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  • Big Pharma Buys Into Crowdsourcing for Drug Discovery.

    Part of the problem is simply that drug design is hard. But many researchers point to the systems of paywalls and patents that lock up data, slowing the flow of information. So a nonprofit called the Structural Genomics Consortium is countering with a strategy of extreme openness. They’re partnering with nine pharmaceutical companies and labs at six universities, including Oxford, the University of Toronto, and UNC Chapel Hill. They’re pledging to share everything with each other—drug wish lists, results in open access journals, and experimental samples—hoping to speed up the long, expensive drug design process for tough diseases like Huntington’s.

  • AI Could Revolutionize War as Much as Nukes.

    As time goes on, improvements in AI and related technology may also shake up balance of international power by making it easier for smaller nations and organizations to threaten big powers like the US. Nuclear weapons may be easier than ever to build, but still require resources, technologies, and expertise in relatively short supply. Code and digital data tend to get cheap, or end up spreading around for free, fast. Machine learning has become widely used and image and facial recognition now crop up in science fair projects.

  • Artificial intelligence suggests recipes based on food photos.

    There are few things social media users love more than flooding their feeds with photos of food. Yet we seldom use these images for much more than a quick scroll on our cellphones.

    Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) believe that analyzing photos like these could help us learn recipes and better understand people's eating habits. In a new paper with the Qatar Computing Research Institute (QCRI), the team trained an artificial intelligence system called Pic2Recipe to look at a photo of food and be able to predict the ingredients and suggest similar recipes.

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Data Links is a periodic blog post published on Sundays (specific time may vary) which contains interesting links about data science, machine learning and related topics. You can subscribe to it using the general blog RSS feed or this one, which only contains these articles, if you are not interested in other things I might publish.

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