Hi-Tech

Google cuts out more Gmail spam with TensorFlow

Google cuts out more Gmail spam with TensorFlow

Neil Kumaran, product manager of counter-abuse technology at Google, said: "By complementing our existing ML [machine learning] models with TensorFlow, we're able to refine these models even further, while allowing the team to focus less on the underlying ML framework and more on solving the problem: ridding your inbox of spam".

We're talking a 99.9 percent success rate and an additional 100 million spam messages blocked every day with the help of machine learning technology.

Google has been using AI along with rule-based filters to detect spam for years. Also, it's been open source since 2015, meaning that new innovations and research from the community can be quickly put to work.

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.




Google's Gmail is used by 1.5bn people each month with 5m businesses using the service as part of G Suite and one of the biggest draws of the service is its built-in security protections. TensorFlow is used to stop image-based messages, emails with hidden embedded content, and messages from newly created domains.

Instead of focusing on just a few of an email's characteristics that could seem "spammy" at a first glance or coincidentally fit with general spam-eliminating guidelines and red flags, ML provides a more complete view of suspicious messages, looking at all available signals before making a final determination. 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. This will break the last 0.1% of spam emails from getting through. Google is aiming to simplify the process with TensorFlow.

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. Machine learning also lets Google personalise its protections to each user.