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These technologies, often described as artificial intelligence, are helping scientists in fields as diverse as understanding the evolution of stars and boosting drug discovery.īut this transformation isn’t without its risks. The combination of masses of data and computing power, combined with powerful methods for spotting patterns known as neural networks, are fast transforming the scientific landscape.
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That profit came entirely from selling its AI to other arms of the Alphabet empire, including tech that improves the efficiency of Google’s voice assistant, its Maps service, and the battery life on its Android phones.ĪI’s complicated role in scientific discovery DeepMind ran at a loss for years, with Alphabet writing off $1.1 billion of debt incurred from those losses in 2019, but it turned a modest profit of $60 million for the first time in 2020. The allure of “artificial general intelligence” perhaps explains why DeepMind’s owner Alphabet (then known as Google), which paid more than $500 million for the lab in 2014, has historically allowed it to work on areas it sees as beneficial to humanity as a whole, even at great immediate cost to the company. But some researchers and AI experts have raised concerns that even if machine learning research does accelerate the pace of scientific progress, it could also concentrate wealth and power in the hands of a tiny number of companies, threatening equity and political participation in wider society.
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The DeepMind CEO has described AlphaFold as a “gift to humanity.” A DeepMind spokesperson told TIME that the company was making AlphaFold’s code and data freely available for any use, commercial or academic, under irrevocable open source licenses in order to benefit humanity and the scientific community. Hassabis has described solving scientific challenges as necessary steps toward that end goal which, if successful, could transform scientific progress and human prosperity. The AlphaFold project is good publicity for DeepMind, whose stated end goal is to build “artificial general intelligence,” or a theoretical computer that could carry out most imaginable tasks more competently and quickly than any human. Read More: Demis Hassabis Is on the 2017 TIME 100 “It’s sort of like unlocking scientific exploration at digital speed.” “Now you can look up a 3D structure of a protein almost as easily as doing a keyword Google search,” Hassabis said. The disclosure, DeepMind CEO Demis Hassabis told reporters, would turbocharge the world of biology, facilitating faster work in fields as diverse as sustainability, food security and neglected diseases. On Thursday, DeepMind announced that it would now be making its predictions of the 3D structures of 200 million proteins-almost all that are known to science-available to the entire scientific community. “AlphaFold has provided the ability to transform the speed and capability of our research.” “The use of AlphaFold was really transformational, giving us a really sharp view of this malaria surface protein,” Higgins told reporters, adding that the new clarity had allowed his team to begin testing new vaccines that targeted the protein. When DeepMind gave Higgins and his colleagues access to AlphaFold, the team was amazed by the results.