“Specifically, Musk used « an Internet application called the ‘Botometer’—which applies different standards than Twitter does and which earlier this year designated Musk himself as highly likely to be a bot, » Twitter said.The Botometer website is a project of the Observatory on Social Media and the Network Science Institute at Indiana University. Citing a May 2022 Protocol article, Twitter’s court filing said that « the Botometer indicated that Elon Musk’s own Twitter account was likely a bot, scoring it 4/5. »”
Source : Twitter says Musk’s spam analysis used tool that called his own account a bot | Ars Technica
“At first glance, Ramsey’s profile looks like many others on LinkedIn: the bland headshot with a slightly stiff smile; a boilerplate description of RingCentral, the software company where she says she works; and a brief job history. She claims to have an undergraduate business degree from New York University and gives a generic list of interests: CNN, Unilever, Amazon, philanthropist Melinda French Gates. But there were oddities in the photo: the single earring and strange hair, the placement of her eyes, the blurry background. Alone, any of these clues might be explained away, but together, they aroused DiResta’s suspicions […].
That chance message launched DiResta and her colleague Josh Goldstein at the Stanford Internet Observatory on an investigation that uncovered more than 1,000 LinkedIn profiles using what appear to be faces created by artificial intelligence.”
Source : The latest marketing tactic on LinkedIn: AI-generated faces : NPR
“Our automated defenses blocked 97.1% of all fake accounts we stopped during the January – June 2021 period. We continue our investment in manual and automated defenses to prevent or remove malicious accounts from LinkedIn.”
Source : Community Report
“Which Face Is Real has been developed by Jevin West and Carl Bergstrom at the University of Washington as part of the Calling Bullshit project. All images are either computer-generated from thispersondoesnotexist.com using the StyleGAN software, or real photographs from the FFHQ dataset of Creative Commons and public domain images. License rights notwithstanding, we will gladly respect any requests to remove specific images; please send the URL of the results pages showing the image in question.”
Source : Which Face Is Real?
“Using the neural-net tool Artbreeder, Photoshop and historical references, I have created photoreal portraits of Roman Emperors. For this project, I have transformed, or restored (cracks, noses, ears etc.) 800 images of busts to make the 54 emperors of The Principate (27 BC to 285 AD).”
Source : Photoreal Roman Emperor Project – Daniel Voshart – Medium
“We are building the next generation of media through the power of AI. Copyrights, distribution rights, and infringement claims will soon be things of the past. To give you a glimpse of what we have been working on we created a free resource of 100k high-quality faces. Every image was generated by our internal AI systems as it continually improves. Use them in your presentations, projects, mockups or wherever — all for just a link back to us!”
Source : 100,000 AI-Generated Faces – Free to Download!
“Reste à savoir où YouTube placera le curseur entre ce qui relèverait de l’authenticité et ce qui serait une théorie complotiste trop néfaste. Le dirigeant de YouTube UK explique ainsi que s’il tolère des vidéos de désinformation sur le 11 septembre, il a un avis tout autre à propos d’un autre attentat plus récent, celui de l’école primaire de Sandy Hook commis en 2012. Des conspirationnistes disent qu’il aurait été monté de toutes pièces, ce qui dépasse selon lui la limite acceptable. Elles sont « douloureuses et offensantes pour certaines familles impliquées », a-t-il précisé. Est-ce que parce que l’on touche à des enfants, ou parce que l’événement tragique est plus récent ? La plateforme garde pour l’instant ses critères d’appréciation pour elle.”
Source : Pourquoi YouTube tolère les vidéos conspirationnistes sur le 11 septembre – Société – Numerama
“We present a method for detecting one very popular Photoshop manipulation — image warping applied to human faces — using a model trained entirely using fake images that were automatically generated by scripting Photoshop itself. We show that our model outperforms humans at the task of recognizing manipulated images, can predict the specific location of edits, and in some cases can be used to « undo » a manipulation to reconstruct the original, unedited image.”
Source : Detecting Photoshopped Faces by Scripting Photoshop
“We’ve trained a large-scale unsupervised language model which generates coherent paragraphs of text, achieves state-of-the-art performance on many language modeling benchmarks, and performs rudimentary reading comprehension, machine translation, question answering, and summarization — all without task-specific training.”
Source : Better Language Models and Their Implications