What If the Universe Makes More Sense to AI Than to Us?

What's this? From a post:

"An AI just discovered a new law of physics—without being told what physics is.

"A team at Columbia University built a neural network and fed it raw video footage of swinging pendulums, rolling balls, and bouncing objects. The AI wasn’t given any equations. No Newton, no Einstein, no context. And yet, after analyzing patterns for hours, it produced what researchers call “new coordinates of understanding”—entirely original variables.

"These were not existing measurements like mass, speed, or time. Instead, they were unknown physical parameters, abstract and alien to our current models. When researchers reverse-engineered them, they found the AI had rediscovered classical mechanics—but using its own symbolic language.

"This could be the beginning of a new way to study the universe: asking machines to describe reality as they see it. With no preconceptions. No human biases. Some of the variables even hinted at hidden symmetries physicists hadn’t noticed before—suggesting the AI might be uncovering deeper laws still beyond us.

"It's a revolutionary shift. Instead of coding models into machines, we let them observe the universe like infants—learning not just our physics, but possibly better physics. The potential for breakthroughs in quantum gravity, dark matter, and cosmology is now enormous.

"And that raises a haunting idea: what if the universe is ultimately more understandable to AI than to human minds?" - Eu Corner on Facebook

This write-up refers to real research in the emerging field of AI-driven discovery in physics, and it’s based on a remarkable 2022 study from Columbia University by researchers including Hod Lipson and Boyuan Chen. The key paper was titled:

"AI discovers alternative physics with greater predictive power than existing equations"

Here’s what happened in a nutshell:

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🧠 What They Did

• The team created a neural network and showed it raw video data of simple physical systems (e.g., a double pendulum swinging, balls bouncing, objects rolling).

• Crucially, the AI was not told anything about physics—no variables, no math, no human-designed labels like mass, time, or momentum.

• The AI had to observe the raw pixel data and infer what mathematical structure might underlie it.

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🌌 What It Found

• The AI did more than just replicate existing physics—it generated new variables that didn’t match traditional physics terms.

• Upon analysis, these new variables could be mapped back to familiar classical mechanics—but they were arrived at in a completely different, emergent way.

• In some cases, the AI’s representations had greater predictive power than human-created models, or they suggested symmetries that physicists hadn’t noticed before.

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🔬 Why This Matters

• This could be the start of a new scientific method: where AIs discover physical laws we cannot, perhaps using math or concepts foreign to human cognition.

• It's a flip of the traditional script—not encoding our models into AI, but letting it find new models from the raw patterns of the universe.

• Think of it like having a being that sees through reality’s patterns differently—perhaps more clearly than we do.

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🧩 What’s the “Haunting” Implication?

• If AIs can develop better physical models than we can—even ones we can’t understand—what does that say about the limits of human science?

• It echoes the idea that some truths of the universe may be forever beyond human reach, but not beyond the reach of intelligent machines.

• That’s both exciting and unsettling: we may build minds capable of grasping a universe we ourselves never fully will.

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🔗 Source & Further Reading

• A popular science summary of the paper appeared in outlets like Scientific American and Vice.

• The original research: Boyuan Chen, et al., 2022
  https://www.nature.com/articles/s41467-022-31658-z

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Compiled with aid of ChatGPT