On this episode of, our hosts unpack the news from Davos, where Trump and major AI companies shared the stage at the World Economic Forum. This week, WIRED's Brian Barrett and Leah Feiger are joining the show as the new cohosts, alongside Zoë Schiffer. And our attention has been drawn to the drama going down in the quaint little town of Davos. Zoë tells us how at the World Economic Forum's event, major AI players like Anthropic have been the protagonists--sharing the spotlight with President Donald Trump, who insists on invading Greenland. Brian has been looking at how ICE activity is developing, and Leah is forcing us to think about this year's midterms because tech giants are already pouring millions into it. Plus, we dive into why OpenAI's decision to roll out ads in ChatGPT was a long time coming. Ads Are Coming to ChatGPT. Write to us at uncannyvalley@wired.com . You can always listen to this week's podcast through the audio player on this page, but if you want to subscribe for free to get every episode, here's how: If you're on an iPhone or iPad, open the app called Podcasts, or just tap this link . Today, we're starting a bit of a new chapter here on the show, and I want to introduce you to my brand new cohost, Brian Barrett, our executive editor here at WIRED, and Leah Feiger, our senior politics editor. So thrilled to be here. So longtime listeners know the show has taken on a bunch of different formats since it launched. We had the Gadget Lab days, the roundtable, news episodes. We really created this podcast because we want to bring you the best stories and the best takes about what's happening in tech and politics. That's all going to stay the same, but this time we're going to go even deeper. What trends you should be watching for, the news that's already happened or about to break, and how we are thinking about all of it.

The truth behind Trump's dramatic late-night Epstein file reversal: It wasn't a gamble, it was a tactic... and White House insiders say it's Democrats who will pay the price Doctor's warning about lesser discussed Mounjaro side effect - which has similar symptom to deadly bowel cancer The incredible new treatment that can cure liver cancer - without surgery, drugs or radiation. Roger had cirrhosis and thought he was going to die. Now he says: 'I'm so grateful' X is DOWN: Elon Musk's social media app crashes for thousands of users around the world Tom Cruise breaks his silence over ex-wife Nicole Kidman's split from Keith Urban: 'Karma' North Korea executes'big shot' couple who became'arrogant' after the success of their business, accusing them of being'anti-republic' Movie icon'lost her virginity to her stepfather at 11', seduced her friend's 17-year-old son... but took a forbidden secret to her grave Charlie Kirk's head of security finally explains the unusual hand signals his team made just moments before kill shot rang out Trump is being utterly humiliated by a dead pedophile. MAGA and his legacy are collapsing. AMANDA PLATELL: Everyone is saying the same thing about pampered Princess Beatrice and her latest PR stunt.

Large language models (LLMs) are widely applied across diverse domains, raising concerns about their limitations and potential risks. In this study, we investigate two types of bias that LLMs may display: stereotype bias and deviation bias. Stereotype bias refers to when LLMs consistently associate specific traits with a particular demographic group. Deviation bias reflects the disparity between the demographic distributions extracted from LLM-generated content and real-world demographic distributions. By asking four advanced LLMs to generate profiles of individuals, we examine the associations between each demographic group and attributes such as political affiliation, religion, and sexual orientation. Our experimental results show that all examined LLMs exhibit both significant stereotype bias and deviation bias towards multiple groups. Our findings uncover the biases that occur when LLMs infer user attributes and shed light on the potential harms of LLM-generated outputs.

We introduce Pixtral-12B, a 12--billion-parameter multimodal language model. Pixtral-12B is trained to understand both natural images and documents, achieving leading performance on various multimodal benchmarks, surpassing a number of larger models. Unlike many open-source models, Pixtral is also a cutting-edge text model for its size, and does not compromise on natural language performance to excel in multimodal tasks. Pixtral uses a new vision encoder trained from scratch, which allows it to ingest images at their natural resolution and aspect ratio. This gives users flexibility on the number of tokens used to process an image. Pixtral is also able to process any number of images in its long context window of 128K tokens. Pixtral 12B substanially outperforms other open models of similar sizes (Llama-3.2 11B \& Qwen-2-VL 7B). It also outperforms much larger open models like Llama-3.2 90B while being 7x smaller. We further contribute an open-source benchmark, MM-MT-Bench, for evaluating vision-language models in practical scenarios, and provide detailed analysis and code for standardized evaluation protocols for multimodal LLMs. Pixtral-12B is released under Apache 2.0 license.

Holistic health expert and bestselling author Deepak Chopra shares a message of hope as his latest book, "Quantum Body," is published: "We have a common identity. Bestselling author and entrepreneur Deepak Chopra may be known the world over as a holistic health and wellness guru -- he's counseled scores of people to lead better, calmer and healthier lives over the decades -- but he also has a lighter side. In an on-camera interview this week just as his new book, "Optimum Body: The New Science of Living a Longer, Healthier, More Vital Life," was published, Chopra poked a little fun at himself when asked how he takes care of personal well-being. "Well, my family doesn't take me seriously, and that's good," he said. "And so," he said, "I don't take myself seriously." Chopra went on about how he personally stays healthy. "I sleep well," he said. And my only purpose is to serve the world. I don't have any personal ambition. And that means no stress, either."

