Through the use of machine learning (ML), the company is able to block 99.9 percent of spam, phishing and malware from ending up in user's inboxes.
Google has said, via the Gmail Blog overnight, that Gmail is already blocking an extra 100 million spam messages every day. It was done by employing artificial intelligence (AI) apart from the traditionally used rule-based filters which block out only the most obvious spam. Moreover, Google, Intel, SAP, Airbnb, and Qualcomm are the top users of this software.
100 MILLION spam messages blocked out every day sounds like a staggeringly high figure, but considering that there are more than 1.5 billion people using Gmail every month, it works out to only ONE extra blocked spam message per 10 users.
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.
TensorFlow also helps Gmail provided more personalised spam detection - for example, if an email is considered spam by one person, it doesn't mean it will be considered spam on your inbox, so Gmail make sure to deal with that appropriately.
Google launched TensorFlow back in 2015 and it has very quickly become an incredibly important part of its AI business. Getting the hand on last bit of spam is increasingly hard, but TensorFlow has been great for terminating that gap.
Tech giant Google is doing everything possible to get rid of spam mails. But with TensorFlow, Gmail can now look out for user signals to train their servers to learn what appears to be spam for each of them out there.
Google has said that, by integrating TensorFlow into Gmail, it can better personalise spam filters and that this is the turning point for understanding spammers signals and "turning those signals into better results". According to the company, it is successful at identifying image-based messages, emails with hidden embedded content, and messages from newly created domains that try to hide a low volume of spammy messages within legitimate traffic.