How Google Leverages ML To Block Over 99.9% Spam Messages In Gmail

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With the new filters, Google claims Gmail is now blocking an extra 100 million spam messages every day.

Artificial intelligence, machine learning, and deep learning may still sound like vague concepts or insufficiently mature technologies to impact the average mobile device consumer in truly significant ways, but according to Google, one palpable development already made possible by something called TensorFlow is less spam than ever before in our Gmail inboxes.

This is over and above the 99.9% spam, phishing and malware the company claimed to have blocked out as early as 2015.

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Google has been using AI along with rule-based filters to detect spam for years.

Initially developed for internal Google use, the TensorFlow open-source machine learning (ML) framework was released under the Apache 2.0 license more than three years ago. 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.

"At the scale we're operating at, an additional 100 million is not easy to come by". "Getting the last bit of incremental spam is increasingly hard, [but] TensorFlow has been great for closing that gap".

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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.

By using TensorFlow's AI technology, it make managing data at this scale easier, while the open-source nature of framework means new research from the community can be quickly integrated.

There is no one definition for 'spam,' and that what looks like a spammy message to one user might be a much-awaited mail for another one, and Google is fully aware of the fact. As reported by The Verge, the company says incorporating TensorFlow into Gmail will enable it to personalise spam filters in a better manner. TensorFlow is used to stop image-based messages, emails with hidden embedded content, and messages from newly created domains.

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