Facebook(NASDAQ: FB) taught Its AI into speak mathYAHOO! #Of_MathJanuary 15, 2020
In fact, I had to redo Calculus 2A four different times in college in order to graduate, mostly because I could never properly calculate a ladder’s rate of acceleration as it fell away from a wall.
You know, the sort of theoretical quandaries that really matter in our day to day lives.
Real superstring stuff.
In effect, FB has taught their neural network to view complex mathematical equations “as a kind of language and then [treat] solutions as a translation problem for sequence-to-sequence neural networks.”
In short, they taught an AI to speak math.
“By training a model to detect patterns in symbolic equations, we believed that a neural network could piece together the clues that led to their solutions, roughly similar to a human’s intuition-based approach to complex problems,” the research team wrote in a blog post released today.
Instead of breaking out the verbs, nouns and adjectives, the system silos the various individual variables.
The researchers focused primarily on solving differential and integration equations, but, because those two flavors of math don’t always have solutions for a given equation, the team had to get tricky in generating training data for the machine learning system.
“For our symbolic integration equations, for example, we flipped the translation approach around: Instead of generating problems and finding their solutions, we generated solutions and found their problem (their derivative), which is a much easier task,” the team wrote and which I vaguely understand.
Still, it apparently worked.
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