---
title: "Organoid Array Computing"
description: "Leung, Loewith and Frisch's proposed biocomputing architecture: dozens of miniature human brain organoids, each a node interfaced with its own high-density microelectrode array and linked by a…"
type: "glossary-term"
canonical_url: "https://antikythera.wiki/terms/organoid-array-computing"
md_url: "https://antikythera.wiki/md/terms/organoid-array-computing"
last_updated: "2026-09-06"
site: "Antikythera Wiki"
---

# Organoid Array Computing

> A working definition written for this wiki from the reading notes; not Antikythera's own wording. From Antikythera Wiki (https://antikythera.wiki/terms/organoid-array-computing), an independent guide to Antikythera's published work.

Leung, Loewith and Frisch's proposed biocomputing architecture: dozens of miniature human brain organoids, each a node interfaced with its own high-density microelectrode array and linked by a multichambered microfluidic device, used together as the untrained *reservoir* in a reservoir-computing framework, with only a linear classifier trained on the readout. Reservoir computing is chosen precisely because it is substrate-independent — it lets messy, unengineerable tissue be used as-is. The claimed gains are parallel "task-pooling intelligence," assembloid learning, and regional specialization; the claimed advantage over ANNs is that the hardware's topology develops. Note the internal tension: the reservoir is by definition untrained, which sidelines the plasticity that motivates the design.

## Appears in

- [Organoid Array Computing: The Design Space of Organoid Intelligence](https://antikythera.wiki/work/journal/coginfra/organoid-array-computing) (2025-05-10)
- [Cognitive Infrastructures](https://antikythera.wiki/work/journal/coginfra) (2025-05-10)

_Glossary generated 2026-09-06._