I would like to ask a few questions here. What key architectural innovations does the APU introduce to achieve its unprecedented performance and efficiency for

I would like to ask a few questions here. What key architectural innovations does the APU introduce to achieve its unprecedented performance and efficiency for AI agent workloads, and how do these design choices differ from existing AI chip architectures? How can the APU's tight hardware-software co-design approach, with the hardware optimized for common agent algorithms and an open software stack, streamline the development and deployment of intelligent agent systems across diverse domains? In what ways does the APU's open source nature and collaborative development model have the potential to accelerate innovation in AI hardware and software, compared to proprietary approaches? How can the APU's cloud-based agile development methodology, leveraging open source EDA tools and PDKs, enable a more efficient and accessible chip design process, and what challenges need to be overcome to make this vision a reality? As the APU aims to catalyze a new wave of intelligent systems spanning research, startups, and industry, what specific application areas or sectors do you envision being most transformed by this technology, and how will it enable new possibilities in these domains?