Biocomputing attracts claims that range from straightforward experimental results to broad projections about intelligence and energy. This ledger keeps the wording, evidence type and current interpretation together.
| Claim | Status | Evidence reading | What the record supports | |
|---|---|---|---|---|
| Cultured neurons learned to play Pong | Peer-reviewed experiment | Strong for task adaptation | DishBrain coupled human and mouse cortical cultures to a simulated Pong environment. Performance changed during closed-loop interaction; interpretation of the mechanism remains debated. | Peer-reviewed paperchecked 2026-08-17 |
| A living-neuron computer played Doom | Public company demonstration | Demonstrated · company evidence | Cortical Labs has published a CL1 Doom demonstration. The public evidence supports a real closed-loop demo; there is no peer-reviewed Doom study in the source record used here. | Company demonstrationchecked 2026-08-17 |
| CL1 is the world's first code-deployable biological computer | Company positioning | Narrow claim | Cortical Labs uses this description for CL1. Earlier living-neural systems existed, so the wording depends on the qualifiers code-deployable and commercial device. | Company claimchecked 2026-08-17 |
| CL1 can maintain neurons for up to six months | Commercial specification | Company specification | Cortical Labs currently states that CL1's life-support environment can keep neurons alive for up to six months. | Company specificationchecked 2026-08-24 |
| Researchers can run remote experiments on human neural organoids | Peer-reviewed platform | Strong | FinalSpark's Neuroplatform exposes stimulation, recording and platform controls through remote software access; its architecture was described in a peer-reviewed 2024 paper. | Peer-reviewed platform paperchecked 2026-08-17 |
| Cortical organoids can improve on a goal-directed control task | Peer-reviewed experiment | Strong for the reported protocol | A 2026 Cell Reports study reported improved cart-pole performance under reinforcement-learning-selected stimulation, with pharmacological evidence implicating synaptic transmission. | Peer-reviewed paperchecked 2026-08-17 |
| Biocomputers use dramatically less energy than silicon AI | Open engineering question | Unproven at complete-system level | Neural tissue itself operates at low power, but fair comparison requires life support, sensing, stimulation, control electronics and matched task performance. A general complete-system advantage remains unestablished. | Peer-reviewed platform/contextchecked 2026-08-24 |
| Current biocomputers are conscious | Unsupported | No accepted evidence | Current experiments measure neural dynamics, task responses and plasticity. There is no accepted test establishing consciousness in these systems. | Peer-reviewed ethics/review articlechecked 2026-08-17 |
| A 20-unit CL1 biological-computing rack was demonstrated in Singapore | Official institutional demonstration | Strong for deployment fact | NUS Medicine, DayOne and Cortical Labs demonstrated a 20-unit CL1 system at the NUS Life Sciences Institute on 6 August 2026. NUS describes it as the first independently operated biologically integrated server rack. | Official institutional announcementchecked 2026-08-24 |
| Human cortical organoids can be maintained and mature over more than five years | Peer-reviewed developmental-organoid result | Strong for the reported culture model | A 2026 Nature study maintained human cortical organoids for more than five years and found molecular ageing that tracked time in culture. Useful five-year computing operation was outside the study. | Peer-reviewed paperchecked 2026-08-24 |
Download: CSV · JSON. Checked 17 August 2026.
Three claims worth reading in detail
Did neurons learn Pong?
The 2022 DishBrain experiment and what its performance measure actually showed.
Can a biocomputer play Doom?
What Cortical Labs demonstrated on CL1 and where the evidence currently stops.
Energy use
Why tissue power and complete-system energy are different quantities.
Consciousness
What current experiments measure and what remains unknown.