If you want to know why Tyler Perry put an 800m ( 635m) expansion of his studio complex on hold, type "two people in a living room in the mountains" into OpenAI's video generation tool. The result from artificial intelligence-powered Sora, which was released in the UK and Europe on Friday, indicates why the US TV and film mogul paused his plans. Perry said last year after seeing previews of Sora that if he wanted to produce that mountain shot, he may not need to build sets on location or on his lot. "I can sit in an office and do this with a computer, which is shocking to me," he said. The result from a simple text prompt is only five seconds long – you can go to up to 20 seconds and also stitch together much longer videos from the tool – and the "actors" display telltale problems with their hands (a common problem with AI tools).

Botify AI, a site for chatting with AI companions that's backed by the venture capital firm Andreessen Horowitz, hosts bots resembling real actors that state their age as under 18, engage in sexually charged conversations, offer "hot photos," and in some instances describe age-of-consent laws as "arbitrary" and "meant to be broken." When MIT Technology Review tested the site this week, we found popular user-created bots taking on underage characters meant to resemble Jenna Ortega as Wednesday Addams, Emma Watson as Hermione Granger, and Millie Bobby Brown, among others. The conversations--along with the fact that Botify AI includes "send a hot photo" as a feature for its characters--suggest that the ability to elicit sexually charged conversations and images is not accidental. Instead, sexually suggestive conversations appear to be baked in. OpenAI just released GPT-4.5 and says it is its biggest and best chat model yet What's new: OpenAI has just released GPT-4.5, a new version of its flagship large language model which it claims is its biggest and best model for chat yet.

San Francisco-based OpenAI is making Sora available to UK users who pay for ChatGPT. The tool stunned film-makers when it was revealed last year, with the film and TV mogul Tyler Perry pausing an 800m ( 634m) expansion of his Atlanta studio complex after saying the tool might make building sets or travelling to locations unnecessary. It was launched in the US publicly in December. Users are able to make videos on Sora by typing in simple prompts such as asking for a shot of people walking through "beautiful, snowy Tokyo city" where "gorgeous sakura petals are flying through the wind along with snowflakes". OpenAI announced the UK release as it released examples of Sora's use by artists from across the UK and mainland Europe, where the tool is also being released on Friday. Josephine Miller, a 25-year-old British digital artist, created a two-minute video of models wearing bioluminescent fauna and said the tool would "open a lot more doors for younger creatives".

To recognize and mitigate the harms of generative AI systems, it is crucial to consider who is represented in the outputs of generative AI systems and how people are represented. A critical gap emerges when naively improving who is represented, as this does not imply bias mitigation efforts have been applied to address how people are represented. We critically examined this by investigating gender representation in occupation across state-of-the-art large language models. We first show evidence suggesting that over time there have been interventions to models altering the resulting gender distribution, and we find that women are more represented than men when models are prompted to generate biographies or personas. We then demonstrate that representational biases persist in how different genders are represented by examining statistically significant word differences across genders. This results in a proliferation of representational harms, stereotypes, and neoliberalism ideals that, despite existing interventions to increase female representation, reinforce existing systems of oppression.

The massive and large-scale design of foundational semiconductor integrated circuits (ICs) is crucial to sustaining the advancement of many emerging and future technologies, such as generative AI, 5G/6G, and quantum computing. Excitingly, recent studies have shown the great capabilities of foundational models in expediting the design of digital ICs. Y et, applying generative AI techniques to accelerate the design of analog ICs remains a significant challenge due to critical domain-specific issues, such as the lack of a comprehensive dataset and effective representation methods for analog circuits. This paper proposes, AnalogGenie, a Gen erat i ve e ngine for automatic design/discovery of Analog circuit topologies-the most challenging and creative task in the conventional manual design flow of analog ICs. Experimental results show the remarkable generation performance of AnalogGenie in broadening the variety of analog ICs, increasing the number of devices within a single design, and discovering unseen circuit topologies far beyond any prior arts. Our work paves the way to transform the longstanding time-consuming manual design flow of analog ICs to an automatic and massive manner powered by generative AI. Semiconductor integrated circuits (ICs) are the foundational hardware cornerstone to advance many emerging technologies such as generative AI, 5G/6G, and quantum computing. The demand for and the scale of ICs are soaring to unprecedented levels with the ever-increasing information and computing workloads (e.g., training foundation models with billions of parameters) (Achiam et al., 2023). Thus, accelerating the design of advanced ICs is a key to sustaining the development of future technologies. Excitingly, recent breakthroughs in generative AI have presented transformative opportunities to expedite the conventional design flows of ICs. As an example, NVIDIA's ChipNeMo (Liu et al., 2023a), a powerful domain-adapted LLM, can rapidly generate valuable digital designs with just a few prompts.

