Whilst it's perhaps fair to say that AI hasn't eaten the world yet, there have nonetheless been some interesting projects that have made valuable inferences from large data sets. The ability to make these inferences requires large qualities of data to get the algorithm up to speed, but of course, not all organizations have such data sets at their disposal.
This has prompted researchers to experiment with simulated data to see if that can be as effective at training the system as real-world data. This approach has provided fruitful early results but does still nonetheless require a degree of time for the system to learn from the data its presented with.
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