If you are one of the few people on the planet who fancies a chat with Keir Starmer, then there's a new AI model for you. A former chief of staff to a Tory minister has created Nostrada, which aims to enable users to talk with an AI version of each of the UK parliament's 650 MPs – and lets you ask them anything you want. Founded by Leon Emirali, who worked for Steve Barclay, Nostrada gives users a chance to speak to the "digital twin", trained to replicate their political stances and mannerisms. It is intended for diplomats, lobbyists and members of the public, who can find out where each MP stands on each issue, as well as each of their colleagues. "Politicians provide such a rich data source because they can't stop talking," said Emirali.

It's a very Imogen Heap way to say hello: "I've got to show you this thing – it's going to change your life!" She beams at me, showing off a mysterious black device. The musician and technologist is an electric, eccentric presence even on video call, talking passionately and changing thoughts like a rally driver turns corners. She whirls me from her kitchen floor to her living room in her family home in Havering near London, familiar to thousands of fans (AKA Heapsters) who tune in to watch her improvise, via livestream, on a grand piano. She points to a glamorous white tent on the edge of a well-kept lawn: "That's my tent I've been sleeping in, by the way," she laughs, enjoying the surprise.

Embodied AI is a rapidly advancing field that bridges the gap between cyberspace and physical space, enabling a wide range of applications. This evolution has led to the development of the Vehicular Embodied AI NETwork (VEANET), where advanced AI capabilities are integrated into vehicular systems to enhance autonomous operations and decision-making. Embodied agents, such as Autonomous Vehicles (AVs), are autonomous entities that can perceive their environment and take actions to achieve specific goals, actively interacting with the physical world. Embodied twins are digital models of these embodied agents, with various embodied AI twins for intelligent applications in cyberspace. In VEANET, embodied AI twins act as in-vehicle AI assistants to perform diverse tasks supporting autonomous driving using generative AI models. Due to limited computational resources of AVs, these AVs often offload computationally intensive tasks, such as constructing and updating embodied AI twins, to nearby RSUs. However, since the rapid mobility of AVs and the limited provision coverage of a single RSU, embodied AI twins require dynamic migrations from current RSU to other RSUs in real-time, resulting in the challenge of selecting suitable RSUs for efficient embodied AI twins migrations. Given information asymmetry, AVs cannot know the detailed information of RSUs. To this end, in this paper, we construct a multi-dimensional contract theoretical model between AVs and alternative RSUs. Considering that AVs may exhibit irrational behavior, we utilize prospect theory instead of expected utility theory to model the actual utilities of AVs. Finally, we employ a generative diffusion model-based algorithm to identify the optimal contract designs. Compared with traditional deep reinforcement learning algorithms, numerical results demonstrate the effectiveness of the proposed scheme.