Replying to an earlier post

To be clear, I wasn’t necessarily disagreeing about AI’s utility, just about how protein fold AI isn’t the same as LLM AI; we’ve used computer models for predictions of protein structure and genetic mutation severity for a while, though they have always been taken with a grain of salt that I fear is no longer being done - a prediction is still a prediction, after all. Doctors were already incorrectly confusing computer model predictions of genetic mutation severity for positive test results back when I was working as a genetic counselor in the 2010’s - my concern is that the widespread trust of “AI” is only going to exacerbate that.

I’m a bit confused, though. The AI doing it was AlphaFold, which is shutting down. Shouldn’t your statement be AI was already doing it? Gemini is an LLM - not the same type of thing as AlphaFold, despite the fact that they’re both called “AI,” which was the cause of my original argument. The AI that was doing the protein fold prediction is being replaced with an “AI” that can’t. It looks like there’s still RoseTTAFold, but losing the frontrunner is still not great when it’s shutting down to focus more on LLM’s.

Replying to @⁨Prathas@lemmy.zip⁩

Gemini is a completely different project.

The term “AI” is rather overloaded these days.

AlphaFold uses a combination of machine learning and physics simulations to predict the shape of a protein given its chemical formula.

Gemini is a Large Language Model which uses machine learning to predict text completion.

They both use “machine learning” but the machine learning models are wildly different. Machine learning is a technique that’s basically a fancy curve fitting approach. The curve AlphaFold is trained to mimic maps chemical formulas to shapes, while the curve Gemini mimics maps a text input to probabilities for predictions of the next letter(s).