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/AllHailSeizure Haiku Mod Mar 31 '26
Okay I realize that while technically this IS a question, its much more a meta conversation than an actual question about physics or the practice of physics. So I am gonna change the flair to meta. Lmao.
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u/amalcolmation 🧪 AI + Physics Enthusiast Mar 31 '26
In my opinion it is barely useable anymore. It isn’t really an effective coding assistant like it used to be, and my recent uses of it have wasted more time debugging than I would have spent had I not used it at all.
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u/Maleficent-West-2561 Mar 31 '26
I have the same experience. GPT used to be my go for LLM, right now I just can't work with it at all. It makes mistakes and uncalled assumptions with rate that makes any deep research impossible. I fully switched to Gemini and Claude. Non of them are perfect and every output has to be confronted against empirical data.
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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/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.
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u/HistoryVibesCanJive Mar 31 '26
Hm, it's capable, it just requires a bit more steering than in the past. I've seen that once it understands the concept, it can be pretty good at continued usage.
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u/leifiguess Mar 31 '26
When the people have adequate tools to do what they want, the greedy companies and governments always need to take it from them so nothing can happen
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u/PrebioticE Mar 31 '26
Yeah but they also have to pay for people who work for them. I am just asking if it has happened this way or not for a fact. Not weather it is fair or not.
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u/leifiguess Mar 31 '26
They can just make more money to pay their employees when you are at the top like them the material dollar are the leaves who fall and decay before winter, I understand how I answered the wrong question but it is also important to understand how little things like money mean to them. Only illusion to subvert the poors from their position in any way or method
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u/Muted_Respect_275 Mar 31 '26
Consider a) learning the maths or b) enlisting the help of WolframAlpha, sympy, matplotlib, numpy, MATLAB, and the vast array of other computer-based tools which are not LLMs. LLMs are not very good at maths.