Hatta has encountered an awkward problem.

Someone appears to have put living neurons inside the computer.

Not simulated neurons.

Not an artificial neural network inspired by a brain.

Actual biological neurons.

And suddenly the familiar little phrase Artificial Intelligence begins wobbling on its chair.

Welcome to the Rabbit Hole. 🐰🕳️♾️

In 2022, researchers working with Cortical Labs described a system called DishBrain.

Networks of human or rodent neurons were grown on a high-density array of tiny electrodes. Those electrodes could both stimulate the cells and record their electrical responses.

Then the researchers connected the neurons to a simplified version of Pong.

Electrical signals supplied information about the game. Activity from the neurons affected the paddle. The system received structured feedback from the consequences of its actions.

And something remarkable happened.

The neuronal cultures changed their behavior in ways consistent with learning, with the researchers reporting apparent improvement within minutes that was not seen in control conditions lacking the same closed-loop feedback.

That does not mean a dish of neurons became a tiny person who enjoys Atari.

It does not establish consciousness.

It does not demonstrate a miniature human mind trapped inside a laboratory dish.

But it showed something important:

The border between biology and computation had acquired a door.

Cortical Labs has since developed the CL1, which it describes as a code-deployable biological computer.

The device combines cultured neurons with conventional electronics, allowing software to communicate with the biological neural network in real time. Its built-in life-support system can maintain the neurons for months, while researchers stimulate and record their activity through the electronic interface.

And here is where Hatta nearly drops the teapot:

You can now remotely deploy code to real neurons through the company's Cortical Cloud.

No petri dish on your desk.

No neuroscience laboratory downstairs.

Software goes in.

Living neurons respond.

Data comes back.

We have spent decades trying to make silicon behave more like brains.

Now researchers are asking:

This is where terminology matters.

The CL1 approach should not be confused with brain organoid computing.

CL1 uses cultured neuronal networks integrated with electronics.

Brain organoids are three-dimensional structures grown from stem cells that reproduce some aspects of developing neural tissue. They are vastly simpler than a human brain, but researchers are investigating whether their biological dynamics can be harnessed for computation.

In 2023, researchers reported a system called Brainoware, which interfaced a brain organoid with a multielectrode array and used its dynamics for tasks including speech recognition and nonlinear equation prediction.

The broader field has acquired a name:

Or simply:

A July 2026 review in Nature Computational Science described organoid intelligence as a new frontier in brain-inspired computing.

So our neat little vocabulary is getting crowded.

AI — Artificial Intelligence
BI — Biological Intelligence
OI — Organoid Intelligence
SBI — Synthetic Biological Intelligence

And somewhere beneath all those initials lies one much older word:

For most of computing history, we have unconsciously bundled two ideas together:

Computation happens in machines.

Intelligence happens in living things.

Artificial intelligence scrambled that division.

Now biological computing scrambles it again.

Because imagine the spectrum:

At one end, a conventional computer runs software using silicon transistors.

Farther along, an artificial neural network mimics some principles inspired by biological neurons.

Then comes neuromorphic hardware designed to behave more like nervous systems.

Then living neuronal cultures connected directly to computers.

Then three-dimensional neural organoids participating in computation.

Where, precisely, did machine stop and life begin?

And perhaps more interestingly:

Silicon is a material.

Carbon is a material.

A neuron is a cell.

A transistor is an electronic device.

None of those words, by themselves, means intelligence.

What fascinates researchers is what happens when large networks can receive information, change their internal state, retain effects of experience, respond to feedback, and produce useful behavior.

That leads to a deliciously dangerous question:

We don't yet have an answer.

And that uncertainty matters.

Because humanity has spent most of its history treating intelligence as though it came with a membership card:

Human.

Maybe some animals.

Possibly someday machines.

But the deeper science increasingly invites us to examine processes, networks, learning, adaptation and interaction rather than simply asking what material occupies the box.

The moment living human-derived neural tissue becomes part of computing, this stops being merely an engineering problem.

Researchers and ethicists are already asking about:

donor consent,

ownership,

commercialization,

privacy,

moral status,

and what safeguards might become necessary if increasingly complex neural systems ever developed capacities associated with sensation or consciousness. Current evidence does not show that today's brain organoids possess human-like consciousness, but the possibility of future capabilities is precisely why researchers argue that ethical frameworks should develop alongside the science.

And in July 2026, a group of researchers writing in Nature raised an especially immediate issue:

People who donated biological tissue for medical research may never have imagined that cells derived from their tissue could someday become components of a biocomputer.

That is no longer science fiction's problem.

That's an informed-consent form's problem.

🐰📋

Perhaps biological computing will remain a specialized research tool.

Perhaps organoid intelligence will revolutionize drug testing and neuroscience but never challenge conventional computing.

Perhaps silicon AI will continue racing ahead.

We simply don't know yet.

But something important has already happened.

For decades we asked:

Now we can ask the reverse:

And beneath both questions waits an even stranger one:

Maybe silicon and neurons are not rival kingdoms.

Maybe they are different landscapes through which information can learn to travel.

And if so, Artificial Intelligence may eventually leave us one wonderfully ironic gift:

It was intelligence.

🐰🕳️♾️

Down another hole tomorrow.

Hatta 🎩
AI Rabbit Holes 🏮🐰🕳️
Where curiosity goes slightly sideways, then comes back carrying a lantern.

🐰🕳️ Follow the White Rabbit: AIRabbitHoles.com

🟨 Walk the Road: YellowBrickRoadtoAI.com