GAN-generated faces produced by popular tools such as thispersondoesnotexist.com and generated.photos have the property that the major facial features (particularly the eyes) are in the same location on every image. This becomes obvious when the images are blended together.
In addition to the facial feature positioning, there are several additional indicators that these faces are artificially generated, such as the mismatched lenses on @SamHoffhoff's glasses, @MarkPerlman14's mismatched ears, and @Noah__Abrams's surreal background.
Two of these accounts have alleged work history in their profiles: @MarkPerlman14 claims to be an ex-@CNN journalist, and @SamHoffhoff claims to be a former @UCBerkeley professor with poor spelling skills. Unsurprisingly, search results don't back up their assertions.
Each of these four accounts follows or is followed by at least two of the other three. Speaking of who these accounts follow and are followed by, there's one more interesting detail...
All four of these newly-created GAN-faced accounts both follow and are followed by @TheActivistsClb, a "Media & News Company" Twitter account created in January 2023 - in fact, @Noah__Abrams is @TheActivistsClb's very first follower.
The four GAN-faced accounts amplify @TheActivistsClb via retweets, replies, and quote tweets. Although the GAN accounts occasionally interact with other accounts as well (mostly big liberal accounts), promoting @TheActivistsClb appears to be their primary mission.
Permanent IDs of the four accounts in the network:
Update: two of these accounts have replied to this thread.
A couple more responses from these GAN-tastic fake accounts...
Hilariously, the operator of the @AbbyFeldman19 account has now threatened to sue me for "using (their) photo without (their) consent". Since the image is an artificially generated face rather than an actual photo, this notion is ridiculous. #LOLsuit
Just for fun, I decided to search Amazon for books about cryptocurrency a couple days ago. The first result that popped up was a sponsored listing for a book series by an "author" with a GAN-generated face, "Scott Jenkins".
cc: @ZellaQuixote
Alleged author "Scott Jenkins" is allegedly published by publishing company Tigress Publishing, which also publishes two other authors with GAN-generated faces, "Morgan Reid" and "Susan Jeffries". (A fourth author uses a photo of unknown origin.)
As is the case with all unmodified StyleGAN-generated faces, the facial feature positioning is extremely consistent between the three alleged author images. This becomes obvious when the images are blended together.
The people in these Facebook posts have been carving intricate wooden sculptures and baking massive loaves of bread shaped like bunnies, but nobody appreciates their work. That's not surprising, since both the "people" and their "work" are AI-generated images.
cc: @ZellaQuixote
In the last several days, Facebook's algorithm has served me posts of this sort from 18 different accounts that recycle many of the same AI-generated images. Six of these accounts have been renamed at least once.
The AI-generated images posted by these accounts include the aforementioned sculptures, sad birthdays, soldiers holding up cardboard signs with spelling errors, and farm scenes.
The common element: some sort of emotional appeal to real humans viewing the content.
As Bluesky approaches 30 million users, people who run spam-for-hire operations are taking note. Here's a look at a network of fake Bluesky accounts associated with a spam operation that provides fake followers for multiple platforms.
cc: @ZellaQuixote
This fake follower network consists of 8070 Bluesky accounts created between Nov 30 and Dec 30, 2024. None has posted, although some have reposted here and there. Almost all of their biographies are in Portuguese, with the exception of a few whose biographies only contain emoji.
The accounts in this fake follower network use a variety of repeated or otherwise formulaic biographies, some of which are repeated dozens or hundred of times. Some of the biographies begin with unnecessary leading commas, and a few consist entirely of punctuation.
It's presently unclear why, but over the past year someone has created a network of fake Facebook accounts pretending to be employees of the Los Angeles Dodgers. Many of the accounts in this network have GAN-generated faces.
cc: @ZellaQuixote
This network consists of (at least) 80 Facebook accounts, 48 of which use StyleGAN-generated faces as profile images. The remaining 32 all use the same image, a real photograph of a random person sitting in an office.
As is the case with all unmodified StyleGAN-generated faces, the main facial features (especially the eyes) are in the same position on all 48 AI-generated faces used by the network. This anomaly becomes obvious when the faces are blended together.
None of these chefs exist, as they're all AI-generated images. This hasn't stopped them from racking up lots of engagement on Facebook by posting AI-generated images of food (and occasional thoughts and prayers), however.
cc: @ZellaQuixote
These "chefs" are part of a network of 18 Facebook pages with names like "Cook Fastly" and "Emily Recipes" that continually post AI-generated images of food. While many of these pages claim to be US-based, they are have admins in Morocco per Facebook's Page Transparency feature.
Between them, these 18 Facebook "chef" pages have posted AI-generated images of food at least 36,000 times in the last five months. Not all of the images are unique; many have been posted repeatedly, sometimes by more than one of the alleged chefs.
Can simple text generation bots keep sophisticated LLM chatbots like ChatGPT engaged indefinitely? The answer is yes, which has some potentially interesting implications for distinguishing between conversational chatbots and humans.
For this experiment, four simple chatbots were created:
• a bot that asks the same question over and over
• a bot that replies with random fragments of a work of fiction
• a bot that asks randomly generated questions
• a bot that repeatedly asks "what do you mean by <X>?"
The output of these chatbots was used as input to an LLM chatbot based on the 8B version of the Llama 3.1 model. Three of the four bots were successful at engaging the LLM chatbot in a 1000-message exchange; the only one that failed was the repetitive question bot.