Google says it is now blocking close to 100 million more spam messages daily following the recent implementation of TensorFlow, its in-house open-source machine learning AI framework. While rules can help block glaring examples of spam, machine learning can find new patterns that flag a message as not trustworthy.
In fact, the firm has insisted it now blocks 99.9 percent of "spam, phishing, and malware from reaching Gmail inboxes" at the moment.
Additionally, Google also detailed the new kinds of spam messages that are now being thwarted on Gmail. Specifically, Google has used TensorFlow, its open-source machine learning framework, to more efficiently modify its spam detection features.
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.
Neil Kumaran, product manager of Counter Abuse Technology at Google, points out that, "at the scale we're operating at, an additional 100 million is not easy to come by". After all, what one person considers spam might be considered important by another user, Kumaran said.
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. "Getting the last bit of incremental spam is increasingly hard, [but] TensorFlow has been great for closing that gap".
But that 99.9 percent success isn't good enough for Google, which is why it has designed new protections for Gmail powered by TensorFlow. TensorFlow Extended (TFX) is one of these components that allows Google to deploy ML pipelines in a quick and standardized fashion while TensorBoard allows it to monitor model training pipelines and quickly evaluate new models to determine their usefulness.
Even though it may seem trivial, as Google tries to eliminate the remaining 0. As reported by The Verge, the company says incorporating TensorFlow into Gmail will enable it to personalise spam filters in a better manner.