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Folding @ Home useful still? (deep mind)

I just learned that the team behind deep mind and deep blue (the chess AI) have cracked the method of correctly folding proteins.  They're on par with scientific experiments.  What I'm wondering... does this make F@H obsolete?  I'm certain that all of the work done by folders and scientists for decades were a stepping stone in giving this AI what it needed to know but are we wasting our clock cycles now?  Is the project going to incorporate this AI into a distributed model, are they assisting with further number crunching, does the F@H project have any plans to assist this new initiative?


Every scientific achievement is built on the shoulders of those before them, I just hope that the immense power of the community can be leveraged to more efficiently work towards the betterment of science and humanity.


Here is the video I watched, I spent the whole video hoping they would mention F@H but I guess the entire field is full of contributors. 



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It probably will still take some time before it's competely obsolete: https://www.nature.com/articles/d41586-021-01968-y


Although the source code for AlphaFold 2 is freely available — including to commercial entities — it might not yet be particularly useful for researchers without technical expertise.


DeepMind — which has a reputation for being cagey about its work — described AlphaFold 2 in a brief presentation at CASP on 1 December. It promised to publish a paper outlining the network in more detail and to make the software available to researchers, but said little else.

“Among academics, there was a fair amount of doom and gloom,” says David Baker, a biochemist at the University of Washington in Seattle whose team developed RoseTTaFold. “If someone has solved the problem you’re working on but doesn’t disclose how they did it, how do you continue working on it?”

“I felt like I lost my job at the time,” says computational chemist Minkyung Baek, a member of Baker’s team. But DeepMind’s presentation also spurred new ideas that Baek couldn’t wait to explore. So she, Baker and their colleagues started brainstorming ways to replicate AlphaFold 2’s success.

I don't want to use the term red flags, but in science it's kind of not-done to claim you have solved something and not publish and explain how you did it. I think (hope) it will take until it's published and peer reviewed, before it picks up steam and sees wider use.


The end might be nigh though.

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