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Apple wants AI to make its products smarter


The trouble with data is the sheer quantity of it. IDC once said that if you stored all the data in the world on DVDs you’d have a pile of disks large enough to circle the planet 222 times.

So, how can you winnow junk data out of the stack to make better decisions? That’s one of the problems Apple seems to want to solve.

Inductiv for the rest of us

Apple has confirmed the purchase of a small Ontario-based machine learning start-up called Inductiv with its usual boiler plate statement that it purchases companies like this from time-to-time, and doesn’t want to tell us anything more about it.

The thing is, while Inductiv was small and didn’t have a big footprint, it did have a small cadre of extremely talented employees (most of whom now appear to be working at Apple), and was run by ranking AI professors from Stanford University, the University of Waterloo, and the University of Wisconsin.

We’ve tracked Apple’s AI acquisitions before. This new deal is just the latest in a lengthy trend as the company invests deeply in optimizing machine learning across its systems.

However, the biggest problem with AI is also its biggest top line element – data: Capturing high-quality data is part of the challenge, but figuring out what data is the most useful is also part of that hurdle.

One of the biggest truisms in machine learning/artificial intelligence development is the phrase: “Junk in, junk out.” Bad data, or poorly analyzed data, creates poor results.

Hey Siri, tell me what you know

That’s particularly visible in Siri.

Copyright © 2020 IDG Communications, Inc.


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