Why So Many Organizations’ Artificial Intelligence Initiatives Fail

2 years ago thenewstack.io

Summary: This is a summary of an article originally published by The New Stack. Read the full original article here →

You’re looking at your iPhone for a particular picture of your friend, taken a couple of years ago. Within seconds you find the picture you’re looking for.

It can be boiled down to three big hurdles: the wrong data in the wrong infrastructure at the wrong time.

New feature engineering — processing data necessary to choose and train models — requires going back to the raw data for different aggregations.

The quality of the models, and their outcomes, increases with the volume of event data ingested.

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