Teams at Yale are now exploring the mechanism uncovered here and testing additional AI-generated predictions in other immune contexts.
Not only is there no validation, they have only begun even looking at it.
Again: LLMs can’t make novel ideas. This is PR, and because you’re unfamiliar with how any of it works, you assume MAGIC.
Like every other bullshit PR release of it’s kind, this is simply a model being fed a ton of data and running through thousands of millions of iterative segments testing outcomes of various combinations of things that would take humans years to do. It’s not that it is intelligent or making “discoveries”, it’s just moving really fast.
You feed it 102 combinations of amino acids, and it’s eventually going to find new chains needed for protein folding. The thing you’re missing there is:
all the logic programmed by humans
The data collected and sanitized by humans
The task groups set by humans
The output validated by humans
It’s a tool for moving fast though data, a.k.a. A REALLY FAST SORTING MECHANISM
Nothing at any stage if developed, is novel output, or validated by any models, because…they can’t do that.
I was almost with you on the whole expert act until the part where you said we feed the model “10^2 combinations of amino acids.”
You realize 10^2 is literally just 100, right?
You are writing paragraphs acting like the smartest guy in the room, but you think protein folding gets solved by checking a list shorter than a grocery receipt. That is honestly hilarious.
It kind of explains your whole point though. No wonder you think it is just a “simple sorting mechanism” if you think the dataset is that small. You might want to check the math before the next lecture because being off by about 300 zeros makes the arrogance look a bit silly.
He knows the basics, it’s just that they don’t lead to any of the conclusions he’s claiming they do. He also boldly assumes that everyone who disagrees with him doesn’t know anything. He’s a beast of confirmation bias.
You find me a model that can take multiple disparate pieces of information and combine them into a new idea not fed with a pre-selected pattern, and I’ll eat my hat. The very basis of how these models operates is in complete opposition of you thinking it can spontaneously have a new and novel idea. New…that’s what novel means.
I can pointlessly link you to papers, blogs from researchers explaining, or just asking one of these things for yourself, but you’re not going to listen, which is on you for intentionally deciding to remain ignorant to how they function.
So you can obviously see…not novel ideation. They fed it a bunch of trained data, and it correctly used the different pattern alignment to say “If it works this way otherwise, it should work this way with this example.”
Sure, it’s not something humans had gotten to get, but that’s the entire point of the tool. Good for the progress, certainly, but that’s it’s job. It didn’t come up with some new idea about anything because it works from the data it’s given, and the logic boundaries of the tasks it’s set to run. It’s not doing anything super special here, just very efficiently.
Start chewing.
You literally admitted it in your own comment: “Sure, it’s not something humans had gotten to yet.”
That is the definition of a novel discovery.
You are arguing that because the AI used logic and existing data to reach the conclusion, it doesn’t count. By that definition, no human scientist has ever had a novel idea either since we all build on existing data and patterns.
The AI looked at the same data humans had, saw a pattern humans missed, and created a solution humans didn’t have. That is novelty.
But honestly it is hard to take your analysis of these papers seriously when you just argued in the comment above that protein folding involves “10^2 combinations.”
You realize 10^2 is just 100 right?
You think complex biology is a list shorter than a grocery receipt. If your math is off by about 300 zeros I am not sure you are the best judge of what these models are actually capable of.
I notice you got real quiet about the math part. I guess realizing you think protein folding is a list of 100 items was too embarrassing to address. Ignoring it doesn’t make you look smarter.
And now you are frantically moving the goalposts. You claim it’s only “novel” if it invents the rules from scratch? By that definition, a human author never has a novel idea because they are just using grammar rules taught by a teacher.
Also: AlphaGo Move 37.
The AI played a move that human masters explicitly said was “wrong” based on human strategy. It defied the logic conventions it was fed and won. That is the literal definition of forming a conclusion independent of, and superior to, human intervention.
But please, use more periods between your words. It definitely covers up the fact that you don’t know what you’re talking about.
If there’s one bad thing about modern medicine and living in an outsized society is that intelligence is no longer evolutionarily beneficial. We are artificially selecting morons and the latest pisa results are the canary in the coal mine for the idiocracy we’re heading to.
Thank you for your efforts in demystifying these fucking ads in the form of breakthroughs that have these insufferable morons thinking “AI” can now do research.
You addressed that they haven’t tested the hypothesis completely while completely overlooking the fact that an ai suggested a novel hypothesis… even if it comes out to be wrong it is still undeniably a novel hypothesis. This is what was validated by yale…
you have still failed to answer the question. You’re also neglecting to include an explanation of temperature in your argument, which may be relevant here.
🤦🤦🤦 No…it really isn’t:
Not only is there no validation, they have only begun even looking at it.
Again: LLMs can’t make novel ideas. This is PR, and because you’re unfamiliar with how any of it works, you assume MAGIC.
Like every other bullshit PR release of it’s kind, this is simply a model being fed a ton of data and running through thousands of millions of iterative segments testing outcomes of various combinations of things that would take humans years to do. It’s not that it is intelligent or making “discoveries”, it’s just moving really fast.
You feed it 102 combinations of amino acids, and it’s eventually going to find new chains needed for protein folding. The thing you’re missing there is:
It’s a tool for moving fast though data, a.k.a. A REALLY FAST SORTING MECHANISM
Nothing at any stage if developed, is novel output, or validated by any models, because…they can’t do that.
