Der Beitrag A Star Professor—And Her Radical, AI-Powered Plan To Discover New Drugs erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.
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“It happens at pretty much any event that has tech people,” Koller says when asked about one recent snapshot. “It’s a little awkward. It’s not like I feel like this is something I deserve.”
Selfie requests are just one sign of Koller’s stardom, earned from more than 20 years bridging computer science, biology and education. She chalked up a string of accolades along the way: getting a master’s degree from Jerusalem’s Hebrew University at 18; becoming a Stanford University professor focused on machine learning at 26; winning, nearly a decade later, a MacArthur “genius grant” for research that combined artificial intelligence and genomics; cofounding $1 billion (valuation) Coursera , an early platform to let people around the world take university classes for free.
The next act for this 51-year-old innovator: Insitro, a firm in South San Francisco that aims to find new drugs by sorting through masses of data. If it succeeds, it will have overturned how drugs get discovered.
Lab biologists typically focus on a few specific proteins as drug targets. If those fail, data scientists make suggestions for others to try. Insitro, on the other hand, wants to collect much more data before the biologists go off on their hunt. It will leverage advances in bioengineering (such as Crispr gene editing) and in software that enables computers to see things that escape humans.
Koller describes her aha moment this way: “Machine learning is now doing amazing things if you give it enough data. We finally have the opportunity to create biological data at scale.”
“There are very few individuals who understand both sides of the beast,” says Mani Subramanian, who heads liver disease clinical research at Gilead. “The biology as well as the deep learning.”
Insitro’s computational experts and biologists work together to create lab experiments to produce massive custom data sets. Machine learning models then find patterns to suggest new tests and potential therapies. Robotics like automated pipetting machines reduce human error. With all this, Insitro can do “experiments in a matter of weeks instead of years,” Koller says.
AI plus biology, her background, was a “marriage made in heaven” for investors, she says. Within six months Koller raised $100 million from ARCH Ventures, Andreessen Horowitz, Foresite Capital, Alphabet’s venture fund GV and Third Rock, with Jeff Bezos and others joining later. In April, she landed a deal with Gilead Sciences that gives Insitro $15 million now with $1 billion to follow if it helps find a treatment for a deadly form of nonalcoholic fatty liver disease. The disease is expected to soon become the leading cause of liver transplants.
“There are very few individuals who understand both sides of the beast,” says Mani Subramanian, who heads liver disease clinical research at Gilead. “The biology as well as the deep learning.” […]
Der Beitrag A Star Professor—And Her Radical, AI-Powered Plan To Discover New Drugs erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.
]]>Der Beitrag Battle of the brains – Google leads in the race to dominate artificial intelligence erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.
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The competition today is not between humans and machines but among the world’s technology giants, which are investing feverishly to get a lead over each other in AI.
Growing computing power
An exponential increase in the availability of digital data, the force of computing power and the brilliance of algorithms has fuelled excitement about this formerly obscure corner of computer science. The West’s largest tech firms, including Alphabet (Google’s parent), Amazon, Apple, Facebook, IBM and Microsoft are investing huge sums to develop their AI capabilities, as are their counterparts in China. Although it is difficult to separate tech firms’ investments in AI from other kinds, so far in 2017 companies globally have completed around $21.3bn in mergers and acquisitions related to AI, according to PitchBook, a data provider, or around 26 times more than in 2015.
Machine learning is the branch of AI that is most relevant to these firms. Computers sift through data to recognise patterns and make predictions without being explicitly programmed to do so. The technique is now used in all manner of applications in the tech industry, including online ad targeting, product recommendations, augmented reality and self-driving cars. Zoubin Ghahramani, who leads AI research at Uber, believes that AI will be as transformative as the rise of computers.
AI and databases
One way to understand AI’s potential impact is to look at databases. From the 1980s these made it cheap to store information, pull out insights and handle cognitive tasks such as inventory management. Databases powered the first generation of software; AI will make the next far more predictive and responsive, says Frank Chen of Andreessen Horowitz, a venture-capital firm. An application such as Google’s Gmail, which scans the content of e-mails and suggests quick, one-touch replies on mobile devices, is an early example of what could be coming. […]
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Der Beitrag Battle of the brains – Google leads in the race to dominate artificial intelligence erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.
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