ScienceAIHardware

This Computer Is Made of Real Human Neurons (I Programmed It)

Siraj Raval
Siraj Raval•Jun 12, 2026

Why It Matters

Biological computers promise ultra‑low‑power AI processing and open a new frontier of ethical and regulatory challenges, making them a strategic focus for innovators and policymakers alike.

Key Takeaways

  • •Cortical Labs offers rent‑able biological computers with 800k human neurons.
  • •SDK lets developers program living neuron cultures via Python, real or simulated.
  • •Neuron substrate learns in real time, consuming power comparable to an LED.
  • •Ethical debate needed now; cultures aren’t conscious but raise new moral questions.
  • •Cloud access costs $300/week; hardware purchase $35k, enabling early experimentation.

Summary

The video introduces Cortical Labs' commercial biocomputer that houses 800,000 living human neurons on a multi‑electrode silicon chip, accessible through a Python SDK and a cloud‑based “wetware‑as‑a‑service” platform.

The system forms a closed‑loop where electrodes record spikes and deliver stimulation, allowing developers to train the culture to perform tasks such as Pong or Doom. Energy consumption is striking—roughly the power of an LED—far lower than comparable silicon AI accelerators. Pricing options include a $300‑per‑week cloud rental or a $35,000 on‑premise unit, with cultures remaining viable for up to six months.

The presenter demonstrates a simple program that records baseline activity, detects spikes, and triggers stimulation on another channel, causing the neurons to reorganize their firing patterns. He cites Brett Kagan’s 2022 Dishbrain project as the first closed‑loop demonstration and emphasizes that the SDK abstracts hardware details, offering a simulator for developers without physical access.

The emergence of a programmable, energy‑efficient biological substrate could reshape AI compute economics if it scales, while the lack of consciousness in the cultures does not eliminate ethical concerns. Early adopters can experiment today, but regulators and the broader tech community must address governance before commercial deployment expands.

Original Description

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I wrote Python code that ran on 800,000 living human neurons - real biological cells grown on a chip in a lab in Melbourne, Australia, rented over the cloud. This isn't a thought experiment. Cortical Labs shipped an actual SDK, and in this video I install it, record real neural activity, and train the cells to adapt to my code in a closed loop. Then we talk about what it means: a new computing substrate, the wild energy economics, and the ethics window that's open right now.
You can build this today — the SDK is on PyPI, the simulator is free, and the same code runs on real neurons if you have cloud access.
🧠 Try it yourself:
• Cortical Labs SDK (free simulator): https://corticallabs.com
• pip install cl-sdk
⏱️ Chapters
0:00 800,000 brain cells are running my code right now
0:24 Wait — what did Cortical Labs actually build?
1:17 DishBrain: when neurons learned to play Pong
1:46 Why living cells crush silicon (the energy gap is insane)
2:13 The ethics question nobody's asking yet
2:40 CL1: wetware-as-a-service ($35k to own, $300/week to rent)
3:07 How it works: the multi-electrode array
3:55 The life-support system keeping the cells alive
4:14 The SDK: real hardware OR a free simulator
4:49 The research problem every dev hits (and the fix)
6:06 Let's build your first biological computer program
6:39 Recording a baseline from living neurons
7:04 The closed loop: making neurons adapt to my code
7:36 Training neurons to PREDICT (the real experiment)
8:42 3 takeaways: substrate, energy, ethics
9:35 You can build this today
9:57 Your challenge — build one and I'll respond
💬 Build your own closed loop and drop it in the comments — I'll respond to the most interesting ones with a follow-up video.
🔎 This video was sponsored by SerpApi — the real-time search API I used to pull every Google Scholar paper and news source for this research (zero captchas):
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