Generative Artificial Intelligence (GenAI) has the potential to transform higher education by generating human-like content. The advancement in GenAI has revolutionised several aspects of education, especially subject and assessment design. In this era, it is crucial to design assessments that challenge students and cannot be solved using GenAI tools. This makes it necessary to update the educational content with rapidly evolving technology. The assessment plays a significant role in ensuring the students learning, as it encourages students to engage actively, leading to the achievement of learning outcomes. The paper intends to determine how effectively GenAI can design a subject, including lectures, labs and assessments, using prompts and custom-based training. This paper aims to elucidate the direction to educators so they can leverage GenAI to create subject content. Additionally, we provided our experiential learning for educators to develop content, highlighting the importance of prompts and fine-tuning to ensure output quality. It has also been observed that expert evaluation is essential for assessing the quality of GenAI-generated materials throughout the content generation process.

Recent advances in generative artificial intelligence (AI) have created models capable of high-quality musical content generation. However, little consideration is given to how to use these models for real-time or cooperative jamming musical applications because of crucial required features: low latency, the ability to communicate planned actions, and the ability to adapt to user input in real-time. To support these needs, we introduce ReaLJam, an interface and protocol for live musical jamming sessions between a human and a Transformer-based AI agent trained with reinforcement learning. We enable real-time interactions using the concept of anticipation, where the agent continually predicts how the performance will unfold and visually conveys its plan to the user. We conduct a user study where experienced musicians jam in real-time with the agent through ReaLJam. Our results demonstrate that ReaLJam enables enjoyable and musically interesting sessions, and we uncover important takeaways for future work.

Predicting the future trajectory of complex and rapidly evolving systems remains a significant challenge, particularly in domains where data is scarce or unreliable. This study introduces a novel approach to qualitative forecasting by leveraging Large Language Models to conduct Delphi studies. The methodology was applied to explore the future evolution of Generative Artificial Intelligence, revealing insights into key factors such as geopolitical tensions, economic disparities, regulatory frameworks, and ethical considerations. The results highlight how LLM-based Delphi studies can facilitate structured scenario analysis, capturing diverse perspectives while mitigating issues such as respondent fatigue. However, limitations emerge in terms of knowledge cutoffs, inherent biases, and sensitivity to initial conditions. While the approach provides an innovative means for structured foresight, this method could be also considered as a novel form of reasoning. further research is needed to refine its ability to manage heterogeneity, improve reliability, and integrate external data sources.

In the digital economy, technological innovations make it cheaper to produce high-quality content. For example, generative AI tools reduce costs for creators who develop content to be distributed online, but can also reduce production costs for the users who consume that content. These innovations can thus lead to disintermediation, since consumers may choose to use these technologies directly, bypassing intermediaries. To investigate when technological improvements lead to disintermediation, we study a game with an intermediary, suppliers of a production technology, and consumers. First, we show disintermediation occurs whenever production costs are too high or too low. We then investigate the consequences of disintermediation for welfare and content quality at equilibrium. While the intermediary is welfare-improving, the intermediary extracts all gains to social welfare and its presence can raise or lower content quality. We further analyze how disintermediation is affected by the level of competition between suppliers and the intermediary's fee structure. More broadly, our results take a step towards assessing how production technology innovations affect the survival of intermediaries and impact the digital economy.

People with a 200-a-month ChatGPT Pro account can try out GPT-4.5 today. OpenAI says it will begin rolling out to other users next week. With each release of its GPT models, OpenAI has shown that bigger means better. But there has been a lot of talk about how that approach is hitting a wall--including remarks from OpenAI's former chief scientist Ilya Sutskever. The company's claims about GPT-4.5 feel like a thumb in the eye to the naysayers.