The AlphaFold paper is pre-released at the Nature url Pieter provided in the original post.
Here's the pdf https://www.nature.com/articles/s41586-021-03819-2_reference.pdf, and it's supplementary information https://static-content.springer.com/esm/art%3A10.1038%2Fs41586-021-03819-2/MediaObjects/41586_2021_3819_MOESM1_ESM.pdf. The program is not listed as an author. https://www.blopig.com/blog/2021/07/alphafold-2-is-here-whats-behind-the-structure-prediction-miracle/ is a non-author's evaluation of the paper. -- rec -- -- rec -- On Wed, Jul 21, 2021 at 7:58 AM Pieter Steenekamp < piet...@randcontrols.co.za> wrote: > Prof Dave West, > > There is something different happening with the current generation of AI > compared to the previous generation. The AI generation of Alan Newell @ > Herb Simon, and I also want to include Big Blue that beat Gary Kasparov at > chess was just encoding human intelligence and making it much faster. The > AI did not contribute any novel concepts to the algorithm, the humans did > that. > > The current neural network based AI does add novelty to the solution. It > learns and gains insight from the data in ways that humans can not. > > Take AlphaFold for example, humans do not understand how to predict the > folding of a protein by analyzing the amino acid sequence; it's beyond > human understanding to do that. It's like AlphaFold looked at the 100000 > odd known examples of amino acid sequences and the resulting folded protein > structure and say - it's easy, you just look at this, then that, and the > resulting folded protein is this. Even comprehending what AlphFold is > saying is beyond human understanding - it's there to look at, it's in the > weights of the gain and biases of the many connections of the artificial > neural network, but humans can just not interpret it. > > For a human to understand AlphaFold's reasoning to solve the protein > folding problem is like expecting a 2 year old child to understand quantum > mechanics. Or like me to understand my wife's mind. > > AI does not have general intelligence, maybe it will never happen. But I > think it's safe to say that in some narrow fields, like in the protein > folding problem, AI is certainly more intelligent than humans. The > important issue is that there is evidence that AI does add novelty to the > solution. > > Pieter > > > > On Tue, 20 Jul 2021 at 22:46, Prof David West <profw...@fastmail.fm> > wrote: > >> Thirty something years ago, Alan Newell walked into his classroom and >> announced, "over Christmas break, Herb Simon and I created an artificial >> intelligence." He was referring to the program Bacon, which fed with the >> same dataset as the human deduced the same set of "laws." It even deduced a >> couple of minor ones that Bacon missed (or, at least, did not publish). >> >> Simon and Newell tried to publish a paper with Bacon as author, but were >> rejected. >> >> AlphaFold (which I think is based on a program Google announced but has >> yet to publish in a "proper" journal) is, to me, akin to Bacon, in that it >> is not "doing science," but is merely a tool that resolves a very specific >> scientific problem and the use of that tool will facilitate humans who >> actually do the science. >> >> I will change my mind when the journals of record publish a paper >> authored by AlphaFold (or kin) as author and that paper at least posits a >> credible theory or partial theory that transcends "here is the fold of the >> xyz sequence to address why that fold is 'necessary' or 'useful'. >> >> davew >> >> >> On Tue, Jul 20, 2021, at 1:12 PM, Pieter Steenekamp wrote: >> >> A year or so ago, Deepmind's AlphGo defeated the then world Go-champion >> Lee Sedol at a time when leading Ai researchers predicted it will be at >> least 10 years before AI can reach that level. But the valid question then >> was - why so excited? It's just a game. There is an interesting documentary >> on youtube about this at https://www.youtube.com/watch?v=WXuK6gekU1Y >> >> What's happening now is that AI makes scientific discoveries beyond human >> ability. >> >> Is anybody worried where it will end? >> >> I quote from https://www.nature.com/articles/s41586-021-03819-2 >> Highly accurate protein structure prediction with AlphaFold >> Proteins are essential to life, and understanding their structure can >> facilitate a mechanistic understanding of their function. Through an >> enormous experimental effort1–4, the structures of around 100,000 unique >> proteins have been determined5, but this represents a small fraction of the >> billions of known protein sequences6,7. Structural coverage is bottlenecked >> by the months to years of painstaking effort required to determine a single >> protein structure. Accurate computational approaches are needed to address >> this gap and to enable large-scale structural bioinformatics. Predicting >> the 3-D structure that a protein will adopt based solely on its amino acid >> sequence, the structure prediction component of the ‘protein folding >> problem’8, has been an important open research problem for more than 50 >> years9. Despite recent progress10–14, existing methods fall far short of >> atomic accuracy, especially when no homologous structure is available. Here >> we provide the first computational method that can regularly predict >> protein structures with atomic accuracy even where no similar structure is >> known. We validated an entirely redesigned version of our neural >> network-based model, AlphaFold, in the challenging 14th Critical Assessment >> of protein Structure Prediction (CASP14)15, demonstrating accuracy >> competitive with experiment in a majority of cases and greatly >> outperforming other methods. Underpinning the latest version of AlphaFold >> is a novel machine learning approach that incorporates physical and >> biological knowledge about protein structure, leveraging multi-sequence >> alignments, into the design of the deep learning algorithm. >> >> >> >> >> - .... . -..-. . -. -.. -..-. .. ... -..-. .... . .-. . >> FRIAM Applied Complexity Group listserv >> Zoom Fridays 9:30a-12p Mtn GMT-6 bit.ly/virtualfriam >> un/subscribe http://redfish.com/mailman/listinfo/friam_redfish.com >> FRIAM-COMIC http://friam-comic.blogspot.com/ >> archives: http://friam.471366.n2.nabble.com/ >> >> >> - .... . -..-. . -. -.. -..-. .. ... -..-. .... . .-. . >> FRIAM Applied Complexity Group listserv >> Zoom Fridays 9:30a-12p Mtn GMT-6 bit.ly/virtualfriam >> un/subscribe http://redfish.com/mailman/listinfo/friam_redfish.com >> FRIAM-COMIC http://friam-comic.blogspot.com/ >> archives: http://friam.471366.n2.nabble.com/ >> > - .... . -..-. . -. -.. -..-. .. ... -..-. .... . .-. . > FRIAM Applied Complexity Group listserv > Zoom Fridays 9:30a-12p Mtn GMT-6 bit.ly/virtualfriam > un/subscribe http://redfish.com/mailman/listinfo/friam_redfish.com > FRIAM-COMIC http://friam-comic.blogspot.com/ > archives: http://friam.471366.n2.nabble.com/ >
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