Gmail's already robust spam filtering features are nearing perfection with machine learning

Gmail's already robust spam filtering features are nearing perfection with machine learning

New improvements to protections powered by TensorFlow allow Google to detect and block an additional 100 million spam messages every day. Along with this, Gmail has also been using AI with the rule-based filters.

The platform was launched in 2015 by Google and is an open source framework. TensorFlow is also used by companies such as Intel, Qualcomm and Airbnb. And the tech company says the existing models, in conjunction with other protections, helped block more than 99.9 percent of spam, phishing, and malware from reaching Gmail inboxes.

100 million emails might sound like a lot, but when put into context against Gmail's 1.5 billion users, it only works out at one extra blocked spam email per 10 users, according to The Verge.

Google LLC is beefing up Gmail's anti-spam capabilities with new protections, powered by its machine learning software framework TensorFlow, that are created to complement its existing algorithms.

More news: Amazon's Jeff Bezos accuses National Enquirer publisher of blackmail

This does not dismiss the achievement of TensorFlow, though, as the blocking of the additional nuisance emails suggests that Google's spam-blocking functionality has been enhanced through machine learning. And although Gmail is decent at detecting basic/slightly-complex spam emails, it often struggles to detect spam emails that are disguised as regular emails.

TensorFlow protections complement Google's machine learning and rule-based protections. "But CxOs want to see proof points before adopting technologies, so that's why Google is showcasing its internal uptake of TensorFlow for fighting spam".

Google isn't saying whether TensorFlow will help with the accuracy of spam detection when it comes to flagging non-spam email as spam, but the personalised spam detection should help. This complete process has been taking place for years where Gmail looks for some particular signals from users on the basis of which it judges the spam.

TensorFlow will now help Gmail users to get rid of emails with hidden embedded content, image-based spam and spam laden messages from newly created domains which getaway through the existing filters by managing to send very few messages within legitimated traffic.