This group explores the rapidly evolving domain of Artificial Intelligence Hardware and Decentralized Compute Infrastructure, with a focus on scalable, secure, and energy-efficient architectures for AI workloads. As AI systems proliferate across edge devices, sovereign data centers, and modular compute networks, the demand for specialized silicon, open-source accelerators, and interoperable AI pipelines is reshaping the global hardware and infrastructure landscape. We welcome professionals, researchers, and entrepreneurs advancing innovations in neuromorphic chips, edge TPU deployment, decentralized training paradigms, and low-latency inference hardware.

This space also facilitates critical discourse on supply chain sovereignty, compute governance, and the political economy of AI hardware—fostering collaborations that aim to push the boundaries of post-cloud, post-foundry intelligence systems.

AI edge computing, AI accelerators, RISC-V, neuromorphic processors, FPGA for AI, decentralized GPU networks, AI inference engines, sovereign compute, open hardware, TinyML, ASIC AI chips, hardware startups, Decentralized Physical Infrastructure Networks (DePIN), SynSense, Tenstorrent, Hailo, Mythic AI, Modular, Graphcore, decentralized training frameworks.