When an algorithm isn’t…

An algorithm is a set of steps (the instructions) each of which is simple and well defined, and that stops after a finite number of these steps.

An algorithm is like a recipe. It takes “inputs” (the ingredients), performs a set of simple and (hopefully) well-defined steps, and then terminates after producing an “output” (the meal)

A learning algorithm is a game of roulette on a 50 dimensional wheel that lands on a particular spot (a recipe) based completely on how it was trained, what examples it saw, and how long it took to search.

We’re trying to design algorithms that mimic what humans can do. In the process, we’re designing algorithms that have the same blind spots, unique experiences, and inscrutable behaviors that we do. We can’t just “look at the code” any more than we can unravel our own “code”.



CS prof: interested in algorithms, geometry, and theoryCS

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