Google blocked 100m spam Gmail messages using AI

Gmail is Now Blocking 100M Spam Messages Everyday Using Machine Learning

Gmail is Now Blocking 100M Spam Messages Everyday Using Machine Learning

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. The company started using the new filters last month and claims that it has managed to block extra 100 million spam messages every day with its help. The report adds, "TensorFlow makes managing this data at scale easier, while the open-source nature of framework means new research from the community can be quickly integrated". To put it into context, Gmail already blocks 99.99% of spam for its 1 billion plus users, meaning there is still 0.1% of spam that still comes through to users inbox. The rule-based filters are capable of blocking obvious spam, while machine learning look for new patterns which reveal that whether an email is trusted of spam.

"Machine learning one of the most promising technologies powering next generation applications and among the various machine learning frameworks, TensorFlow is one of the most successful and popular", Mueller said. 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 also provides the flexibility to train and experiment with different models in parallel.

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TensorFlow protections complement Google's machine learning and rule-based protections. Implementation of TensorFlow has helped Gmail block image-based messages, emails with hidden embedded content, and messages from newly created domains that try to hide a low volume of spam messages within legitimate traffic. This process has been taking place for years, says Kumaran, with Gmail looking for certain signals from users about what they judge to be spam, but TensorFlow is "turning those signals into better results".

Google continued: "Where did we find these 100 million extra spam messages?"

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.

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