21–30 of 38 posts
They're called image macros, not memes.
One is a subset of the other. You could also call these ones "advice dog variants" or "unfunny reddit cancer".
This is a complete joke, right? What is better about those results than a simple "image + headline + random bottom line" algorithm?
Exactly. Memes are funny because they make meta references that are culturally relevant or simply attach absurd bottom lines. It's highly unlikely a deep neural network can model anything like that.
Reminds me a bit of https://www.reddit.com/r/SubredditSimulator/
Interestingly, this subreddit is generated by vanilla Markov chains: no neural networks.
It looks like a joke now but I'm fairly convinced that in the not too distant future the most influential social media accounts will be run by some kind of AI.
Who knows, maybe they already are? I mean I'm confident there's a ton of content farms out there already that just run a cronjob every couple minutes to pluck the top ten images off of a subreddit, checks if they've been published on their own channel yet and republishes them. If not, I'll brb, need to set up some websites / facebook accounts.
You could tell it was automated, because every once in a while, a very reddit specific meme would appear on the 9gag front page, with a bunch of confused comments from 9gag users who didn't understand it. Here's a writeup from a couple of years ago on it [1]
I don't doubt that other clickbait sites like BoredPanda do exactly the same thing.
[1] https://www.reddit.com/r/pcmasterrace/comments/3z2wvf/about_...
Very silly; best not to alert the media or we'll soon see "AI can now generate memes" clickbait. I thought it was funny though that Richard Socher, one of the authors of GLoVe and NLP researcher is pictured in the generated memes on p. 8. ("the face you make when")
This Artificial Intelligence Learned to Create Its Own Memes and the Results will Make you ROFL!!
How scientists trained an AI to create memes by looking at images
The end is near. The singluarity is here. Run for your lives!1!!
As someone who has spent a lot of time working with text-generating neural networks ( https://github.com/minimaxir/textgenrnn ), I have a few quick comments. 1) The input dataset from Memegenerator is a bit weird. More importantly, it does not distinctly identify top and bottom texts (some have a capital letter to signifify the start of the bottom text, which isn't always true). A good technique when encoding text fo…
If this was submitted we are certainly in the dankest timeline.
Full paper with some examples here: https://web.stanford.edu/class/cs224n/reports/6909159.pdf
Pretty unfunny results.
The other generated images are just dumb.
This is a complete joke, right? What is better about those results than a simple "image + headline + random bottom line" algorithm?
Exactly. Memes are funny because they make meta references that are culturally relevant or simply attach absurd bottom lines. It's highly unlikely a deep neural network can model anything like that.
Earlier quoted context omitted.
Exactly. Memes are funny because they make meta references that are culturally relevant or simply attach absurd bottom lines. It's highly unlikely a deep neural network can model anything like that.
Considering most deep learning results are interpreted as absurd/bizarre, I don't think the machine will have much difficulty intentionally or unintentionally emulating meme culture.