Which Face Is Real? was developed by Jevin West and Carl Bergstrom from the University of Washingtion as part of the Calling Bullshit Project.

It acts as a kind of game that anyone can play. Visitors to the site have a choice of two images, one of which is real and the other of which is a fake generated by StyleGAN.

As to what motivated them, here’s a quote from the article:

Our aim in this course is to teach you how to think critically about the data and models that constitute evidence in the social and natural sciences.

Which Face is Real?

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InfoWorld talks about the power of Microsoft’s new Cognitive Service: anomaly detection.

Fortunately, the first new cognitive service to explore other aspects of machine learning entered beta recently: adding anomaly detection to the roster. Anomaly detection is an important AI tool, analyzing time-series data for items that are outside normal operating characteristics for the data source. That makes it an extremely flexible tool because modern businesses have a lot of streamed data, from financial transactions to software logs to device telemetry. The ability to use one API to work across all these different feeds shouldn’t be underestimated, because it makes building appropriate software a lot easier.

Here’s an interesting article on creating and using custom loss functions in Keras. Why would you need to do this?

Here’s one example from the article:

Let’s say you are designing a Variational Autoencoder. You want your model to be able to reconstruct its inputs from the encoded latent space. However, you also want your encoding in the latent space to be (approximately) normally distributed.

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Chances are that you already know what TensforFlow is and why it’s important. However, as AI spreads from the lab to data science departments and into production, tools like TensorFlow will start crossing paths with the rest of enterprise IT.

TechRebublic has details on a free ebook on TensorFlow: a Guide for IT Pros.

TensorFlow is an open source software library developed by Google for numerical computation with data flow graphs. It offers tremendous opportunities for developers building machine learning into their products. This ebook looks at what TensorFlow is, where it’s headed, and how it’s being put to work.