I was almost with you on the whole expert act until the part where you said we feed the model “10^2 combinations of amino acids.” You realize 10^2 is literally just 100, right? You are writing paragraphs acting like the smartest guy in the room, but you think protein folding gets solved by checking a list shorter than a grocery receipt. That is honestly hilarious. It kind of explains your whole point though. No wonder you think it is just a “simple sorting mechanism” if you think the dataset is that small. You might want to check the math before the next lecture because being off by about 300 zeros makes the arrogance look a bit silly.
Wow, if you really do know something about this subject, you’re being a real asshole about it 🙄
He knows the basics, it’s just that they don’t lead to any of the conclusions he’s claiming they do. He also boldly assumes that everyone who disagrees with him doesn’t know anything. He’s a beast of confirmation bias.
Nah, I’m just not going to write a novel on Lemmy, ma dude.
I’m not even spouting anything that’s not readily available information anyway. This is all well known, hence everybody calling out the bubble.
You have not said one thing i did not already know, none of it has to do with anything
an ai did something novel, this is an easily verified fact. The only alternative is that somebody else wrote the hypothesis.
It most certainly did not…because it can’t.
You find me a model that can take multiple disparate pieces of information and combine them into a new idea not fed with a pre-selected pattern, and I’ll eat my hat. The very basis of how these models operates is in complete opposition of you thinking it can spontaneously have a new and novel idea. New…that’s what novel means.
I can pointlessly link you to papers, blogs from researchers explaining, or just asking one of these things for yourself, but you’re not going to listen, which is on you for intentionally deciding to remain ignorant to how they function.
Here’s Terrence Kim describing how they set it up using GRPO: https://www.terrencekim.net/2025/10/scaling-llms-for-next-generation-single.html
And then another researcher describing what actually took place: https://joshuaberkowitz.us/blog/news-1/googles-cell2sentence-c2s-scale-27b-ai-is-accelerating-cancer-therapy-discovery-1498
So you can obviously see…not novel ideation. They fed it a bunch of trained data, and it correctly used the different pattern alignment to say “If it works this way otherwise, it should work this way with this example.”
Sure, it’s not something humans had gotten to get, but that’s the entire point of the tool. Good for the progress, certainly, but that’s it’s job. It didn’t come up with some new idea about anything because it works from the data it’s given, and the logic boundaries of the tasks it’s set to run. It’s not doing anything super special here, just very efficiently.
Start chewing. You literally admitted it in your own comment: “Sure, it’s not something humans had gotten to yet.” That is the definition of a novel discovery. You are arguing that because the AI used logic and existing data to reach the conclusion, it doesn’t count. By that definition, no human scientist has ever had a novel idea either since we all build on existing data and patterns. The AI looked at the same data humans had, saw a pattern humans missed, and created a solution humans didn’t have. That is novelty. But honestly it is hard to take your analysis of these papers seriously when you just argued in the comment above that protein folding involves “10^2 combinations.” You realize 10^2 is just 100 right? You think complex biology is a list shorter than a grocery receipt. If your math is off by about 300 zeros I am not sure you are the best judge of what these models are actually capable of.
No, that’s not what novel ideation is whatsoever 🤦
Again…these models work from a list of boundaries, logic, and rules made by humans. They don’t make it up themselves because…they.fucking.cant.
If they could make their own rules and conclusions without human intervention, then you have novel ideas. But…they.100%.FUCKING.CANT.DO.THAT.
Okay, let me posit one more question to you. Please define novel ideation in technical terms.
I notice you got real quiet about the math part. I guess realizing you think protein folding is a list of 100 items was too embarrassing to address. Ignoring it doesn’t make you look smarter. And now you are frantically moving the goalposts. You claim it’s only “novel” if it invents the rules from scratch? By that definition, a human author never has a novel idea because they are just using grammar rules taught by a teacher. Also: AlphaGo Move 37. The AI played a move that human masters explicitly said was “wrong” based on human strategy. It defied the logic conventions it was fed and won. That is the literal definition of forming a conclusion independent of, and superior to, human intervention. But please, use more periods between your words. It definitely covers up the fact that you don’t know what you’re talking about.
Pearls to pigs my friend, pearls to pigs.
If there’s one bad thing about modern medicine and living in an outsized society is that intelligence is no longer evolutionarily beneficial. We are artificially selecting morons and the latest pisa results are the canary in the coal mine for the idiocracy we’re heading to.
Thank you for your efforts in demystifying these fucking ads in the form of breakthroughs that have these insufferable morons thinking “AI” can now do research.
So many people have successfully argued against claims I did not make.
https://www.emergentmind.com/papers/2409.06185
https://huggingface.co/papers/2409.04109
ai does new things all the time and this is easily validated and explained with the concept of temperature.
https://www.emergentmind.com/papers/2409.06185
https://huggingface.co/papers/2409.04109
You addressed that they haven’t tested the hypothesis completely while completely overlooking the fact that an ai suggested a novel hypothesis… even if it comes out to be wrong it is still undeniably a novel hypothesis. This is what was validated by yale…
you have still failed to answer the question. You’re also neglecting to include an explanation of temperature in your argument, which may be relevant here.