English: "Architecture of an OI system for biological computing. At the core of OI is the 3D brain cell culture (organoid) that performs the computation. The learning potential of the organoid is optimized by culture conditions and enrichment by cells and genes critical for learning (including IEGs). The scalability, viability, and durability of the organoid are supported by integrated microfluidic systems. Various types of input can be provided to the organoid, including electrical and chemical signals, synthetic signals from machine sensors, and natural signals from connected sensory organoids (e.g. retinal). We anticipate high-resolution output measurement both by electrophysiological recordings obtained via specially designed 2D or 3D (shell) MEA, and potentially from implantable probes, and imaging of organoid structural and functional properties. These outputs can be used directly for computation purposes and as biofeedback to promote organoid learning. AI and machine learning are used throughout to encode and decode signals and to develop hybrid biocomputing solutions, in conjunction with a suitable big-data management system."