Categories
Apple Machine Learning

Machine Learning in practical terms

I noticed the other night that Siri was giving more appropriate answers.

While researching the anecdotal history of some local property, I did what I’ve done previously: ask Siri. In this case, asking about actors dates of birth and death. In the past, these type of questions would have pulled up the relevant IMDB or Wikipedia page with Siri saying “I’ve found some links for you on the web” or similar.

It took several rounds before I realized that, while the pages were still being pulled up as before, Siri was parsing out the answer to the question I’d asked, and gave that to me directly. I never had to glance down or open my phone.

Similarly, in Mail, there is now a predictive mailbox making suggestions (usually accurate) into which email box I might want to move the selected email.

In Calendar, I find addresses being suggested for my events, based on whether I’ve been there or not, address book entries, or other information.

It’s clear to me that these are all improvements related directly the Apple’s increased use of Machine Learning across it’s software products.