On Mon, May 14, 2018 at 09:45:16AM +0000, Curt wrote:
On 2018-05-13, Nathaniel Suchy (Lunorian) <me@lunorian.is> wrote:Have any spam filters attempted to use neural networks? How well did that work out?Apparently, they work quite well (but it seems you need mucho processing power--an "enormous collection of computers"; "massive amounts of hardware and massive amounts of data"). https://www.wired.com/2015/07/google-says-ai-catches-99-9-percent-gmail-spam/ https://www.wired.com/2015/04/jeff-dean/ Perhaps the absorption of a grain of salt might be indicated while perusing these articles, I'm uncertain. Then again maybe a grain of salt is always indicated no matter what the article or source.
I'm no expert in AI, but it was my understanding that, while you need massive amounts of data and processing of that data to CREATE an AI model, the model itself can be relatively modest to run. This, I believe, is how smartphones can now boast "AI processing" for your photos and how Google's "auto-complete your emails" feature works.
So, in theory, someone - such as google - could produce a marketable version of their Great Email AI, which could run on single consumer PC and still benefit from the knowledge of what's spam and what's not.
Perhaps, though, where many Run-It-Yourself spam filters are lacking is in breadth of knowledge. Oftentimes, it is not JUST the text in the email that indicates a message is spam. Has it come from a domain which has only recently been created? Has the sender just sent the same, or nearly the same, message to umpteen different domains? Does the sender normally do this (e.g. it's a mailing list host) or has it just started (e.g. it's infected by a botnet). These days, spam filtering needs to be quite involved in the email server.
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