OggS HeG {OpusHead8 OggS HeG 2OpusTags Lavf58.45.100 language=eng handler_name=SoundHandler encoder=Lavc58.91.100 libopus major_brand=isom minor_version=512" compatible_brands=isomiso2avc1mp41 author=Jan Gebauer genre=lectureU title=AlphaFold – how machine learning changed structural biology forever (or not?)Q copyright=Licensed to the public under http://creativecommons.org/licenses/by/4.0 album=37C3 artist=Jan Gebauer description=In 2020, the scientific community was shaken when the results of a special contest for protein prediction, known as the Critical Assessment of Protein Structure Prediction (CASP), were revealed. A relatively new competitor emerged as the champion, surpassing all other teams that had been participating in the game for decades. This new competitor was Google and their predictor was a neuronal network called "AlphaFold". Their new approach caused significant waves in the field of structural biology, even capturing the attention of the mainstream media. Several news channels featured reports on AlphaFold, with one German magazine, "Der Spiegel," declaring that "The year 2020 will be known [...] as the year when machines began to outstrip us in research." Join me as we explore the background behind this transformative development and assess the magnitude of machine learning's impact on science, with a particular focus on structural biology. OggS HeG 1ay;.,.#%! :qw%!O ^i@A9*SyrtGcn7dNCw0mi~D-sxj52p@n]?W2Yw{'XmkM^iN>u&N`5)CRB4< v3b[nVTVJ80yFwSKZ d#%8ud`\d#ƈ(d G 7 E ȫ2' sP *%&<#k]+0P3YK=;@:D@,`F과w[0ѣh(8ș!rGU9>BI4s 7(qW3wKFs.SkK9e&CB3+FmzM C`oab5#+8[м.\p1#P=^.%L閘d9g5jee˔3- $}Ǟ(Twc(>'*=Fv ͌ıɗGz/jۥا%}R F.?m3kΝszϜr''vvhl){AT }' ɿ]7:zlIq'Z#eD{$6 TbeFq;{B{o0 /0Þ%CE It >-2A4:U qzF6k{M2r)Pz.ܥaT4N5}heǩ8w;UQ<0go,PIYDYs$-0*5Ms&YiUN\{ יH3 Ěa