Programming a computer is a bit like teaching it how to bake: you give the computer a recipe, and the computer takes care of the rest of the work.
But beyond sheer mathematical calculations, can computers make the same subjective decisions that a human might make: such as a medical diagnosis, a treatment plan proposal, or even an investment or trading decision?
The exploration of how machines can learn by learning from human examples is a fast-growing area of academic research. In the realm of machine learning', the goal is to let computers figure out those programming recipes all by themselves. Perhaps computers will ultimately be capable of solving ideas too complex for the human mind to contemplate, let alone write down. What would that mean for society?
One very popular approach to machine learning is to equip computers with mathematical tools inspired by biological brains. Known as deep neural networks', these tools have been astonishingly successful at teaching computers how to see, speak and think like humans. In fact, deep neural networks work so well that it can be challenging to understand why they are doing what they are doing even for their human creators.
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