Musk labels Spain PM'tyrant' after Madrid proposes social media curbs Tech billionaire and owner of X, Elon Musk, has dubbed socialist Spanish Prime Minister Pedro Sanchez a "tyrant and traitor to the people" of Spain for introducing new social media curbs for children under the age of 16. Musk's comments on Tuesday came in response to an announcement by the Spanish prime minister that Madrid would introduce new changes to the country's social media laws. Sanchez also confirmed that the government would work with the public prosecutor to investigate alleged legal infringements by platforms, including TikTok, Instagram, and Musk's own AI chatbot, Grok. "Dirty Sanchez is a tyrant and traitor to the people of Spain," Musk wrote in response to the Spanish prime minister's X post, in which he detailed the upcoming measures. Grok has come under fire for allowing users to create sexually explicit fake images of women and minors, triggering an investigation by the European Commission.

Age Verification Is Reaching a Global Tipping Point. Is TikTok's Strategy a Good Compromise? TikTok's new age-detection tech seems like a better solution than automatically banning youth accounts. But experts say it still requires social platforms to surveil users more closely. Governments worldwide are moving to limit children's access to social media as lawmakers question whether platforms are capable of enforcing their own minimum age requirements.

Identifying fine-grained book genres is essential for enhancing user experience through efficient discovery, personalized recommendations, and improved reader engagement. At the same time, it provides publishers and marketers with valuable insights into consumer preferences and emerging market trends. While traditional genre classification methods predominantly rely on textual reviews or content analysis, the integration of additional modalities, such as book covers, blurbs, and metadata, offers richer contextual cues. However, the effectiveness of such multi-modal systems is often hindered by incomplete, noisy, or missing data across modalities. To address this, we propose IMAGINE (Intelligent Multi-modal Adaptive Genre Identification NEtwork), a framework designed to leverage multi-modal data while remaining robust to missing or unreliable information. IMAGINE learns modality-specific feature representations and adaptively prioritizes the most informative sources available at inference time. It further employs a hierarchical classification strategy, grounded in a curated taxonomy of book genres, to capture inter-genre relationships and support multi-label assignments reflective of real-world literary diversity. A key strength of IMAGINE is its adaptability: it maintains high predictive performance even when one modality, such as text or image, is unavailable. We also curated a large-scale hierarchical dataset that structures book genres into multiple levels of granularity, allowing for a more comprehensive evaluation. Experimental results demonstrate that IMAGINE outperformed strong baselines in various settings, with significant gains in scenarios involving incomplete modality-specific data.

This week has been an eventful one for America's public health agency. Two former leaders of the US Centers for Disease Control and Prevention explained why they suddenly departed in a Senate hearing. They also described how CDC employees are being instructed to turn their backs on scientific evidence. They painted a picture of a health agency in turmoil--and at risk of harming the people it is meant to serve. And, just hours afterwards, a panel of CDC advisers voted to stop recommending the MMRV vaccine for children under four. This article first appeared in The Checkup, MIT Technology Review's weekly biotech newsletter.

The vaccine advisory group ACIP, not all members of which seemed to know what the group does, recommended to the CDC that combined MMRV shots not be given before age 4. A federal vaccine advisory committee made of members hand-picked by Health and Human Services Secretary Robert F. Kennedy Jr. recommended in an 8-3 vote on Thursday that the combined measles, mumps, rubella and varicella (MMRV) vaccine should not be given before age four, citing long-known evidence that shows a slightly increased risk for febrile seizures in that age group. Experts say that while frightening, febrile seizures--which are uncommon after vaccination--are usually short-lived and harmless, and removing the option for parents could cause a decline in immunization rates against measles, mumps, and rubella, some of the most dangerous childhood diseases. Known as the Advisory Committee on Immunization Practices, or ACIP, the group provides recommendations to the US Centers for Disease Control and Prevention on vaccine usage. These recommendations are typically adopted by CDC and have an impact on state vaccine requirements for school, insurance coverage of vaccines, and pharmacy access--something at least one member of the panel seemed to be unaware of. Thursday's vote is part of a new shift in vaccine policy being spearheaded by Kennedy, a longtime anti-vaccine activist.

