Brain Organoid Computing -- an Overview

TL;DR

Brain organoid computing addresses the growing limits of silicon-based AI by proposing biological substrates that exhibit plasticity, parallelism, and energy efficiency. The paper surveys opportunities, challenges, and potential applications, drawing on recent experiments and platforms such as MEA-readouts and remote-access infrastructures. It discusses the mortal computing paradigm and the integration with neuromorphic research as pathways to adaptive, low-power AI, while foregrounding ethical and reproducibility concerns. The work highlights that, although conceptually promising, real-world deployment awaits breakthroughs in lifespan, interfacing, and standardization, making this a foundational field for future multidisciplinary research.

Abstract

The aim of this paper is to give an overview of brain organoid computing, its characteristics, challenges, as well as possible advantages for future applications in the field of artificial intelligence. An important part is the extensive bibliography covering all relevant aspects and questions on this topic. Brain organoids - three-dimensional in vitro neural structures derived from human stem cells - have recently garnered attention not only in medical research but also as potential substrates for unconventional computing. Their biological nature allows them to exhibit learning behavior, plasticity, and parallel information processing, making them fundamentally different from traditional silicon-based systems. This opens up new perspectives on how intelligent systems might be designed in the future. Using brain organoids for computing presents a possible pathway towards more adaptive, energy-efficient, and biologically inspired forms of AI. However, challenges persist, particularly regarding lifespan, interfacing, reproducibility, and ethical concerns regarding the use of human-derived tissue. This paper aims to provide a foundational understanding for researchers exploring the convergence of human biology and computation.