Gmail Blocks 100 Millions Of Spam Emails Using AI

Surely if you get into the spam folder in Gmail unavoidably, you will have some unread mail (or many). Even users who take care of ourselves and do not register our emails on doubtful pages have spam, and it is a scourge that has been affecting us for a long time, almost since the beginning of the domestication of the Internet.

But how does Google, for example, to avoid this massive spam email? Because what we see is not one thousandth of what really happens every day: billions of spam emails are launched in the world. And Google has a very effective weapon against them: artificial intelligence.

The AI Against Spam: A Titanic Battle

Google has launched Tensor Flow, its machine learning technology to the task. Specifically, it is responsible for helping to train additional spam filters for Gmail users. With the new filters implemented last month, Google states that Gmail is now blocking more than 100 million spam messages every day.

Although these figures are impressive, can be somewhat short considering that right now there are more than one billion users with Gmail, so it does not seem to be enough. But in figures of the same Google, this is able to block 99.99 percent of spam, so in case these filters did not exist our folders would be full to the brim. We assume that this remaining 00.01 percent is the most difficult to detect.

But this is not new. Google has been using artificial intelligence to establish filters in Gmail for years, following a series of rules. These filters can block the most obvious and easy to detect spam, but being automatic learning, it looks for new patterns to distrust a malicious email. Recall that attackers do not stop trying to get these emails to users so the techniques they use are increasingly advanced and the AI must learn from it.

Google Gmail AI Became More Stronger By Tensorflow

All the metric data that these AI handle are very wide, from the format of an email to the time of day when it is sent. Tensor Flow, according to Google, facilitates the management of this data to scale, while the open source nature of this AI implies that the community can participate and that investigations of this can be included in Tensor Flow easily.

Google is tremendously proud of Tensor Flow, this is a free machine learning framework that allows the developers involved to create artificial intelligence tools for all kinds of purposes. It highlights its flexibility, the ability to scale, and of course its functionality and integration to perfection with the other artificial intelligence services of Google.

Also Read: Google Is Gradually Retiring Google Hangouts For G Suite Users

If someday there comes a time when we do not have to suffer thanks to this method, we will have to raise our hands as a celebration. The problem is that spam is like Tik Tok or those offended on Twitter: you know it’s there no matter how much you do not see it and want to avoid it.

Google AI Become Stronger By Tensorflow
Google AI Become Stronger By Tensorflow (Image Source: Google)

Also Read: Facebook Users Will Get the New Facebook Messenger Redesign

AI Intelligence Smart Identification Of Pattern

  • The automatic learning allows detecting the spam thanks to the identification of patterns that can suggest that an email is suspicious.
  • Algorithms trained in this way balance a large number of metrics, from the format of an email to the time of day it is sent.
  • In this sense, it creates patterns in large data sets making it much more efficient than the rules established by Gmail.
  • Because of this mechanism, Gmail can quickly adapt to spam attempts that are constantly changing.
  • Tensor Flow is an Open Source library launched by Google in 2015 and has currently taken revelation in the environment of solutions based on artificial intelligence.
  • This advance allows Google to block categories of spam that previously cost more work to detect. By using Tensor Flow to scan mails, the company can now find emails created from images, with integrated content and messages from new domains trying to impersonate legitimate issues.
  • Machine learning helps Google detect patterns in large amounts of data that often go unnoticed. In addition, it allows it to adapt to new types of tactics used by those who send these types of malicious emails.

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