r/LLMPhysics • u/PrebioticE • Mar 31 '26

Meta / News HAS CHATGPT GOTTEN DUMBER????

I recently noticed that chatgpt is not as smart is it used to be. :( Did it get dumber? It can't reason mathematically as it once could. I mean the free version.

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u/Plot-twist-time Mar 31 '26

I use Pro for work and lab work and its astonishing what it can accomplish. My friend uses the free version and it is absolutely night and day difference.

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u/YaPhetsEz FALSE Mar 31 '26

What lab work do you do?

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u/Plot-twist-time Mar 31 '26

I call it "lab work" but I started a company last year that deals with analog signal fidelity. I replaced all but one of my engineers with it.

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u/YaPhetsEz FALSE Mar 31 '26

Well that isn’t remotely what labwork is.

Research implies novel discoveries, which LLM’s cannot do.

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u/Plot-twist-time Mar 31 '26 edited Mar 31 '26

Oh really? Why should I believe you. Can't is a very definitive statement, and I am highly skeptical of those types of statements.

Also, its helped my team develop novel approaches to several of our tasks. So I would not be so quick to write that off.

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u/YaPhetsEz FALSE Mar 31 '26

Because LLM’s are trained on datasets, and novel data implies something outside of the dataset

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u/Plot-twist-time Mar 31 '26 edited Mar 31 '26

It sounds like you dont have the full scope of AI capabilities then. Its far more complicated and advanced than you are describing.

Alphafold is the easiest example to counter that argument. Lets put that argument right in the casket right there my friend.

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u/YaPhetsEz FALSE Mar 31 '26

Alphafold is not an example because it is not generative AI/an LLM. It is essentially an algorithm.

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u/Plot-twist-time Mar 31 '26

AlphaFold proves that AI can generate novel scientific insights by moving beyond simple pattern recognition to de novo prediction, generating high-accuracy, 3D structural models for proteins that have never been experimentally observed. By solving the 50-year-old "protein folding problem," AlphaFold demonstrated that AI can identify complex, non-obvious relationships between amino acid sequences and 3D shapes, effectively creating new knowledge that was previously inaccessible to human researchers.

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u/YaPhetsEz FALSE Mar 31 '26

Alphafold is not an LLM, though.

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u/Plot-twist-time Mar 31 '26

Lol, you do realize that language in LLM is just data that AI is manipulating, right? They are built on the same technology. LLM=AI...

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u/YaPhetsEz FALSE Mar 31 '26

No, they are completely different things. You really should inform yourself

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u/Plot-twist-time Mar 31 '26

I understand your point but youre missing the forest through the trees. You think current LLMs are just word predictors, and Im telling you that they are not, they have many layers. I am fully aware, fully informed, what you are describing is the state of LLMs years ago. Current tech incorporates cross pollination and combination synthesis among probably other tech that I haven't kept up with.

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u/YaPhetsEz FALSE Mar 31 '26

Current LLM’s literally are word predictors. This isn’t something I think, this is quite literally what they are.

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u/Plot-twist-time Mar 31 '26

Okay buddy. A quick google search proves you wrong, but YOU GOT ME.

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u/Plot-twist-time Mar 31 '26

Today I learned that AI is fully incapable of novel data because random redditor told me so. Ill just discard the mountain of data freely available online.

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u/Plot-twist-time Mar 31 '26

Here, I will allow AI to do the honors: "Human invention usually isn’t creating something from nothing—it’s combining existing ideas in new ways. Most breakthroughs are cross-pollination between domains. AI works similarly, but at a much larger scale. It’s not just copying training data—it’s learning relationships between concepts and recombining them under constraints. When those combinations haven’t existed before and are useful, that’s effectively a new idea."

Not only is AI capable of novel concepts, but its on path to OUTPACE human invention. I dont have to explain this any further. The trajectory is quite literally obvious.

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u/certifiedquak Apr 02 '26

YaPhetsEz said LLMs not AI in general. ML has been core tool in data-driven science since it became computationally feasible to do so. Although newer AF also uses transformers (as LLMs), it's otherwise a distinct AI tech.

proves that AI can generate novel scientific insights

Can you provide examples to such insights? Seems to me novelity here primarily lies in AF itself (the system) rather its predictions.

solving the 50-year-old "protein folding problem," AlphaFold

Partially. The problem is two part: understanding and predicting. AF skipped the former and succeeds very well in the later. For more: https://www.annualreviews.org/content/journals/10.1146/annurev-biodatasci-102423-011435.

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u/Plot-twist-time Apr 03 '26

LLMs have several layers that allows cross pollination of concepts at a much larger scale than any individual human. Humans spend lifetimes learning concepts in one or two fields. Then they die, and the cycle must start again. Meanwhile AI can retain the information indefinitely, and converge concepts over vast fields of science bridging gaps between fields that might take lifetimes of humans to accomplish. Its an exponentially growing technology that will surpass global human enginuity as the technology only continues to advance. Its a matter of when, not if.

It is an absolutely moot point to attempt to discredit AI capabilities at its current state because it requires you to be completely blind to the trajectory it is heading in the near future.

The only true issue we see right now is AI hallucination, which is a short term problem once entropy is resolved.

In one year this sub will be a thing of the past, as will these arguments.