Power10 retweet automation creator @JasonLSullivan_ has been excitedly promoting his new magainfo(dot)tv video site. This thread is not about that site, however. It is about another site with the same IP address: michaelsolisunus(dot)com.
(Previous thread on the now-defunct Power10 retweet automation software, as well as reporting from Business Insider on the topic) businessinsider.com/power10-activi…
At first glance, michaelsolisunus(dot)com looks like an empty website with placeholder "Home", "About Us", and "Contact Us" sections. What's up with that "Go to App" button in the corner?
The "Go to App" button leads to an authorization screen for a third-party Twitter app named "Michaelsolisunus" that requests a pretty comprehensive litany of permissions. We had @DrunkAlexJones give the mysterious app a whirl.
This is a good time to point out that one should exercise extreme caution when visiting dodgy websites or giving third-party apps permission to one's social media accounts, especially if one has no idea what the app in question does.
We (or rather @DrunkAlexJones) had to verify an email address in order to access all of the app's features. Interestingly, the confirmation email appears to be from Cyphoon, Power10 creator Sullivan's social media consulting company. reuters.com/article/us-usa…
Much like the old Power10 automation app (banned in September 2019), the Michaelsolisunus app offers automated retweets and automated follows. It also has some rudimentary analytics features, including the ability to track and log the retweeters of a set of tweets.
We poked through the app's Javascript code and found a constant indicating the maximum length of a tweet is 140 characters (Twitter bumped it to 280 in late 2018). In addition to being amusing, this is a possible indicator that the developer reused code from several years ago.
We had trouble getting some of the Michaelsolisunus app's features to work, and were also unable to find any content that had been retweeted with it. If either of these things change, this thread will be updated with additional analysis.
Update: both the Michaelsolisunus Twitter app and the @JasonLSullivan_ Twitter account are presently suspended.
• • •
Missing some Tweet in this thread? You can try to
force a refresh
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.