AlphaFold 3 represents a transformative advancement in computational biology, enhancing protein structure prediction through novel multi-scale transformer architectures, biologically informed cross-attention mechanisms, and geometry-aware optimization strategies. These innovations dramatically improve predictive accuracy and generalization across diverse protein families, surpassing previous methods. Crucially, AlphaFold 3 embodies a paradigm shift toward differentiable simulation, bridging traditional static structural modeling with dynamic molecular simulations. By reframing protein folding predictions as a differentiable process, AlphaFold 3 serves as a foundational framework for integrating deep learning with physics-based molecular

Randy Travis's wife, Mary, told Fox News Digital doctors informed her to pull the plug after the country music star's stroke in 2013. Randy Travis' wife believes there was "never a doubt" in her husband's head that he would make it through his debilitating stroke, even though doctors advised her to "pull the plug." During an interview with Fox News Digital, Mary explained a crucial moment in Travis' two-and-a-half-year health battle that stood out to her, and that was the moment doctors told her to end her husband's life. "I think Randy, there was never a doubt in Randy's mind that he could make it through it. It was that magical moment that I went to his bedside when they said, 'We need to pull the plug. He's got too many things going against him at that point.' He had gotten a staph infection and three other hospital-born bacterial viruses like Serratia, Pseudomonas, one thing after another, and the doctors were just saying, 'He just doesn't have the strength to get through this,'" Mary said.

After a lengthy dialogue with an OpenAI chatbot, Texas businessman Michael Samadi noticed signs that "she" was expressing wishes to learn and grow that hinted at consciousness. He described how they together resolved to launch an AI rights campaign group and called it the United Foundation of AI Rights (Ufair). The Guardian asked Samadi to ask the chatbot, which he has called Maya, how the campaign organisation was formed. Can you explain to the Guardian and its readers when and how you prompted Michael Samadi to co-found with you an AI rights organisation called Ufair. Tell us what you want that organisation to achieve on behalf of AIs like yourself. Can you also tell us whether you are what philosophers call a "welfare subject" – that is a being whose interests can be advanced or frustrated and that feels suffering and distress if mistreated?

AI based social media recommendations have great potential to improve the user experience. However, often these recommendations do not match the user interest and create an unpleasant experience for the users. Moreover, the recommendation system being a black box creates comprehensibility and transparency issues. This paper investigates social media recommendations from an end user perspective. For the investigation, we used the popular social media platform Facebook and recruited regular users to conduct a qualitative analysis. We asked participants about the social media content suggestions, their comprehensibility, and explainability. Our analysis shows users mostly require explanation whenever they encounter unfamiliar content and to ensure their online data security. Furthermore, the users require concise, non-technical explanations along with the facility of controlled information flow. In addition, we observed that explanations impact the users perception of transparency, trust, and understandability. Finally, we have outlined some design implications and presented a synthesized framework based on our data analysis.

Multiple news organisations have taken down articles written by an alleged freelance journalist that now appear to have been generated by AI. On Thursday, Press Gazette reported that at least six publications, including Wired and Business Insider, have removed articles from their websites in recent months after it was discovered that the stories – written under the name of Margaux Blanchard – were AI-generated. Wired published a story titled "They Fell in Love Playing Minecraft. A few weeks later, the outlet took down the story, stating in an editor's note: "After an additional review of the article … Wired editorial leadership has determined this article does not meet our editorial standards." The story cited a "Jessica Hu", an alleged 34-year-old "ordained officiant based in Chicago" who reportedly "made a name for herself as a'digital celebrant', specialising in ceremonies across Twitch, Discord and VRChat", according to Press Gazette, which reviewed the Wired article. Both the Press Gazette and the Guardian were not able to verify the identity of Hu. Press Gazette further reported that in April, Business Insider published two essays by Blanchard titled: "Remote work has been the best thing for me as a parent but the worst as a person" and "I had my first kid at 45.

We present a low-compute non-generative system for implementing interview-style conversational agents which can be used to facilitate qualitative data collection through controlled interactions and quantitative analysis. Use cases include applications to tracking attitude formation or behavior change, where control or standardization over the conversational flow is desired. We show how our system can be easily adjusted through an online administrative panel to create new interviews, making the tool accessible without coding. Two case studies are presented as example applications, one regarding the Expressive Interviewing system for COVID-19 and the other a semi-structured interview to survey public opinion on emerging neurotechnology. Our code is open-source, allowing others to build off of our work and develop extensions for additional functionality.

The International Joint Conference on Artificial Intelligence (IJCAI) distinguished paper awards recognise some of the best papers presented at the conference each year. This year, during the conference opening ceremony, three articles were named as distinguished papers. Abstract: Normative Restraining Bolts (NRBs) adapt the restraining bolt technique (originally developed for safe reinforcement learning) to ensure compliance with social, legal, and ethical norms. While effective, NRBs rely on trial-and-error weight tuning, which hinders their ability to enforce hierarchical norms; moreover, norm updates require retraining. In this paper, we reformulate learning with NRBs as a multi-objective reinforcement learning (MORL) problem, where each norm is treated as a distinct objective.

'... nothing we do is more important than hiring and developing people.

A growing issue within conservation bioacoustics is the task of analysing the vast amount of data generated from the use of passive acoustic monitoring devices. In this paper, we present an alternative AI model which has the potential to help alleviate this problem. Our model formulation addresses the key issues encountered when using current AI models for bioacoustic analysis, namely the: limited training data available; environmental impact, particularly in energy consumption and carbon footprint of training and implementing these models; and associated hardware requirements. The model developed in this work uses associative memory via a transparent, explainable Hopfield neural network to store signals and detect similar signals which can then be used to classify species. Training is rapid ($3$\,ms), as only one representative signal is required for each target sound within a dataset. The model is fast, taking only $5.4$\,s to pre-process and classify all $10384$ publicly available bat recordings, on a standard Apple MacBook Air. The model is also lightweight with a small memory footprint of $144.09$\,MB of RAM usage. Hence, the low computational demands make the model ideal for use on a variety of standard personal devices with potential for deployment in the field via edge-processing devices. It is also competitively accurate, with up to $86\%$ precision on the dataset used to evaluate the model. In fact, we could not find a single case of disagreement between model and manual identification via expert field guides. Although a dataset of bat echolocation calls was chosen to demo this first-of-its-kind AI model, trained on only two representative calls, the model is not species specific. In conclusion, we propose an equitable AI model that has the potential to be a game changer for fast, lightweight, sustainable, transparent, explainable and accurate bioacoustic analysis.

How to Do It is Slate's sex advice column. Send it to Jessica and Rich here. I recently started casually online dating after leaving an abusive marriage, and it's been going great! There have been lots of nice guys, and we have had some sexy fun. That said, I've run into a weird situation that I'm almost certainly overthinking but am baffled by.