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Context is an extension of precision in some regards but still merits a place in the conversation especially in cases where humans interact with AI.If you chat with Tay, ask Alexa for information, or look to Inspiro Bot for motivation, you are set in a context where time, place, emotion, weather, identity, company, etc.

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While its domains of applications are far reaching, successfully putting AI into production requires a having very specific problem to solve.

For example, fraud detection can be treated in a very specific manner when used in conjunction with a neural network that has few input and output terms.

Your output terms (transactions) can be limited to fraudulent or non-fraudulent.

Remember, in this type of a situation, you're modeling an algorithm to correctly classify data into two classes.

It could be because of precision, context, or training.

AI has shown it can produce results in all industries — from predicting insurance sales opportunities and reducing medicine research times to automating production lines, optimizing transportation routes, and much much more.

My personal favorite, Inspiro Bot, is designed to provide you with a daily dose of inspiring quotes.

Ironically, the fact it regularly fails at creating motivational messages will most likely lighten up your day.

With such a limited number of possible outputs, it is easier to model an algorithm that will efficiently classify transactions.

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