A new artificial intelligence (AI) model developed by the Chinese company behind TikTok rocked Hollywood this week - not just because of what it can do, but what it could mean for creative industries. Created by tech giant ByteDance, Seedance 2.0 can generate cinema-quality video, complete with sound effects and dialogue, from just a few written prompts. Many of the clips said to have been made using Seedance, and featuring popular characters like Spider-Man and Deadpool, went viral. What is Seedance - and why the stir? Seedance was launched to little fanfare in June 2025 but it is the second version that came eight months later that has caused a major stir.

'We May Have a Crisis on Our Hands': The Unregulated Rise of Emotionally Intelligent AI Pillay is an editorial fellow at TIME. Pillay is an editorial fellow at TIME. At least once a month, two-thirds of people who regularly use AI turn to their bots for advice on sensitive personal issues and emotional support. Many people now report trusting their chatbots more than their elected representatives, civil servants, faith leaders--and the companies building AI. That's according to data from 70 countries, gathered by the Collective Intelligence Project (CIP).

Fomi watches you work, then scolds you when your attention wanders. It's helpful, but there are privacy issues to consider. I've tested a lot of software tools over the years designed to block distractions and keep you focused. None of them work perfectly, mostly because of context. Reddit, for example, is something I should generally avoid during the workday, so I tend to block it--this is a good decision for me overall.

The days of tech giants buying up discrete chips are over. AI companies now need GPUs, CPUs, and everything in between. Ask anyone what Nvidia makes, and they're likely to first say "GPUs." For decades, the chipmaker has been defined by advanced parallel computing, and the emergence of generative AI and the resulting surge in demand for GPUs has been a boon for the company . But Nvidia's recent moves signal that it's looking to lock in more customers at the less compute-intensive end of the AI market--customers who don't necessarily need the beefiest, most powerful GPUs to train AI models, but instead are looking for the most efficient ways to run agentic AI software.

César de la Fuente is on a mission to combat antimicrobial resistance by looking at nature's own solutions. César de la Fuente is an associate professor at the University of Pennsylvania, where he leads the Machine Biology Group. When he was just a teenager trying to decide what to do with his life, César de la Fuente compiled a list of the world's biggest problems. He ranked them inversely by how much money governments were spending to solve them. Antimicrobial resistance topped the list. Twenty years on, the problem has not gone away.

Solving complicated AI tasks with different domains and modalities is a key step toward artificial general intelligence. While there are numerous AI models available for various domains and modalities, they cannot handle complicated AI tasks autonomously. Considering large language models (LLMs) have exhibited exceptional abilities in language understanding, generation, interaction, and reasoning, we advocate that LLMs could act as a controller to manage existing AI models to solve complicated AI tasks, with language serving as a generic interface to empower this. Based on this philosophy, we present HuggingGPT, an LLM-powered agent that leverages LLMs (e.g., ChatGPT) to connect various AI models in machine learning communities (e.g., Hugging Face) to solve AI tasks. Specifically, we use ChatGPT to conduct task planning when receiving a user request, select models according to their function descriptions available in Hugging Face, execute each subtask with the selected AI model, and summarize the response according to the execution results. By leveraging the strong language capability of ChatGPT and abundant AI models in Hugging Face, HuggingGPT can tackle a wide range of sophisticated AI tasks spanning different modalities and domains and achieve impressive results in language, vision, speech, and other challenging tasks, which paves a new way towards the realization of artificial general intelligence.

People are relying on AI agents to assist them with various tasks.