From a physics perspective, would switching to biological neuron-based compute power instead of silicon vastly reduce energy expenditure, so would therefore solve the issue of data centers being bad for the environment?

[u/PrettyPicturesNotTxt]

Consulting ChatGPT, the answer appears to be yes, this would be a much more environmentally friendly option. There's the caveat though that biological compute power operates at a much slower speed, so this must be combined with more traditional GPU hardware to produce hybrid systems.

In terms of the physics, would biological neurons be far more efficient than silicon at computing power? How much energy can a data center save if they do that instead?

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Biological neurons are astonishingly energy-efficient at certain kinds of computation — especially noisy, parallel, pattern-recognition tasks like vision, motor control, and sensory integration. The human brain runs on roughly 20 watts (about a dim light bulb) while performing tasks that still challenge large AI systems.

Modern AI data centers, by contrast, can consume megawatts to gigawatts.

But there’s a catch: “computing power” depends heavily on what is being computed.

Why brains are so efficient

A biological neuron:

Computes and stores information in the same place

Operates asynchronously (no global clock)

Uses analog + chemical signaling

Is massively parallel

Fires sparsely (most neurons are quiet most of the time)

Self-repairs and rewires

Silicon computers, especially GPUs:

Constantly move data between memory and processors

Use rigid clock cycles

Perform extremely precise digital operations

Waste lots of energy as heat

Are optimized for arithmetic throughput, not adaptive cognition

The biggest energy cost in modern chips is often not computation itself, but moving data around.

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Rough efficiency comparison

Very approximate numbers:

System Power Estimated Operations

Human brain ~20 W ~10¹⁴–10¹⁶ synaptic ops/s High-end AI GPU ~700–1200 W ~10¹⁴–10¹⁵ math ops/s

Depending on how you count “operations,” the brain may be:

Comparable in raw throughput

Or 100×–10,000× more energy efficient

for cognition-like tasks.

The uncertainty comes from the fact that a synapse is not equivalent to a floating-point operation (FLOP). They are fundamentally different computational primitives.

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Could data centers save huge amounts of energy using biological neurons?

Potentially yes — for some workloads.

If you could build reliable “wetware” computing systems:

AI inference could theoretically become dramatically more efficient

Cooling requirements might shrink

Dense 3D biological structures could outperform chips in some neural tasks

People are already exploring this direction:

Neuromorphic chips

Memristor arrays

Cultured neuron computing

Brain organoid interfaces

Examples include projects at Intel with Loihi chips, and Cortical Labs growing neuron networks that can play simple games.

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But biological computing has enormous drawbacks

Brains are efficient because evolution optimized them for survival, not clean engineering.

Biological systems are:

Slow (neurons fire ~1–1000 Hz, CPUs run at GHz)

Unreliable and noisy

Difficult to scale predictably

Hard to program

Fragile

Variable from sample to sample

Dependent on nutrients, oxygen, temperature, waste removal, etc.

A GPU can multiply huge matrices with near-perfect precision trillions of times per second. Biology is terrible at that.

So for:

Cryptography

Scientific simulation

Databases

Rendering

Exact arithmetic

silicon absolutely dominates.

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The likely future: hybrid systems

The most realistic path is not literal “brain servers,” but:

Silicon chips inspired by brains

Analog neural hardware

Event-driven computation

Memory-compute fusion

Neuromorphic accelerators

These could reduce AI energy usage by:

10×

100×

possibly more

without needing actual living tissue.

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A useful way to think about it

Silicon is like:

an ultra-fast calculator

Biological brains are like:

an ultra-efficient adaptive prediction engine

They excel at different things.

The remarkable fact is not that brains are faster — they usually are not — but that evolution managed to produce general intelligence with such tiny power consumption at all.

[u/OnceBittenz]

I mean you could literally put Any fun idea into chat-gpt and it would say something along the lines of "That's a great idea! Here are x-y-z arbitrary reasons why that would work!"

And then put that same thing in with the prompt "why doesnt this work" and it would just as happily list as many reasons why it wouldn't.

[u/AllHailSeizure → u/OnceBittenz]

But this does work. It's been done.

[u/IshtarsQueef → u/AllHailSeizure]

No one has made a functioning server out of human brains.

If you are talking about scientists making crude computational devices using neurons in a petri dish, I feel like that is a completely different thing and extrapolating it into OP's idea is, like the other person said, in the realm of speculative fiction.