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We've already talked about neural nets in some detail (links below), and in particular we've been blown away by the way that image recognition from convolutional neural nets can be fed into recurrent neural nets that generate descriptions and captions of the images. Our episode today tells a similar tale, except today we're talking about a blog post where the author fed in wireframes of a website design and asked the neural net to generate the HTML and CSS that would actually build a website that looks like the wireframes. If you're a programmer who thinks your job is challenging enough that you're automation-proof, guess again...

Link to blog post: https://blog.floydhub.com/turning-design-mockups-into-code-with-deep-learning/

Auto-generating websites with deep learning

It's been a nasty flu season this year. So we were remembering a story from a few years back (but not covered yet on this podcast) about when Google tried to predict flu outbreaks faster than the Centers for Disease Control by monitoring searches and looking for spikes in searches for flu symptoms, doctors appointments, and other related terms. It's a cool idea, but after a few years turned into a cautionary tale  of what can go wrong after Google's algorithm systematically overestimated flu incidence for almost 2 years straight. 

Relevant link: https://gking.harvard.edu/publications/parable-google-flu%C2%A0traps-big-data-analysis

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