I tried, It required making an account to use.
In this day and age, everybody realises that forcing people to make an account does not count as free. It is paying with personal information.
Readit NewsI tried, It required making an account to use.
In this day and age, everybody realises that forcing people to make an account does not count as free. It is paying with personal information.
I completely agree! Please see the bottom of our post where we offer free access in two ways:
1) Email up to 50 files to yc@realitydefender.com, we’ll scan them for you, no setup required
2) 1-click add to Zoom/Teams (via Appstore) to try detection live in your own calls immediately
Are you sure you guys want to tackle this problem?
This isn’t the type of thing where you build a product doing a lot of work up front, and then spend the rest of its life offering support and new features and relaxing a bit.
You are committing to a cat and mouse game. You will constantly have to stay on top of ever improving tech that gets harder to beat, you will never know peace. You will have to exert more and more effort each year.
This is something we're constantly updating, upgrading, iterating, and improving on. Every. Single. Day.
Whether it's introducing new models, deprecating old ones, or improving existing ones, there is an element of both staying current but also looking ahead at research. Many of the new models generating hyperreal content we catch on day one because they're based on existing technology and/or research.
Interesting that fakes text is not an artifact they support. I can understand there isn’t enough entropy for the detection logic to work may be
It is in fact something we support with our enterprise clients and will roll out at a later date via Public API. Including the free tier.
On a 2k desktop using Chrome, your website font/layout is way too big, especially your consent banner--it takes up 1/3 of the screen.
Noted. Our marketing team only uses 640x480 CRTs and works exclusively in IE6, so will flag to them via Yahoo Messenger.
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How would you detect someone who tests a single image using a new free tier, and then (if successful) uses that image against a targeted customer account?
Working in a similar area (bot detection) I think it's very difficult to proactively stop such targeted attacks, but maybe in this space you can do something interesting like duplicate detection across a consortium.
We'd rather not tip our hand on any/all techniques used to discern actual users from bad actors and those seeking to reverse engineer, but suffice to say we do have are methods (and plenty of them).
And we’ve published peer-reviewed research at top AI conferences E.g. CVPR, NeurIPS, ECCV, AAAI, Interspeech which are available at https://www.realitydefender.com/research