Wednesday, 24 April, 2019

Google blocks 100m Gmail spam emails with TensorFlow

Google eliminates more spam from Gmail with TensorFlow Google blocked 100m spam Gmail messages using AI
Emmett Howard | 08 February, 2019, 20:08

Since then, "teams and researchers all over the world" have produced a whopping 71,000 forks of the public code and other open-source contributions, establishing a strong community that makes it easy to quickly apply "new research and ideas".

TensorFlow is an open-source machine learning (ML) framework developed at Google, and was launched in 2015.

It an achievement it calls "a feat", Google claims it now blocks an additional 100 million spam emails every day.

Google was already using machine learning to power its spam detection capabilities. It was done by employing artificial intelligence (AI) apart from the traditionally used rule-based filters which block out only the most obvious spam.

One of the more mainstream ideas was to further improve Gmail's already impressive spam protection by adapting quickly to ever-changing, increasingly sophisticated techniques of spreading spammy messages. TensorFlow is also used by companies such as Intel, Qualcomm and Airbnb. It actually results in one extra blocked spam email for every 10 Gmail users, The Verge noted.

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Before implementing TensorFlow-powered protection features, Google's effectiveness in blocking spam, phishing, and malware attempts was pretty great, but now it's essentially flawless.

Google has declared the new technology has allowed it to block spam messages that were previously "very hard to detect", meaning users should be seeing less emails that are unwanted. 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.

What kind of additional spam messages did Google now get better at deflecting?

With TensorFlow, Google can also better personalize its spam protections for each user. The company has now taken help of in-house machine learning system. 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.

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