Recently, several users on social media platform X have claimed to earn 'thousands of dollars' by posting fake information related to the US elections, AI-generated images, and various unfounded conspiracy theories. These users often share each other's content online, retweeting multiple times a day to increase their exposure and revenue. A BBC investigation found that these users have formed networks consisting of dozens of accounts that interact with each other, sharing a mix of true and false information with the aim of boosting their presence on the platform.

A recent study proposed a new method that leverages human attention to enhance the quality of AI-generated images. This method uses a saliency detector to identify the most important areas in the image and prioritizes the generation of these areas. Traditional image generation methods optimize the entire image uniformly, whereas the new method identifies and prioritizes more 'important' regions, similar to human attention. This approach can improve image quality and fidelity to textual prompts. Researchers utilized stable diffusion models and saliency detectors to generate images, and

With the continuous advancement of artificial intelligence technology, the difficulty of forging images and videos has decreased significantly, making the deepfake phenomenon increasingly severe. Identifying these false contents has become an urgent issue to address. Recently, a research team from Binghamton University conducted an in-depth discussion on this topic, using frequency domain analysis techniques to reveal the characteristics of AI-generated images, thus helping people identify false information. Image source note: The image is AI-generated, with permission from image licensing provider Midjourney. This research was conducted by the Department of Electrical and Computer Engineering.

Apple's upcoming iOS 18 features various AI functionalities, including SMS rewriting, email summarization, and object recognition in photos. Notably, the 'Image Playground' creates cartoon-style illustrations from text prompts, with Bailey, the dog of Apple SVP Craig Federighi, as the first AI-generated image subject. Other practical AI tools are also included, but they are currently limited to the beta version.....

As the realism of AI-generated images increases, people begin to question the authenticity of videos. A video released by 'Quantum Bit' on Bilibili discusses how to identify AI-produced videos, triggering widespread interest. The video introduces some intuitive recognition methods, such as observing whether characters' movements and expressions are natural, as well as the coordination of voice, mouth shapes, and emotions. In the face of a vast number of videos, AI recognition technology becomes crucial. The traces left by AI face swapping technology during the splicing process serve as important clues for AI recognition. The research team developed classifiers from dimensions such as models, motion, and geometry.

A research team from Fudan University has developed the 'Concept Erasure Technique' (RECE), which can efficiently and accurately modify inappropriate ideas in AI models, significantly reducing the likelihood of generating inappropriate images while maintaining the AI's other creative capabilities. This technology uses a 'closed solution' to locate and modify specific parts, ensuring the AI behaves more appropriately during creation and stays on track. Experiments show that the RECE technology can effectively enhance the morality and quality of AI creations, providing new directions for the future development of AI, making future AI assistants smarter and more perceptive.

Former President Trump shared an AI-generated image of Taylor Swift supporting him on the social media platform Truth Social, claiming he was not involved in its creation. One image depicted Taylor Swift as 'Uncle Sam,' accompanied by a slogan supporting Trump. Trump stated he was unaware of these images and that they were generated by others. He further indicated that AI technology could pose dangers and seemed confused about the origins and content of these images. This action came after he previously accused Vice President Kamala Harris of using AI to create fake images.

Zomato, a major food delivery platform in India, announced a ban on the use of AI-generated food images on restaurant menus to safeguard customer trust and reduce complaints, refunds, and declines in ratings. CEO Deepinder Goyal emphasized that starting this month, the platform will remove AI-generated images and encourage restaurants to use professional photography services with cost price support. Zomato plans to utilize automation technology to detect and reject the upload of AI images. At the same time, the marketing team has also prohibited the use of such images in promotional materials. Despite taking a strong stance,

Artificial Intelligence (AI) generated images have triggered a revolutionary change in the field of architectural design, providing architects with the flexibility to produce highly complex and imaginative designs. However, in areas involving culture, sensitivity, and religion, such as Islamic architecture, AI-generated depictions often fail to accurately present historical Islamic elements and their interpretations, according to a study published in the journal 'Buildings'.

Midjourney founder David Holz emphasizes that AI is not meant to replace artists but to expand human imagination. The platform helps users quickly generate ideas and provides concept design support for professional users. The development of AI technology will drive the market towards higher quality, creativity, and diverse content. The future impact on artists remains to be seen, but respecting copyright laws is crucial. AI technology, as a supportive tool, can enhance creative efficiency but cannot replace the unique creative abilities of artists.

Meta has announced that it will label AI-generated images on Facebook and Instagram to help users distinguish between real and false information. The company is collaborating with the industry to establish technical standards, expanding the initiative to videos and audio in response to the issue of false content. This initiative has garnered attention, and the labels will be gradually rolled out, covering major global elections, with an effort to identify false content. Technology industry partners are working together to create authenticity standards for content and promote the implementation of digital watermarking.

Coca-Cola's sports drink brand BodyArmor features AI-generated images in its Super Bowl advertisement titled 'Field of Fake', emphasizing the product's lack of additives through cultural commentary comparing real footage with AI-generated content. The ad will air in 20 U.S. markets and Canada.

Camera manufacturers are responding to the rise of AI-generated images by embedding digital signatures to verify real photos. Nikon plans to offer a mirrorless camera with certification technology and a Verify web tool to check the authenticity of images, seeking methods to identify AI-generated content.

The Beijing Internet Court has reached a first-instance judgment on the AI-generated image copyright infringement case, stating that AI-generated images possess originality and are protected by copyright law. When generating images, the intellectual contribution comes from humans rather than the model. As long as the human intellectual input reflects originality, it should be entitled to copyright. This ruling holds significant implications for copyright protection in the field of AI-generated images.

Google search results have shown that a photo of Israeli singer Kamakawiwo'ole is actually AI-generated, replacing a real photo. Google states that it is working on improving the reliability and representativeness of Knowledge Panels, but the issue remains unresolved. The article calls for Google to better address the misinformation generated by AI, stating that its responses have been insufficient. Although Google has taken steps to enhance the credibility of image search results, the issue still persists, raising concerns about the accuracy and reliability of AI in search engines.

Researchers from MIT and Google have collaborated to develop StableRep technology, which trains detailed and efficient AI image models using AI-generated images. StableRep employs multi-positive contrastive learning methods and trains on millions of labeled synthetic images, achieving significant results in ImageNet classification. Despite its success, StableRep's image generation is relatively slow, suffers from semantic mismatch issues, and requires the underlying model to be initially trained on real data. The technology has been open-sourced on GitHub.

Researchers have found that all current watermarking techniques for AI-generated images can be easily bypassed. Digital watermarks can be removed or added to real images, resulting in false positives. Watermarking technology currently cannot reliably identify AI-generated images. Malicious actors can easily circumvent or manipulate the watermarks. Artists' works may be incorrectly labeled as AI-generated due to watermarking technology.