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Google uses machine learning to help Gmail users get rid of spam

“Less than 0.1% of email in the average Gmail inbox is spam, and the amount of wanted mail landing in the spam folder is even lower, at under 0.05%,”

Google logo is seen in this file photo. AP

“Even still, Gmail spam detection isn’t perfect. So we’re sharing some of the new ways we are supporting the senders of wanted mail, and using the latest Google smarts to filter out spam,” stated.

Google is launching Gmail Postmaster Tools that help qualified high-volume senders analyse their email, including data on delivery errors, spam reports, and reputation. This way they can diagnose any hiccups, study best practices, and help Gmail route their messages to the right place.

The company said the spam filter now uses an artificial neural network to detect and block the especially sneaky spam—the kind that could actually pass for wanted mail.
“We also recognise that not all inboxes are alike. So while your neighbor may love weekly email newsletters, you may loathe them. With advances in machine learning, the spam filter can now reflect these individual preferences,” the blog post reads.
“Finally, the spam filter is better than ever at rooting out email impersonation—that nasty source of most phishing scams. Thanks to new machine learning signals, Gmail can now figure out whether a message actually came from its sender, and keep bogus email at bay.”

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