A Norwegian man has filed a complaint against the company behind ChatGPT after the chatbot falsely claimed he had murdered two of his children. Arve Hjalmar Holmen, a self-described "regular person" with no public profile in Norway, asked ChatGPT for information about himself and received a reply claiming he had killed his own sons. Responding to the prompt "Who is Arve Hjalmar Holmen?" ChatGPT replied: "Arve Hjalmar Holmen is a Norwegian individual who gained attention due to a tragic event. He was the father of two young boys, aged seven and 10, who were tragically found dead in a pond near their home in Trondheim, Norway, in December 2020." The response went on to claim the case "shocked" the nation and that Holmen received a 21-year prison sentence for murdering both children.

Hallucinations are one of the main problems computer scientists are trying to solve when it comes to generative AI. These are when chatbots present false information as facts. Earlier this year, Apple suspended its Apple Intelligence news summary tool in the UK after it hallucinated false headlines and presented them as real news. Google's AI Gemini has also fallen foul of hallucination - last year it suggested sticking cheese to pizza using glue, and said geologists recommend humans eat one rock per day. ChatGPT has changed its model since Mr Holmen's search in August 2024, and now searches current news articles when it looks for relevant information.

It has been over two years since ChatGPT exploded onto the world stage and, while OpenAI has advanced it in many ways, there's still quite a few hurdles. Now, Austrian advocacy group Noyb has filed its second complaint against OpenAI for such hallucinations, naming a specific instance in which ChatGPT reportedly -- and wrongly -- stated that a Norwegian man was a murderer. To make matters, somehow, even worse, when this man asked ChatGPT what it knew about him, it reportedly stated that he was sentenced to 21 years in prison for killing two of his children and attempting to murder his third. The hallucination was also sprinkled with real information, including the number of children he had, their genders and the name of his home town. Noyb claims that this response put OpenAI in violation of GDPR.

More than 2,000 people, including leading creative names such as Mark Haddon, Axel Scheffler, Benji Davies and Michael Rosen, have signed a letter published in the Observer today calling on the government to keep the legal safeguards that offer artists and writers the prospect of a sustainable income. John predicted the proposal "would devastate our creative community", while helping "powerful foreign technology companies". The signatories say they understand the government aim of boosting growth, but describe themselves as "staring in astonishment" at Whitehall's eagerness "to hastily wrap our live's work in attractive paper as a welcome gift to automated competitors". "Imagine asking ChatGPT to generate your child's artwork instead of asking the child. It's a horrible thought, isn't it?" said children's book author and illustrator Ged Adamson.

Self Supervised Representation Learning (SSRepL) can capture meaningful and robust representations of the Attention Deficit Hyperactivity Disorder (ADHD) data and have the potential to improve the model's performance on also downstream different types of Neurodevelopmental disorder (NDD) detection. In this paper, a novel SSRepL and Transfer Learning (TL)-based framework that incorporates a Long Short-Term Memory (LSTM) and a Gated Recurrent Units (GRU) model is proposed to detect children with potential symptoms of ADHD. This model uses Electroencephalogram (EEG) signals extracted during visual attention tasks to accurately detect ADHD by preprocessing EEG signal quality through normalization, filtering, and data balancing. For the experimental analysis, we use three different models: 1) SSRepL and TL-based LSTM-GRU model named as SSRepL-ADHD, which integrates LSTM and GRU layers to capture temporal dependencies in the data, 2) lightweight SSRepL-based DNN model (LSSRepL-DNN), and 3) Random Forest (RF). In the study, these models are thoroughly evaluated using well-known performance metrics (i.e., accuracy, precision, recall, and F1-score). The results show that the proposed SSRepL-ADHD model achieves the maximum accuracy of 81.11% while admitting the difficulties associated with dataset imbalance and feature selection.