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.
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.
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.
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.
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.