Subtracting about 350 duplicate matches, that leaves about 1,500 separate occurrences of "bear arms" in the 17th and 18th centuries, and only a handful don't refer to war, soldiering or organized, armed action.
A company spokesperson noted that photo and video removal is currently performed through exact duplicate matching only, while textual posts are also removed through a machine learning approach.
Instead, they largely result from simple exact duplicate matching, in which once a human moderator deletes a piece of content, it is added to a site-wide blacklist that prevents other users from reuploading it.
The company has to date declined to break out the numbers of what percent of the terrorism content it deletes is simple exact duplicate matching versus actual AI-powered machine learning tools flagging novel material.
Thus, from the media narrative of pioneering new deep learning advances powering bleeding edge AI algorithms that delete 99% of terrorism content, we have the actual reality of the far more mundane story of exact duplicate matching preventing 99% of reuploads and perhaps some machine learning text matching thrown in for good measure.
Likewise, those duplicate matches were defined as incorrect links.
If exact duplicate matches occurred in a pass, one was selected at random (this rarely happened).
All links identified by the selected match keys were accepted as valid, with the exception of duplicate matches.
ReXSpecies 2.0 was used to remove duplicate matches, to find putative homologous matches, and to remove implausible matches such as plant specific transcription factor binding sites in mammals.
All links identified by the selected match keys were accepted as valid, with the exception of the very small number of duplicate matches.
