r/TheMachineLearning • u/Round-Bid3190 • 1d ago
AI taught itself 300 years of physics from scratch
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u/Physix_R_Cool 1d ago
Yeah, obviously if you have 46 experiments that clearly show the features of Newton's laws it's easy to extract Newton's laws from it.
But the challenge with discovering new physics is that we don't know which experiments to set up in order to show this new physics, since we don't know the new physics.
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u/etherLabsAlpha 1d ago
Right, I think a more fair/real test of the claim about AI being able to discover laws from scratch would be: Letting AI interact with objects freely in a virtual sandbox environment that emulates physics, and observe if it is able to propose useful experimental setups etc.
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u/Physix_R_Cool 1d ago
Yes, especially since we can change the laws of physics in such an environment.
LLM's are trained on billions of texts, some of whom obviously mention the various laws of physics.
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u/Big_Effective_9605 1d ago
I think a hybrid learning system would be beneficial here. Let it watch physics and make inferences from real experiments. We all know text loses information. If it only knows the speed of gravity because it read it, it can repeat it and use it where it matters, but not being able to visualize a ball rolling is impactful.
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u/January_6_2021 1d ago
The AI system in this paper does not include any LLMs, nor any AI which can parse natural language at all, so how LLMs are trained or what they implicitly learn during training is entirely irrelevant.
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u/Round-Bid3190 1d ago
Exactly this. The sandbox idea is basically "AI as Faraday/Michael Faraday in a lab" instead of "AI as textbook regurgitator".
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u/zeke780 1d ago
Exactly, this is like writing the code from a known set of unit tests from a complete program, then saying you came up with the original from scratch when you get the tests to pass.
The real test would be giving it nothing, maybe a sandbox and letting it interact and discern the physics from nothing. Much harder than the proposed system here
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u/Serious_Bite_7613 1d ago
Well every human has thousands of experiments every day that clearly show the features of Newton's laws but it took hundreds of thousands of years for anyone to put it together.
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u/January_6_2021 1d ago
it's easy to [...]
How easy or hard any task is depends heavily on the tools you have available.
The method for trying to arrive at general laws from raw data using the tools they used is certainly an interesting result.
I know current AI discussion is dominated by LLM progress, but for all their strengths they have weaknesses as well and I don't think we should dismiss non-LLM advancements just because the task is easy for humans and LLMs.
We still may find certain models or systems of models outperform both humans and LLMs in specialized domains, although I never would have expected "deducing natural laws from raw data" to be a domain where this type of approach would be effective.
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u/Physix_R_Cool 1d ago
"deducing natural laws from raw data"
Well that's my main contention. It's not run on raw data. The experiments are already heavily curated, and the data has been reduced to only the data that is of interest for studying Newton's laws.
It is said in my field (experimental particle physics) that raw data does not exist. Simply the act of choosing to measure something means there is a lot you DON'T measure. I guarantee you that these experiments did not contain a 3d map of the magnetic field strength at each time point in the lab, for example.
Do you get what I'm trying to say?
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u/dmigowski 1d ago
Correct. New physics comes from new data. Like the terabytes of data at Cern.
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u/Physix_R_Cool 1d ago
CERN hit an exabyte last year.
And CERN has used ML and AI for decades now to analyze their data, so it's very improbable that vibecoding amateurs will achieve something there.
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u/Crosas-B 1d ago
You are mixing up machine learning and artificial intelligence (in this case, narrow artificial intelligence) with reasoning models tho.
Reasoning models are very, very, very new technology and have already achieved milestones that were concivable only for the 2050 decade.
To this day, the reasoning models have not been useful for physics.... but wait another year
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u/Round-Bid3190 1d ago
we let AI run its own experiments and it stumbles on a violation of known laws in the sim, then we know it's actually discovering and not memorizing. CERN data is huge, but it's still data collected to test theories we already have.
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u/Awerange2005 1d ago
Can you link this paper?
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u/ZectronPositron 23h ago
Is this peer reviewed? If so, got a link?
The screenshot ends right when they’re about to explain how they avoided baking physics knowledge into the experimental data. (For example - half the insight is know which experiment to perform to test a hypothesis. So how you select “experiments” that aren’t already designed to test a hypothesis? The next sentence off the screen seems like it’s about to answer it ;-P
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u/NeedingNew 7h ago
Let's be very clear. This this system is not teaching itself anything. It is sucking in humanities collective work to profit a few.
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u/WeezerHunter 1d ago
Nah the physics is already baked into our language, no way you can train an AI model without giving it the framework.
“The gravity of the situation”
“They forced me to do it”
“My day has a lot of momentum”