The field of virtual prototyping and acceleration technologies is moving towards greater integration of cloud-based services and specialized hardware, such as FPGAs, to improve scalability, performance, and security. Researchers are exploring the trade-offs between local and cloud-based simulation environments, and developing new methodologies and tools to optimize the development workflow for embedded AI systems. Noteworthy papers include: Funky, which presents a full-stack FPGA-aware orchestration engine for cloud-native applications, allowing for high performance, utilization, scalability, and fault tolerance. Belenos, which provides a comprehensive workload characterization of finite element biomechanics using FPGAs, identifying optimal hardware configurations for Domain-Specific Accelerators and highlighting the need for architecture-aware co-design. The ARCHYTAS project, which aims to design and evaluate non-conventional hardware accelerators, including optoelectronic and neuromorphic accelerators, to tackle the power, efficiency, and scalability bottlenecks of AI.