn't change. It doesn't seek new stimuli. It doesn't create new ideas while waiting for someone to prompt it. The only way it can change and create anything new is if it's given more human-generated content to work with. If you give it content from other AI's, that alters the statistical probabilities behind its output. If the AIs were actually conscious minds sitting alone in boxes, then exposing them to content created by other AIs would, in fact, be new stimuli that could generate new ideas, in the same way that a lonely human meeting another lonely human would quickly strike up a conversation and get all kinds of ideas.
You're caught up in an idea that has been going around since long before any AI systems had been built
Humans rarely, if ever, produce something new. We stumble upon a concept or apply one idea to another thing
Neural networks are carefully distilled entropy. They have no subjective biases and no foundation - they're so good at being original that they default to things useless to humans.
I like to think of training like a mold, or a filter. You only want things in the right shape to come through - the more you train, the more everything coming through looks the same.