Flagg3D is a platform designed to detect and flag unsuitable and prohibited 3D content on sites, platforms, networks and databases, powered by proprietary shape recognition technology
A new AI tool, Flagg3D, has launched, claiming to trace and flag the digital files of 3D printable gun blueprints for administrators of 3D content sharing and collaboration sites, as well as online 3D printing platforms and bureaux.
Powered by proprietary 3D shape recognition algorithms, the Flagg3D platform states it is able to scan large 3D databases and networks at scale, whilst also analysing inbound 3D designs in real time.
The machine-learning based platform matches against existing known gun parts, as well as similar and related designs, thus identifying and flagging unsuitable content.
Flagg3D is primarily targeted at the moderators and administrators of 3D content sharing and collaboration sites, IT networks, cloud storage services and social media platforms. It is also aimed at 3D printing platforms and 3D printer firmware businesses.
Created by London-based machine vision and AI company 3D Industries Limited, the platform can be deployed and integrated via APIs or accessed as a platform-as-a-service (PaaS) via a dashboard, while Flagg3D is also offering a ‘Seek-and-Flag’ service for those wanting to outsource the process completely.
Speaking at the launch of the platform, 3D Industries CEO Seena Rejal, said: “The challenge posed by the potential release of 3D printed gun files clearly demonstrates the limits and futility of outdated text-based tools for dealing with today’s increasingly 3D web.
“The physical and digital are now more integrated than ever, and this demands far more sophisticated vision and AI solutions for tackling the issues that arise at this intersection.”
“We offer database, network and platform owners and moderators full visibility and knowledge of their systems, allowing them to better protect themselves against policy violations, DMCA take-down notices, or irreparable brand damage. The potential savings in labour, legal and reputational costs are potentially enormous.”