Artificial intelligence has predicted the majority of the world will be vegan by 2075. This is due to the record numbers of environmentally conscious Gen Z and Millennials ditching meat for plant-based options. Now, OpenAI's ChatGPT has shared details for the end of meat and dairy consumption after being asked to ' provide a timeline of the world going vegan starting in 2024 when Gen Z and Millennials raise awareness on animal agriculture.' The chatbot said the term'flexitarian' will become more common by 2027 as people adopt a more plant-based diet worldwide. And by 2073, 'the world is almost entirely vegan' because it is the typical diet among the current generation in 2055.

The AI generation gap: Are Gen Z students more interested in adopting generative AI such as ChatGPT in teaching and learning than their Gen X and Millennial Generation teachers? Abstract This study aimed to explore the experiences, perceptions, knowledge, concerns, and intentions of Gen Z students with Gen X and Gen Y teachers regarding the use of generative AI (GenAI) in higher education. A sample of students and teachers were recruited to investigate the above using a survey consisting of both open and closed questions. The findings showed that Gen Z participants were generally optimistic about the potential benefits of GenAI, including enhanced productivity, efficiency, and personalized learning, and expressed intentions to use GenAI for various educational purposes. Gen X and Gen Y teachers acknowledged the potential benefits of GenAI but expressed heightened concerns about overreliance, ethical and pedagogical implications, emphasizing the need for proper guidelines and policies to ensure responsible use of the technology. The study highlighted the importance of combining technology with traditional teaching methods to provide a more effective learning experience. Implications of the findings include the need to develop evidence-based guidelines and policies for GenAI integration, foster critical thinking and digital literacy skills among students, and promote responsible use of GenAI technologies in higher education. Keywords: ChatGPT; Generative AI; AI Literacy; Risks; Advantages; Holistic competencies; Challenges; Benefits 1. Introduction Generation Z (Gen Z) students have largely replaced Millennials in undergraduate programmes, with institutions of higher education now primarily enrolling students from the former (Seemiller & Grace, 2016; Shatto & Erwin, 2016). With educators welcoming a new cohort of students to campus, there is a growing concern regarding how to effectively teach this'always-on' generation; for example, a study by Pearson (2018) showed that almost half of all Gen Z-ers (47%) spend a minimum of three hours daily on YouTube. The Gen Z population, much like its predecessors - the Silent and Baby Boomer generations, followed by Generation X (Gen X) and Generation Y (also known as Millennials) - has its own unique, distinct characteristics that have been shaped by information communication technologies, social and cultural shifts, and financial volatility. As such, it is crucial for higher education institutions to effectively engage with Gen Z, in order for scholars, teachers, and university staff to understand their aforementioned characteristics (Seemiller & Grace, 2017; Shatto & Erwin, 2016; Shorey et al., 2021) and in turn, effectively and ethically integrate generative AI (GenAI) technologies into the curriculum.

MUHAMMADIYAH.OR.ID, JAKARTA – Seeing the tendency of today's generation of children closely related to social and digital media, the Vice Chairman of the Muhammadiyah Council for Library and Information Council Ismail Fahmi said that they learn Islam and meet those who are anti-Islam. Ismail, who is also the Founder of Drone Emprit, said that their interaction with those who are anti-Islam or anti-religion has made this millennial generation consider religion unimportant. Learning from this tendency, Ismail Fahmi suggested that methods of da'wah should be adjusted to suit the needs. "The communication style and the way of seeking information are essential foundation to change our da'wah methods," said Ismail at the Pesantren Digital on'Digital Da'wah Strategy' conducted by the Council for Telkomsel Taqwa on Monday (27/3). The rapid development of digital technology has impacted the authority of religion that has long been considered authoritative.

The fintech industry is constantly evolving and improving, and 2023 is no exception. It is predicted that the fintech space will multiply and reach $174 billion in 2023. The banking industry has recently experienced a massive surge in adopting fintech solutions as users become more tech-savvy. There are several emerging technologies in Fintech, and I have highlighted some of the most predominant ones that will be witnessed in 2023 below. AI and ML can transform investments, payments, banking, risk management, and related industries.

Economic issues, such as inflation, energy costs, taxes, and interest rates, are a constant presence in our daily lives and have been exacerbated by global events such as pandemics, environmental disasters, and wars. A sustained history of financial crises reveals significant weaknesses and vulnerabilities in the foundations of modern economies. Another significant issue currently is people quitting their jobs in large numbers. Moreover, many organizations have a diverse workforce comprising multiple generations posing new challenges. Transformative approaches in economics and labour markets are needed to protect our societies, economies, and planet. In this work, we use big data and machine learning methods to discover multi-perspective parameters for multi-generational labour markets. The parameters for the academic perspective are discovered using 35,000 article abstracts from the Web of Science for the period 1958-2022 and for the professionals' perspective using 57,000 LinkedIn posts from 2022. We discover a total of 28 parameters and categorised them into 5 macro-parameters, Learning & Skills, Employment Sectors, Consumer Industries, Learning & Employment Issues, and Generations-specific Issues. A complete machine learning software tool is developed for data-driven parameter discovery. A variety of quantitative and visualisation methods are applied and multiple taxonomies are extracted to explore multi-generational labour markets. A knowledge structure and literature review of multi-generational labour markets using over 100 research articles is provided. It is expected that this work will enhance the theory and practice of AI-based methods for knowledge discovery and system parameter discovery to develop autonomous capabilities and systems and promote novel approaches to labour economics and markets, leading to the development of sustainable societies and economies.