Cognificance

Cognificance

About the significance of machine cognition

Cognificance

About the significance of machine cognition

Dreaming of "zero Inbox"?

"I have a dream"… about an AI-powered email filter that has a 100% hit rate on spam, prioritizes and classifies the remaining email and possibly answers simple queries automatically.

Current spam filters generally work heuristically or with statistic-driven Bayes filters, which means that they try to detect spam by looking at keywords and semantics of the message. This is why you will find spam messages getting through even high-price professional filter appliances, because the sender has found some creative way to spell a word that a human will immediately be able to interpret but a machine has no chance of understanding.

Not unless AI comes into the mix. The problem here is, of course - as always - that AI requires large sample sets to make proper decisions. Even power-managers with 400 emails per day won't fit this bill and while the central email server of large corporates would have enough daily samples to properly train a deep learning system, apparently no vendor has jumped on this bandwagon (please prove me wrong here!).

A good first step
has just been announced by a Google team led by Ray Kurzweil. A service that has already been available in the browser client version of Gmail is now also available on mobile devices (Android and iOS): if activated, Gmail will suggest three likely responses to any email received. The responses are the output of Google's AI that attaches to Gmail directly. Sample set size? Not an issue here!

I would think a sensible next step is for Google to use the learning set from this endeavor to add additional email services, such as spam filtering and automatic classification. Go, Google, Go!

Now, I'm waiting for YouTube videos of two Gmail accounts talking to one another…
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