The vision of i-RASE is to pioneer a new class of radiation sensor system-in-package (SIP) chips at the intersection of computer science- and neuroscience-oriented approaches to artificial intelligence (AI) development. The i-RASE project aims to design, build, test, and implement the first on-the-fly photon-by-photon radiation detector with transformational potential for various radiation applications, such as medical imaging, industrial inspection, scientific space instrumentation, environmental monitoring, and more. The i-RASE project will develop physics-inspired artificial neural networks (ANNs) for comprehensive sensor signal processing (SP) and real-time (RT) measurement of radiation interactions. It will compact this technology into an ultimate vision for SP embedded in hardware (HW) as an "all-in-one" SIP, enabling cost- and energy-efficient detection and intelligent radiation data output with unparalleled accuracy and speed. This approach enhances measurement precision and speed by utilizing complex SP, event characterization, and on-the-fly processing of incident radiation-induced signals in near real-time. As a result, it facilitates the retrieval of comprehensive information on incident radiation, ultimately improving measurement accuracy and speed while reducing digital data output.