Recently, Meta began testing a new feature that will insert AI-generated content into Facebook and Instagram feeds based on users' interests and current trends. Meta states that these AI-generated images will be tailored to each user's preferences. Users can click on suggested prompts to guide the content in new directions. Interestingly, users can simply swipe the screen to have AI create more personalized content in real-time. As Meta pushes forward...

Meta has announced that it will continue with its plan to use millions of publicly available posts from UK Facebook and Instagram users to train its artificial intelligence technology. Although this practice is largely prohibited under EU privacy laws, Meta states that it has been in active communication with the UK Information Commissioner's Office (ICO), after previously pausing similar proposals in June. The pause was due to the ICO's warnings that tech companies must respect user privacy when developing generative AI.

Social media giant Meta is about to make significant adjustments to the way AI content is tagged on its platforms Instagram, Facebook, and Threads. Starting next week, the 'AI Information' label for content edited or modified by AI tools will be moved to the post menu and will no longer be displayed directly below the user's name. This change brings several key points: 1. Tagging Distinction: Content that is entirely generated by AI will still retain a prominent label, while labels for content that has been merely edited by AI will be hidden. 2. Sources of Transparency: Me

Recently, Meta announced that it will adjust the way it labels AI-edited content on Instagram, Facebook, and Threads. This change means that the 'AI Information' label indicating whether content has been edited by AI tools will be moved from below the username to the post menu. Previously, users could easily see this label below the username, but now they will need to click the menu to find it. However, Meta also stated that content generated entirely by AI will still be labeled.

Facebook acknowledged in an investigation that it is collecting publicly available data from all adult users in Australia. The company does not provide an opt-out option for Australians as it does for EU citizens, as privacy laws do not require it to do so.

Meta has recently tested a new AI comment summarization feature on Facebook, aiming to help users quickly grasp the overall sentiment of comments under posts. This feature aggregates user comments and displays a summary at the top of the comment section, providing an overview of the discussion.The introduction of this feature has garnered widespread attention, especially against the backdrop of social media platforms continuously seeking to enhance user experience. Meta hopes that this feature w

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.

The market valuation of the world's largest tech giants has now exceeded $1 trillion, partially due to investments and advancements in generative artificial intelligence, totaling over $10 trillion. Nvidia has surpassed Facebook as a newcomer, while Microsoft has overtaken Apple to lead. The total market value of global tech giants exceeds $1 trillion, with Nvidia emerging above Facebook and Microsoft taking the lead over Apple, including Microsoft, Apple, Google, and Amazon.

Facebook Research has developed the BrainMagick model that decodes matching speech content from brain activity recorded via EEG and MEG. The model achieves a Top-10 accuracy of 72.5% and a Top-1 accuracy of 41% for speech segments in MEG recordings, supporting the decoding of unseen words. It offers a non-invasive communication hope for aphasia patients with language dysfunction, eliminating the risks associated with brain surgery. The project is open-sourced on GitHub and can be executed using a GPU with 16GB of memory.