• AI and ML are transforming new areas in unexpected ways.
• The more data you have on a topic, the more likely you are to
to derive concrete information.
• Models developed for a particular situation may not be
suitable for another, even similar.
Let’s take a tree leaf: it’s hard to imagine that it contains data, but
its degree of humidity can, for example, help predict the spread of a
forest fire.
“Dry plants ignite, wet plants don’t,” says Krishna Rao, a PhD
student in earth system science at Stanford University. It may seem
obvious, but the line between too dry or wet enough is actually quite
blurred. This is why Rao has developed a deep learning algorithm that
assesses the moisture content of fuels.
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