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Alphabet’s DeepMind achieves historic new milestone in AI-based protein structure prediction

DeepMind, the AI technology company that’s part of Google parent Alphabet, has achieved a significant breakthrough in AI-based protein structure prediction. The company announced today that its AlphaFold system has officially solved a protein folding grand challenge that has flummoxed the scientific community for 50 years. The advance inn DeepMind’s AlphaFold capabilities could lead to a significant leap forward in areas like our understanding of disease, as well as future drug discovery and development.
The test that AlphaFold passed essentially shows that the AI can correctly figure out, to a very high degree of accuracy (accurate to within the width of an atom, in fact), the structure of proteins in just days – a very complex task that is crucial to figuring out how diseases can be best treated, as well as solving other big problems like working out how best to break down ecologically dangerous material like toxic waste. You may have heard of ‘Folding@Home,’ the program that allows people to contribute their own home computing (and formerly, game console) processing power to protein folding experiments. That massive global crowdsourcing effort was necessary because using traditional methods, portion folding prediction takes years and is extremely expensive in terms of straight cost, and computing resources.
DeepMind’s approach involves using an “Attentionb-basd neural network system” (basically a neural network that can focus on specific inputs in order to increase efficiency). It’s able to continually refine its own predictive graph of possible protein folding outcomes based on their folding history, and provide highly accurate predictions as a result.
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