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Google added the ability to measure pressure to its operating system because the data can help improve location finding.
The weakness of the American manufacturing sector often is not recognized — in part, as I've explained, because the data can be confusing.
Because the data can be recorded and retrieved at hundreds of angles within a storage material rather than just on the surface, page after page can be stored on material an inch thick.
Data will not be shared because the data can be used with a specific simulation environment.
Because the data can be trusted, the risk of fraud will be lower and the level of trust will be higher.
For example, we're willing to share information about our musical tastes because the data can be used to help us find new albums, and there is certainly value in having credit card companies exchange otherwise confidential information in order to spot fraud.
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This situation is unfortunate because reusing the data can offer insights into pathways and diseases entirely distinct from those considered in original experimental designs.
Others have panned student-growth percentiles because they say the data can unfairly paint a teacher as ineffective.
Because of auditable logging, the data can never go out of that environment.
I think this will be a constraint to how big the data can get because it will always require an element of human insight.
And because AcceptPay is an online service, the data can be accessed from anywhere.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com