Walrus: Physics might be entering its own “LLM moment.”

What if one AI model could simulate all fluids, from ocean currents to plasma in space?

The problem:

Simulating liquids and gases has always been slow and expensive.

And that’s the reason current AI models are limited to one specific use case.

But that’s starting to change.

Here comes Walrus, a transformer model that can simulate liquids, gases, and plasmas in a general way.

It’s even open-source.

What’s different with Walrus?

Instead of focusing on one system, Walrus learns how physics behaves broadly.

It predicts the next state of a system from past states , similar to how models like ChatGPT predict the next word.

The key idea: “jittering”

Simulations break down over time because small errors keep adding up.

Walrus fixes this with a simple trick:

– Slightly shift the data at every step

In simple language: 

Imagine you’re trying to walk straight ahead with your eyes closed.

Each step you take is slightly off, maybe a tiny bit to the right.

At first, it’s barely noticeable.

But after 100 steps, you have drifted far off course.

That’s exactly what happens in simulations:

tiny errors -> keep adding -> completely wrong result

Now add “jittering”

Instead of always stepping straight (and slightly right), you:

– Randomly adjust your direction a tiny bit each step, left, right, forward

Now:

Your errors don’t keep pushing you in one direction

They cancel each other out over time

This is actually a good move toward general-purpose physics models.

What do you think?

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