DeepMind’s AlphaFold AI has solved a 50-year old problem of biology
December 1, 2020 6:11:01 pm
A Deepmind Health logo sits displayed on the screen of an Apple Inc. iPhone in this arranged photograph in London, U.K. on Monday, Nov. 26, 2018. Three years ago, artificial intelligence company DeepMind Technologies Ltd. embarked on a landmark effort to transform health care in the U.K. Now plans by owner Alphabet Inc. to wrap the partnership into its Google search engine business are tripping alarm bells about privacy. Photographer: Jason Alden/Bloomberg
Google’s artificial intelligence unit took a giant step to predict the structure of proteins, potentially decoding a problem that has been described as akin to mapping the genome. DeepMind Technologies Ltd’s AlphaFold reached the threshold for “solving” the problem at the latest Critical Assessment of Structure Prediction competition. The event started in 1994 and is held every two years to accelerate research on the topic.
Different folds in a protein determine how it will interact with other molecules, and understanding them has implications for discovering how new diseases like Covid-19 invade our cells, designing enzymes to break down pollutants and improving crop yields.
DeepMind became a subsidiary of Google after a 2014 acquisition and is best known for its gamer AI, teaching itself to beat Atari video games and defeating world-renowned Go players like Lee Sedol. The company’s ambition has been to develop AI that can be applied to broader problems, and it’s so far created systems to make Google’s data centers more energy efficient, identify eye disease from scans and generate human-sounding speech.
“These algorithms are now becoming strong enough and powerful enough to be applicable to scientific problems,” DeepMind Chief Executive Officer Demis Hassabis said in a call with reporters. After four years of development “we have a system that’s accurate enough to actually have biological significance and relevance for biological researchers.”
DeepMind is now looking into ways of offering scientists access to the AlphaFold system in a “scalable way,” Hassabis said.
