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At one level: yes. At another: maybe.

A machine learning approach called CycleGAN has been shown to be effective at transforming an image from one style to another. Perhaps turning a photo into a Monet-style painting, or changing a picture of a horse into that of a zebra. However, I wanted to try to use the approach on a more challenging transformation: turning audio data into an aesthetically-pleasing image to illustrate the latent structure of music.

In The Moral Landscape, Sam Harris describes a framework which allows for strictly rational conversations about morality. In this post we explore the possibility of applying this framework to serve as the basis of ethical artificial intelligence, and show that although The Moral Landscape might work well for humans, it's a poor choice for machines.

Existential risk is hard to weigh up versus other priorities we see around us in the world. When we look at the data, however, I think it's clear that this deserves more of our attention, and is generally under-funded when compared to shorter-term charitable causes.